The propensity of compounds to produce adverse health effects in humans is generally evaluated using animal-based test methods. Such methods can be relatively expensive, low-throughput, and associated with pain suffered by the treated animals. In addition, differences in species biology may confound extrapolation to human health effects.
The National Toxicology Program and the National Institutes of Health Chemical Genomics Center are collaborating to identify a battery of cell-based screens to prioritize compounds for further toxicologic evaluation.
A collection of 1,408 compounds previously tested in one or more traditional toxicologic assays were profiled for cytotoxicity using quantitative high-throughput screening (qHTS) in 13 human and rodent cell types derived from six common targets of xenobiotic toxicity (liver, blood, kidney, nerve, lung, skin). Selected cytotoxicants were further tested to define response kinetics.
qHTS of these compounds produced robust and reproducible results, which allowed cross-compound, cross-cell type, and cross-species comparisons. Some compounds were cytotoxic to all cell types at similar concentrations, whereas others exhibited species- or cell type–specific cytotoxicity. Closely related cell types and analogous cell types in human and rodent frequently showed different patterns of cytotoxicity. Some compounds inducing similar levels of cytotoxicity showed distinct time dependence in kinetic studies, consistent with known mechanisms of toxicity.
The generation of high-quality cytotoxicity data on this large library of known compounds using qHTS demonstrates the potential of this methodology to profile a much broader array of assays and compounds, which, in aggregate, may be valuable for prioritizing compounds for further toxicologic evaluation, identifying compounds with particular mechanisms of action, and potentially predicting in vivo biological response.
1,536-well; cell viability; NTP 1,408 compound library; PubChem; qHTS; RT-CES
In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation.
modeling; toxicity prediction; structural features; cell viability; caspase-3,7 activation; in vivo toxicity
High-throughput screening (HTS) is increasingly being adopted in academic institutions, where the decoupling of screening and drug development has led to unique challenges, as well as novel uses of instrumentation, assay formulations, and software tools. Advances in technology have made automated unattended screening in the 1536-well plate format broadly accessible and have further facilitated the exploration of new technologies and approaches to screening. A case in point is our recently-developed quantitative high-throughput screening (qHTS) paradigm which tests each library compound at multiple concentrations to construct concentration-response curves (CRCs) generating a comprehensive data set for each assay (Inglese et al, Proc. Natl. Acad. Sci USA 103, 11473–11478). The practical implementation of qHTS for cell-based and biochemical assays across libraries of >100,000 compounds (e.g. between 700,000 –2,000,000 sample wells tested) requires maximal efficiency and miniaturization, and the ability to easily accommodate many different assay formats and screening protocols. Here, we describe the design and utilization of a fully-integrated and automated screening system for qHTS at the NIH Chemical Genomics Center. We report system productivity, reliability, and flexibility, as well as modifications made to increase throughput, add additional capabilities, and address limitations. The combination of this system and qHTS has lead to the generation of over 6 million CRCs from >120 assays in the last three years, and is a technology that can be widely implemented to increase efficiency of screening and lead generation.
quantitative high-throughput screening; screening; qHTS; 1536-well plate; laboratory automation; interleaved screens; laser cytometer
High-throughput screening (HTS) is increasingly being adopted in academic institutions, where the decoupling of screening and drug development has led to unique challenges, as well as novel uses of instrumentation, assay formulations, and software tools. Advances in technology have made automated unattended screening in the 1,536-well plate format broadly accessible and have further facilitated the exploration of new technologies and approaches to screening. A case in point is our recently developed quantitative HTS (qHTS) paradigm, which tests each library compound at multiple concentrations to construct concentration-response curves (CRCs) generating a comprehensive data set for each assay. The practical implementation of qHTS for cell-based and biochemical assays across libraries of > 100,000 compounds (e.g., between 700,000 and 2,000,000 sample wells tested) requires maximal efficiency and miniaturization and the ability to easily accommodate many different assay formats and screening protocols. Here, we describe the design and utilization of a fully integrated and automated screening system for qHTS at the National Institutes of Health's Chemical Genomics Center. We report system productivity, reliability, and flexibility, as well as modifications made to increase throughput, add additional capabilities, and address limitations. The combination of this system and qHTS has led to the generation of over 6 million CRCs from > 120 assays in the last 3 years and is a technology that can be widely implemented to increase efficiency of screening and lead generation.
Tumor Necrosis Factor-α (TNF-α), a secreted cytokine, plays an important role in inflammatory diseases and immune disorders, and is a potential target for drug development. The traditional assays for detecting TNF-α, enzyme linked immunosorbent assay (ELISA) and radioimmunoassay, are not suitable for the large size compound screens. Both assays suffer from a complicated protocol, multiple plate wash steps and/or excessive radioactive waste. A simple and quick measurement of TNF-α production in a cell based assay is needed for high throughput screening to identify the lead compounds from the compound library. We have developed and optimized two homogeneous TNF-α assays using the HTRF (homogeneous time resolved fluorescence) and AlphaLISA assay formats. We have validated the HTRF based TNF-α assay in a 1536-well plate format by screening a library of 1280 pharmacologically active compounds. The active compounds identified from the screen were confirmed in the AlphaLISA TNF-α assay using a bead-based technology. These compounds were also confirmed in a traditional ELISA assay. From this study, several beta adrenergic agonists have been identified as TNF-α inhibitors. We also identified several novel inhibitors of TNF-α, such as BTO-1, CCG-2046, ellipticine, and PD 169316. The results demonstrated that both homogeneous TNF-α assays are robust and suitable for high throughput screening.
AlphaLISA technology; HTRF technology; inhibition of TNF-α production; qHTS; TNF-α; 1536-well plate.
The Cyclic-AMP Response Element Binding (CREB) proteins comprise a family of transcription factors that stimulate or repress the expression of a wide variety of genes by binding to nucleotide sequences known as cAMP Response Elements. CREB-mediated transcription has been implicated in a wide variety of important physiological processes, including long-term memory, and enhancement of CREB signaling has been suggested as an attractive therapeutic strategy for human memory disorders. To identify small molecule compounds that enhance CREB pathway signaling, we have optimized and validated a cell-based β-lactamase reporter gene CREB pathway assay in 1536-well plate format. The LOPAC library of 1280 compounds was screened in triplicate in this assay on a quantitative high throughput screening (qHTS) platform. A variety of compounds which affect known members of the CREB pathway were identified as active, including twelve known phosphodiesterase (PDE) inhibitors, and forskolin, a known activator of adenylate cyclase, thus validating the assay’s performance. This qHTS platform assay will facilitate identification of novel small molecule CREB signaling enhancers, which will be useful for chemical genetic dissection of the CREB pathway and as starting points for potentially memory-enhancing therapeutics.
The Cyclic-AMP Response Element Binding (CREB) proteins comprise a family of transcription factors that stimulate or repress the expression of a wide variety of genes by binding to nucleotide sequences known as cAMP Response Elements (CREs). CREB-mediated transcription has been implicated in a wide variety of important physiological processes, including long-term memory, and enhancement of CREB signaling has been suggested as an attractive therapeutic strategy for human memory disorders. To identify small molecule compounds that enhance CREB pathway signaling, we have optimized and validated a cell-based β-lactamase reporter gene CREB pathway assay in 1536-well plate format. The LOPAC library of 1280 compounds was screened in triplicate in this assay on a quantitative high throughput screening (qHTS) platform. A variety of compounds which affect known members of the CREB pathway were identified as active, including twelve known phosphodiesterase (PDE) inhibitors, and forskolin, a known activator of adenylate cyclase, thus validating the assay’s performance. This qHTS platform assay will facilitate identification of novel small molecule CREB signaling enhancers, which will be useful for chemical genetic dissection of the CREB pathway and as starting points for potentially memory-enhancing therapeutics.
The U.S. Tox21 collaborative program represents a paradigm shift in toxicity testing of chemical compounds from traditional in vivo tests to less expensive and higher throughput in vitro methods to prioritize compounds for further study, identify mechanisms of action, and ultimately develop predictive models for adverse health effects in humans. The NIH Chemical Genomics Center (NCGC) is an integral component of the Tox21 collaboration due to its quantitative high throughput screening (qHTS) paradigm, in which titration-based screening is used to profile hundreds of thousands of compounds per week. Here, we describe the Tox21 collaboration, qHTS-based compound testing, and the various Tox21 screening assays that have been validated and tested at the NCGC to date.
Tox21; National Research Council; National Toxicology Program; toxicity testing; in vitro assays; NIH Roadmap; NIH Chemical Genomics Center; quantitative high-throughput screening
Dengue virus is a mosquito-borne flavivirus that has a large impact in global health. It is considered as one of the medically important arboviruses, and developing a preventive or therapeutic solution remains a top priority in the medical and scientific community. Drug discovery programs for potential dengue antivirals have increased dramatically over the last decade, largely in part to the introduction of high-throughput assays. In this study, we have developed an image-based dengue high-throughput/high-content assay (HT/HCA) using an innovative computer vision approach to screen a kinase-focused library for anti-dengue compounds. Using this dengue HT/HCA, we identified a group of compounds with a 4-(1-aminoethyl)-N-methylthiazol-2-amine as a common core structure that inhibits dengue viral infection in a human liver-derived cell line (Huh-7.5 cells). Compounds CND1201, CND1203 and CND1243 exhibited strong antiviral activities against all four dengue serotypes. Plaque reduction and time-of-addition assays suggests that these compounds interfere with the late stage of viral infection cycle. These findings demonstrate that our image-based dengue HT/HCA is a reliable tool that can be used to screen various chemical libraries for potential dengue antiviral candidates.
Dengue, a re-emergent human disease that places nearly half of the world's population at risk, threatens to further expand in geographical distribution. The lack of an available effective dengue vaccine has encouraged the search for antiviral drugs as an alternative approach. In recent years, drug discovery through high-throughput screening has become a trend in the search for dengue antivirals. In this study, we developed an image-based dengue high-throughput/high-content assay using prevalent viral strains of three dengue serotypes (DENV1, DENV2 and DENV3) isolated from dengue outbreaks in South America and a laboratory-adapted strain of DENV4. We demonstrated the usefulness of our image-based dengue HT/HCA in identifying potential dengue antivirals by screening a small subset of chemical compounds for inhibition of dengue virus infection in a human-derived host cell line (Huh-7.5), and partially characterized their activities against dengue infection in a mosquito host cell line (C6/36), a distantly-related virus (hepatitis C virus), and an unrelated virus that is transmitted by the same mosquito vector (chikungunya virus).
Background: The ability of a substance to induce a toxicological response is better understood by analyzing the response profile over a broad range of concentrations than at a single concentration. In vitro quantitative high throughput screening (qHTS) assays are multiple-concentration experiments with an important role in the National Toxicology Program’s (NTP) efforts to advance toxicology from a predominantly observational science at the level of disease-specific models to a more predictive science based on broad inclusion of biological observations.
Objective: We developed a systematic approach to classify substances from large-scale concentration–response data into statistically supported, toxicologically relevant activity categories.
Methods: The first stage of the approach finds active substances with robust concentration–response profiles within the tested concentration range. The second stage finds substances with activity at the lowest tested concentration not captured in the first stage. The third and final stage separates statistically significant (but not robustly statistically significant) profiles from responses that lack statistically compelling support (i.e., “inactives”). The performance of the proposed algorithm was evaluated with simulated qHTS data sets.
Results: The proposed approach performed well for 14-point-concentration–response curves with typical levels of residual error (σ ≤ 25%) or when maximal response (|RMAX|) was > 25% of the positive control response. The approach also worked well in most cases for smaller sample sizes when |RMAX| ≥ 50%, even with as few as four data points.
Conclusions: The three-stage classification algorithm performed better than one-stage classification approaches based on overall F-tests, t-tests, or linear regression.
activity calls; concentration–response; Hill equation; quantitative high throughput screening; Tox21
To develop efficient approaches for rapid evaluation of chemical toxicity and human health risk of environmental compounds, the National Toxicology Program (NTP) in collaboration with the National Center for Chemical Genomics has initiated a project on high-throughput screening (HTS) of environmental chemicals. The first HTS results for a set of 1,408 compounds tested for their effects on cell viability in six different cell lines have recently become available via PubChem.
We have explored these data in terms of their utility for predicting adverse health effects of the environmental agents.
Methods and results
Initially, the classification k nearest neighbor (kNN) quantitative structure–activity relationship (QSAR) modeling method was applied to the HTS data only, for a curated data set of 384 compounds. The resulting models had prediction accuracies for training, test (containing 275 compounds together), and external validation (109 compounds) sets as high as 89%, 71%, and 74%, respectively. We then asked if HTS results could be of value in predicting rodent carcinogenicity. We identified 383 compounds for which data were available from both the Berkeley Carcinogenic Potency Database and NTP–HTS studies. We found that compounds classified by HTS as “actives” in at least one cell line were likely to be rodent carcinogens (sensitivity 77%); however, HTS “inactives” were far less informative (specificity 46%). Using chemical descriptors only, kNN QSAR modeling resulted in 62.3% prediction accuracy for rodent carcinogenicity applied to this data set. Importantly, the prediction accuracy of the model was significantly improved (72.7%) when chemical descriptors were augmented by HTS data, which were regarded as biological descriptors.
Our studies suggest that combining NTP–HTS profiles with conventional chemical descriptors could considerably improve the predictive power of computational approaches in toxicology.
carcinogenesis; computational toxicology; high-throughput screening; QSAR
The Alamar Blue (AB) assay, which incorporates a redox indicator that causes a fluorescence signal enhancement in response to metabolic activity, is commonly used to assess the viability of mammalian cells. In response to the need for homogeneous, inexpensive, high throughput assays for anti-cancer drug screening, a 1536-well microtiter plate based assay which utilizes the AB fluorescent dye as a measure of cellular growth was developed and validated in 10 µL assay volume. The performance and robustness of the miniaturized assay was assessed using a human Mantle Cell Lymphoma (MCL) cell line in a pilot screen against a library of 2,000 known bioactive chemicals; with an overall Z’ value of 0.89 for assay robustness, several known cytotoxic agents were identified including and not limited to anthracyclines, cardiac glycosides, gamboges, and quinones. To further test the sensitivity of the assay, IC50 determinations were performed in both 384-well and 1536-well formats and the obtained results show a very good correlation between the two density formats. These findings demonstrate that this newly developed assay is simple to set up, robust, highly sensitive and inexpensive. The non-radiometric strategy employed in this study should also offer the potential for the rapid screening, without a wash or a lysis step, of well established and primary tumor cell lines against large chemical libraries using the 1536-well microtiter plates.
Assay; miniaturization; Alamar Blue; cytotoxicity; anthracyclines; screening; HTS; fluorescence; resazurin; cell viability; NCEB1; cancer
Flaviviruses cause severe disease in humans and are a public health priority worldwide. However, no effective therapies or drugs are commercially available yet. Several flavivirus replicon-based assays amenable to high-throughput screening of inhibitors have been reported recently. We developed and performed a replicon-based high-throughput assay for screening small-molecule inhibitors of yellow fever virus (YFV) replication. This assay utilized packaged pseudoinfectious particles containing a YFV replicon that expresses Renilla luciferase in a replication-dependent manner. Several small-molecule compounds with inhibitory activity at micromolar concentrations were identified in the high-throughput screen. These compounds were subsequently tested for their inhibitory activities against YFV replication and propagation in low-throughput assays. Furthermore, YFV mutants that escaped inhibition by two of the compounds were isolated, and in both cases, the mutations were mapped to the NS4B coding region, suggesting a novel inhibitory target for these compounds. This study opens up new avenues for pursuing the nonenzymatic nonstructural proteins as targets for antivirals against YFV and other flaviviruses.
Traditional toxicity testing using animal models is slow, low capacity, expensive and assesses a limited number of endpoints. Such approaches are inadequate to deal with the increasingly large number of compounds found in the environment for which there are no toxicity data. Mechanism-centered high-throughput testing represents an alternative approach to meet this pressing need but is limited by our current understanding of toxicity pathways. Functional toxicogenomics, the global study of the biological function of genes on the modulation of the toxic effect of a compound, can play an important role in identifying the essential cellular components and pathways involved in toxicity response. The combination of the identification of fundamental toxicity pathways and mechanism-centered targeted assays represents an integrated approach to advance molecular toxicology to meet the challenges of toxicity testing in the 21st century.
toxicity testing; functional toxicogenomics; toxicity pathways; barcoding; yeast
The secretory and transmembrane isoforms of Prostatic acid phosphatase (PAP) can dephosphorylate extracellular adenosine 5′-monophosphate (AMP) to adenosine, classifying PAP as an ectonucleotidase. Currently, there are no compounds that inhibit PAP in living cells. To identify small molecule modulators of PAP, we used a 1,536-well based quantitative high-throughput fluorogenic assay to screen the Library of Pharmacologically Active Compounds (LOPAC1280) arrayed as eight-concentration dilution series. This fluorogenic assay used difluoro-4-methylumbelliferyl phosphate (DiFMUP) as substrate and collected data in kinetic mode. Candidate hits were subsequently tested in an orthogonal absorbance-based biochemical assay that used AMP as substrate. From these initial screens, three inhibitors of secretory human (h) and mouse (m)PAP were identified: 8-(4-chlorophenylthio) cAMP (pCPT-cAMP), calmidazolium chloride and nalidixic acid. These compounds did not inhibit recombinant alkaline phosphatase. Of these compounds, only pCPT-cAMP and a related cyclic nucleotide analog [8-(4-chlorophenylthio) cGMP; pCPT-cGMP] inhibited the ectonucleotidase activity of transmembrane PAP in a cell-based assay. These cyclic nucleotides are structurally similar to AMP but cannot be hydrolyzed by PAP. In summary, we identified two cyclic nucleotide analogs that inhibit secretory and transmembrane PAP in vitro and in live cells.
ectonucleotidase; prostatic acid phosphatase; ACPP; pain; nociception
A shift in toxicity testing from in vivo to in vitro may efficiently prioritize compounds, reveal new mechanisms, and enable predictive modeling. Quantitative high-throughput screening (qHTS) is a major source of data for computational toxicology, and our goal in this study was to aid in the development of predictive in vitro models of chemical-induced toxicity, anchored on interindividual genetic variability. Eighty-one human lymphoblast cell lines from 27 Centre d’Etude du Polymorphisme Humain trios were exposed to 240 chemical substances (12 concentrations, 0.26nM–46.0μM) and evaluated for cytotoxicity and apoptosis. qHTS screening in the genetically defined population produced robust and reproducible results, which allowed for cross-compound, cross-assay, and cross-individual comparisons. Some compounds were cytotoxic to all cell types at similar concentrations, whereas others exhibited interindividual differences in cytotoxicity. Specifically, the qHTS in a population-based human in vitro model system has several unique aspects that are of utility for toxicity testing, chemical prioritization, and high-throughput risk assessment. First, standardized and high-quality concentration-response profiling, with reproducibility confirmed by comparison with previous experiments, enables prioritization of chemicals for variability in interindividual range in cytotoxicity. Second, genome-wide association analysis of cytotoxicity phenotypes allows exploration of the potential genetic determinants of interindividual variability in toxicity. Furthermore, highly significant associations identified through the analysis of population-level correlations between basal gene expression variability and chemical-induced toxicity suggest plausible mode of action hypotheses for follow-up analyses. We conclude that as the improved resolution of genetic profiling can now be matched with high-quality in vitro screening data, the evaluation of the toxicity pathways and the effects of genetic diversity are now feasible through the use of human lymphoblast cell lines.
chemical cytotoxicity; apoptosis; HapMap; lymphoblasts; qHTS
The limitations of traditional toxicity testing characterized by high-cost animal models with low-throughput readouts, inconsistent responses, ethical issues, and extrapolability to humans call for alternative strategies for chemical risk assessment. A new strategy using in vitro human cell-based assays has been designed to identify key toxicity pathways and molecular mechanisms leading to the prediction of an in vivo response. The emergence of quantitative high-throughput screening (qHTS) technology has proved to be an efficient way to decompose complex toxicological end points to specific pathways of targeted organs. In addition, qHTS has made a significant impact on computational toxicology in two aspects. First, the ease of mechanism of action identification brought about by in vitro assays has enhanced the simplicity and effectiveness of machine learning, and second, the high-throughput nature and high reproducibility of qHTS have greatly improved the data quality and increased the quantity of training datasets available for predictive model construction. In this review, the benefits of qHTS routinely used in the US Tox21 program will be highlighted. Quantitative structure–activity relationships models built on traditional in vivo data and new qHTS data will be compared and analyzed. In conjunction with the transition from the pilot phase to the production phase of the Tox21 program, more qHTS data will be made available that will enrich the data pool for predictive toxicology. It is perceivable that new in silico toxicity models based on high-quality qHTS data will achieve unprecedented reliability and robustness, thus becoming a valuable tool for risk assessment and drug discovery.
computational toxicology; qHTS; risk assessment; Tox21
Most of current strategies for antiviral therapeutics target the virus specifically and directly, but an alternative approach to drug discovery might be to enhance the immune response to a broad range of viruses. Based on clinical observation in humans and successful genetic strategies in experimental models, we reasoned that an improved interferon (IFN) signaling system might better protect against viral infection. Here we aimed to identify small molecular weight compounds that might mimic this beneficial effect and improve antiviral defense. Accordingly, we developed a cell-based high-throughput screening (HTS) assay to identify small molecules that enhance the IFN signaling pathway components. The assay is based on a phenotypic screen for increased IFN-stimulated response element (ISRE) activity in a fully automated and robust format (Z′>0.7). Application of this assay system to a library of 2240 compounds (including 2160 already approved or approvable drugs) led to the identification of 64 compounds with significant ISRE activity. From these, we chose the anthracycline antibiotic, idarubicin, for further validation and mechanism based on activity in the sub-µM range. We found that idarubicin action to increase ISRE activity was manifest by other members of this drug class and was independent of cytotoxic or topoisomerase inhibitory effects as well as endogenous IFN signaling or production. We also observed that this compound conferred a consequent increase in IFN-stimulated gene (ISG) expression and a significant antiviral effect using a similar dose-range in a cell-culture system inoculated with encephalomyocarditis virus (EMCV). The antiviral effect was also found at compound concentrations below the ones observed for cytotoxicity. Taken together, our results provide proof of concept for using activators of components of the IFN signaling pathway to improve IFN efficacy and antiviral immune defense as well as a validated HTS approach to identify small molecules that might achieve this therapeutic benefit.
Human African Trypanosomiasis (HAT) is caused by two trypanosome species, Trypanosoma brucei rhodesiense and Trypanosoma brucei gambiense. Current drugs available for the treatment of HAT have significant issues related to toxicity, administration regimes with limited effectiveness across species and disease stages, thus there is a considerable need to find alternative drugs. A well recognised approach to identify new drug candidates is high throughput screening (HTS) of large compound library collections.
We describe here the development of a luciferase based viability assay in 384-well plate format suitable for HTS of T.b.brucei. The parameters that were explored to determine the final HTS assay conditions are described in detail and include DMSO tolerability, Z', diluents and cell inoculum density. Reference compound activities were determined for diminazene, staurosporine and pentamidine and compared to previously published IC50 data obtained. The assay has a comparable sensitivity to reference drugs and is more cost effective than the 96-well format currently reported for T.b.brucei.
Due to the reproducibility and sensitivity of this assay it is recommended for potential HTS application. As it is commercially available this assay can also be utilised in many laboratories for both large and small scale screening.
Prostatic acid phosphatase (PAP) is expressed in nociceptive neurons and functions as an ectonucleotidase. Injection of the secretory isoform of PAP has potent antinociceptive effects in mouse models of chronic pain. These data suggested that a small molecule activator of PAP may have utility as a novel therapeutic for chronic pain, while inhibitors could be used to acutely inhibit PAP in vitro and in vivo. To identify small molecule modulators of PAP activity, we validated a high throughput, fluorescence-based biochemical assay and then used this assay to screen a compound library. We decreased the frequency of false positive activators by subtracting compound fluorescence from the final assay fluorescence. This approach significantly reduced the number of false positive activators found in the screen. While no activators were confirmed, seven novel inhibitors of PAP were identified. Our results suggest this high throughput assay could be used to identify small molecule modulators of PAP activity.
Chemical toxicity testing is being transformed by advances in biology and computer modeling, concerns over animal use, and the thousands of environmental chemicals lacking toxicity data. The U.S. Environmental Protection Agency’s ToxCast program aims to address these concerns by screening and prioritizing chemicals for potential human toxicity using in vitro assays and in silico approaches.
This project aims to evaluate the use of in vitro assays for understanding the types of molecular and pathway perturbations caused by environmental chemicals and to build initial prioritization models of in vivo toxicity.
We tested 309 mostly pesticide active chemicals in 467 assays across nine technologies, including high-throughput cell-free assays and cell-based assays, in multiple human primary cells and cell lines plus rat primary hepatocytes. Both individual and composite scores for effects on genes and pathways were analyzed.
Chemicals displayed a broad spectrum of activity at the molecular and pathway levels. We saw many expected interactions, including endocrine and xenobiotic metabolism enzyme activity. Chemicals ranged in promiscuity across pathways, from no activity to affecting dozens of pathways. We found a statistically significant inverse association between the number of pathways perturbed by a chemical at low in vitro concentrations and the lowest in vivo dose at which a chemical causes toxicity. We also found associations between a small set of in vitro assays and rodent liver lesion formation.
This approach promises to provide meaningful data on the thousands of untested environmental chemicals and to guide targeted testing of environmental contaminants.
in vitro screening; liver proliferative lesions; liver tumors; pathways; ToxCast
Legislation at state, federal, and international levels is requiring rapid evaluation of the toxicity of numerous chemicals. Whole-animal toxicologic studies cannot yield the necessary throughput in a cost-effective fashion, leading to a critical need for a faster and more cost-effective toxicologic evaluation of xenobiotics.
We tested whether mechanistically based screening assays can rapidly provide information on the potential for compounds to affect key enzymes and receptor targets, thus identifying those compounds requiring further in-depth analysis.
A library of 176 synthetic chemicals was prepared and examined in a high-throughput screening (HTS) manner using nine enzyme-based and five receptor-based bioassays.
All the assays have high Z′ values, indicating good discrimination among compounds in a reliable fashion, and thus are suitable for HTS assays. On average, three positive hits were obtained per assay. Although we identified compounds that were previously shown to inhibit a particular enzyme class or receptor, we surprisingly discovered that triclosan, a microbiocide present in personal care products, inhibits carboxylesterases and that dichlone, a fungicide, strongly inhibits the ryanodine receptors.
Considering the need to rapidly screen tens of thousands of anthropogenic compounds, our study shows the feasibility of using combined HTS assays as a novel approach toward obtaining toxicologic data on numerous biological end points. The HTS assay approach is very useful to quickly identify potentially hazardous compounds and to prioritize them for further in-depth studies.
bioassays; biomarkers; enzyme inhibition; high-throughput assays; triclocarban; triclosan
APE1 is the major nuclease for excising abasic (AP) sites and particular 3′-obstructive termini from DNA, and is an integral participant in the base excision repair (BER) pathway. BER capacity plays a prominent role in dictating responsiveness to agents that generate oxidative or alkylation DNA damage, as well as certain chain-terminating nucleoside analogs and 5-fluorouracil. We describe within the development of a robust, 1536-well automated screening assay that employs a deoxyoligonucleotide substrate operating in the red-shifted fluorescence spectral region to identify APE1 endonuclease inhibitors. This AP site incision assay was used in a titration-based high-throughput screen of the Library of Pharmacologically Active Compounds (LOPAC1280), a collection of well-characterized, drug-like molecules representing all major target classes. Prioritized hits were authenticated and characterized via two high-throughput screening assays – a Thiazole Orange fluorophore-DNA displacement test and an E. coli endonuclease IV counterscreen – and a conventional, gel-based radiotracer incision assay. The top, validated compounds, i.e. 6-hydroxy-DL-DOPA, Reactive Blue 2 and myricetin, were shown to inhibit AP site cleavage activity of whole cell protein extracts from HEK 293T and HeLa cell lines, and to enhance the cytotoxic and genotoxic potency of the alkylating agent methylmethane sulfonate. The studies herein report on the identification of novel, small molecule APE1-targeted bioactive inhibitor probes, which represent initial chemotypes towards the development of potential pharmaceuticals.
Ovarian cancer stem cells are characterized by self-renewal capacity, ability to differentiate into distinct lineages, as well as higher invasiveness and resistance to many anticancer agents. Since they may be responsible for the recurrence of ovarian cancer after initial response to chemotherapy, development of new therapies targeting this special cellular subpopulation embedded within bulk ovarian cancers is warranted.
A high-throughput screening (HTS) campaign was performed with 825 compounds from the Mechanistic Set chemical library [Developmental Therapeutics Program (DTP)/National Cancer Institute (NCI)] against ovarian cancer stem-like cells (CSC) using a resazurin-based cell cytotoxicity assay. Identified sets of active compounds were projected onto self-organizing maps to identify their putative cellular response groups.
From 793 screening compounds with evaluable data, 158 were found to have significant inhibitory effects on ovarian CSC. Computational analysis indicates that the majority of these compounds are associated with mitotic cellular responses.
Our HTS has uncovered a number of candidate compounds that may, after further testing, prove effective in targeting both ovarian CSC and their more differentiated progeny.
High-throughput screening; Ovarian cancer; Cancer stem cells
Assessing the potential health risks of environmental chemical compounds is an expensive undertaking which has motivated the development of new alternatives to traditional in vivo toxicological testing. One approach is to stage the evaluation, beginning with less expensive and higher throughput in vitro testing before progressing to more definitive trials. In vitro testing can be used to generate a hypothesis about a compound's mechanism of action, which can then be used to design an appropriate in vivo experiment. Here we begin to address the question of how to design such a battery of in vitro cell-based assays by combining data from two different types of assays, cell viability and caspase activation, with the aim of elucidating mechanism of action. Because caspase activation is a transient event during apoptosis, it is not possible to design a single end-point assay protocol that would identify all instances of compound-induced caspase activation. Nevertheless, useful information about compound mechanism of action can be obtained from these assays in combination with cell viability data. Unsupervised clustering in combination with Dunn's cluster validity index is a robust method for identifying mechanisms of action without requiring any a priori knowledge about mechanisms of toxicity. The performance of this clustering method is evaluated by comparing the clustering results against literature annotations of compound mechanisms.
cell-based assay; cell viability; caspase-3/7; apoptosis; qHTS; mechanism of action