In vertebrates, the retinol (vitamin A) signaling pathway (RSP) controls the biosynthesis and catabolism of all-trans retinoic acid (atRA), which regulates transcription of genes essential for embryonic development. Chemicals that interfere with the RSP to cause abnormal intracellular levels of atRA are potential developmental toxicants. To assess chemicals for the ability to interfere with retinol signaling, we have developed a cell-based RARE (Retinoic Acid Response Element) reporter gene assay to identify RSP disruptors. To validate this assay in a quantitative high-throughput screening (qHTS) platform, we screened the Library of Pharmacologically Active Compounds (LOPAC) in both agonist and antagonist modes. The screens detected known RSP agonists, demonstrating assay reliability, and also identified novel RSP agonists including kenpaullone, niclosamide, PD98059 and SU4312, and RSP antagonists including Bay 11-7085, LY294002, 3,4-Methylenedioxy-β-nitrostyrene, and topoisomerase inhibitors (camptothecin, topotecan, amsacrine hydrochloride, and idarubicin). When evaluated in the P19 pluripotent cell, these compounds were found to affect the expression of the Hoxa1 gene that is essential for embryo body patterning. These results show that the RARE assay is an effective qHTS approach for screening large compound libraries to identify chemicals that have the potential to adversely affect embryonic development through interference with retinol signaling.

Target-specific, mechanism-oriented in vitro assays post a promising alternative to traditional animal toxicology studies. Here we report the first comprehensive analysis of the Tox21 effort, a large-scale in vitro toxicity screening of chemicals. We test ∼ 10,000 chemicals in triplicates at 15 concentrations against a panel of nuclear receptor and stress response pathway assays, producing more than 50 million data points. Compound clustering by structure similarity and activity profile similarity across the assays reveals structure-activity relationships that are useful for the generation of mechanistic hypotheses. We apply structural information and activity data to build predictive models for 72 in vivo toxicity end points using a cluster-based approach. Models based on in vitro assay data perform better in predicting human toxicity end points than animal toxicity, while a combination of structural and activity data results in better models than using structure or activity data alone. Our results suggest that in vitro activity profiles can be applied as signatures of compound mechanism of toxicity and used in prioritization for more in-depth toxicological testing.

New strategies targeting Plasmodium falciparum gametocytes, the sexual-stage parasites that are responsible for malaria transmission, are needed to eradicate this disease. Most commonly used antimalarials are ineffective against P. falciparum gametocytes, allowing patients to continue to be infectious for over a week after asexual parasite clearance. A recent screen for gametocytocidal compounds demonstrated that the carboxylic polyether ionophore maduramicin is active at low nanomolar concentrations against P. falciparum sexual stages. In this study, we showed that maduramicin has an EC50 (effective concentration that inhibits the signal by 50%) of 14.8 nM against late-stage gametocytes and significantly blocks in vivo transmission in a mouse model of malaria transmission. In contrast to other reported gametocytocidal agents, maduramicin acts rapidly in vitro, eliminating gametocytes and asexual schizonts in less than 12 h without affecting uninfected red blood cells (RBCs). Ring stage parasites are cleared by 24 h. Within an hour of drug treatment, 40% of the normally crescent-shaped gametocytes round up and become spherical. The number of round gametocytes increases to >60% by 2 h, even before a change in membrane potential as monitored by MitoProbe DiIC1 (5) is detectable. Maduramicin is not preferentially taken up by gametocyte-infected RBCs compared to uninfected RBCs, suggesting that gametocytes are more sensitive to alterations in cation concentration than RBCs. Moreover, the addition of 15.6 nM maduramicin enhanced the gametocytocidal activity of the pyrazoleamide PA21A050, which is a promising new antimalarial candidate associated with an increase in intracellular Na(+) concentration that is proposed to be due to inhibition of PfATP4, a putative Na(+) pump. These results underscore the importance of cation homeostasis in sexual as well as asexual intraerythrocytic-stage P. falciparum parasites and the potential of targeting this pathway for drug development.

Nuclear receptors (NRs) are ligand-activated transcriptional regulators that play vital roles in key biological processes such as growth, differentiation, metabolism, reproduction, and morphogenesis. Disruption of NRs can result in adverse health effects such as NR-mediated endocrine disruption. A comprehensive understanding of core transcriptional targets regulated by NRs helps to elucidate their key biological processes in both toxicological and therapeutic aspects. In this study, we applied a probabilistic graphical model to identify the transcriptional targets of NRs and the biological processes they govern. The Tox21 program profiled a collection of approximate 10 000 environmental chemicals and drugs against a panel of human NRs in a quantitative high-throughput screening format for their NR disruption potential. The Japanese Toxicogenomics Project, one of the most comprehensive efforts in the field of toxicogenomics, generated large-scale gene expression profiles on the effect of 131 compounds (in its first phase of study) at various doses, and different durations, and their combinations. We applied author-topic model to these 2 toxicological datasets, which consists of 11 NRs run in either agonist and/or antagonist mode (18 assays total) and 203 in vitro human gene expression profiles connected by 52 shared drugs. As a result, a set of clusters (topics), which consists of a set of NRs and their associated target genes were determined. Various transcriptional targets of the NRs were identified by assays run in either agonist or antagonist mode. Our results were validated by functional analysis and compared with TRANSFAC data. In summary, our approach resulted in effective identification of associated/affected NRs and their target genes, providing biologically meaningful hypothesis embedded in their relationships.

BACKGROUND: Hepatotoxicity accounts for a substantial number of drugs being withdrawn from the market. Using traditional animal models to detect hepatotoxicity is expensive and time-consuming. Alternative in vitro methods, in particular cell-based high-throughput screening (HTS) studies, have provided the research community with a large amount of data from toxicity assays. Among the various assays used to screen potential toxicants is the antioxidant response element beta lactamase reporter gene assay (ARE-bla), which identifies chemicals that have the potential to induce oxidative stress and was used to test > 10,000 compounds from the Tox21 program. OBJECTIVE: The ARE-bla computational model and HTS data from a big data source (PubChem) were used to profile environmental and pharmaceutical compounds with hepatotoxicity data. METHODS: Quantitative structure-activity relationship (QSAR) models were developed based on ARE-bla data. The models predicted the potential oxidative stress response for known liver toxicants when no ARE-bla data were available. Liver toxicants were used as probe compounds to search PubChem Bioassay and generate a response profile, which contained thousands of bioassays (> 10 million data points). By ranking the in vitro-in vivo correlations (IVIVCs), the most relevant bioassay(s) related to hepatotoxicity were identified. RESULTS: The liver toxicants profile contained the ARE-bla and relevant PubChem assays. Potential toxicophores for well-known toxicants were created by identifying chemical features that existed only in compounds with high IVIVCs. CONCLUSION: Profiling chemical IVIVCs created an opportunity to fully explore the source-to-outcome continuum of modern experimental toxicology using cheminformatics approaches and big data sources. CITATION: Kim MT, Huang R, Sedykh A, Wang W, Xia M, Zhu H. 2016. Mechanism profiling of hepatotoxicity caused by oxidative stress using antioxidant response element reporter gene assay models and big data. Environ Health Perspect 124:634-641; http://dx.doi.org/10.1289/ehp.1509763.

We demonstrate a computational network model that integrates 18 in vitro, high-throughput screening assays measuring estrogen receptor (ER) binding, dimerization, chromatin binding, transcriptional activation, and ER-dependent cell proliferation. The network model uses activity patterns across the in vitro assays to predict whether a chemical is an ER agonist or antagonist, or is otherwise influencing the assays through a manner dependent on the physics and chemistry of the technology platform ("assay interference"). The method is applied to a library of 1812 commercial and environmental chemicals, including 45 ER positive and negative reference chemicals. Among the reference chemicals, the network model correctly identified the agonists and antagonists with the exception of very weak compounds whose activity was outside the concentration range tested. The model agonist score also correlated with the expected potency class of the active reference chemicals. Of the 1812 chemicals evaluated, 111 (6.1%) were predicted to be strongly ER active in agonist or antagonist mode. This dataset and model were also used to begin a systematic investigation of assay interference. The most prominent cause of false-positive activity (activity in an assay that is likely not due to interaction of the chemical with ER) is cytotoxicity. The model provides the ability to prioritize a large set of important environmental chemicals with human exposure potential for additional in vivo endocrine testing. Finally, this model is generalizable to any molecular pathway for which there are multiple upstream and downstream assays available.

The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal.

DNA repair pathways play a critical role in maintaining cellular homeostasis by repairing DNA damage induced by endogenous processes and xenobiotics, including environmental chemicals. Induction of DNA damage may lead to genomic instability, disruption of cellular homeostasis and potentially tumours. Isogenic chicken DT40 B-lymphocyte cell lines deficient in DNA repair pathways can be used to identify genotoxic compounds and aid in characterising the nature of the induced DNA damage. As part of the US Tox21 program, we previously optimised several different DT40 isogenic clones on a high-throughput screening platform and confirmed the utility of this approach for detecting genotoxicants by measuring differential cytotoxicity in wild-type and DNA repair-deficient clones following chemical exposure. In the study reported here, we screened the Tox21 10K compound library against two isogenic DNA repair-deficient DT40 cell lines (KU70 (-/-) /RAD54 (-/-) and REV3 (-/-) ) and the wild-type cell line using a cell viability assay that measures intracellular adenosine triphosphate levels. KU70 and RAD54 are genes associated with DNA double-strand break repair processes, and REV3 is associated with translesion DNA synthesis pathways. Active compounds identified in the primary screening included many well-known genotoxicants (e.g. adriamycin, melphalan) and several compounds previously untested for genotoxicity. A subset of compounds was further evaluated by assessing their ability to induce micronuclei and phosphorylated H2AX. Using this comprehensive approach, three compounds with previously undefined genotoxicity-2-oxiranemethanamine, AD-67 and tetraphenylolethane glycidyl ether-were identified as genotoxic. These results demonstrate the utility of this approach for identifying and prioritising compounds that may damage DNA.

Invading pathogens trigger specific host responses, an understanding of which might identify genes that function in pathogen recognition and elimination. In this study, we performed trans-species expression quantitative trait locus (ts-eQTL) analysis using genotypes of the Plasmodium yoelii malaria parasite and phenotypes of mouse gene expression. We significantly linked 1,054 host genes to parasite genetic loci (LOD score ≥ 3.0). Using LOD score patterns, which produced results that differed from direct expression-level clustering, we grouped host genes that function in related pathways, allowing functional prediction of unknown genes. As a proof of principle, 14 of 15 randomly selected genes predicted to function in type I interferon (IFN-I) responses were experimentally validated using overexpression, small hairpin RNA knockdown, viral infection, and/or infection of knockout mice. This study demonstrates an effective strategy for studying gene function, establishes a functional gene database, and identifies regulators in IFN-I pathways.

Phenotypic assays have a proven track record for generating leads that become first-in-class therapies. Whole cell assays that inform on a phenotype or mechanism also possess great potential in drug repositioning studies by illuminating new activities for the existing pharmacopeia. The National Center for Advancing Translational Sciences (NCATS) pharmaceutical collection (NPC) is the largest reported collection of approved small molecule therapeutics that is available for screening in a high-throughput setting. Via a wide-ranging collaborative effort, this library was analyzed in the Open Innovation Drug Discovery (OIDD) phenotypic assay modules publicly offered by Lilly. The results of these tests are publically available online at www.ncats.nih.gov/expertise/preclinical/pd2 and via the PubChem Database (https://pubchem.ncbi.nlm.nih.gov/) (AID 1117321). Phenotypic outcomes for numerous drugs were confirmed, including sulfonylureas as insulin secretagogues and the anti-angiogenesis actions of multikinase inhibitors sorafenib, axitinib and pazopanib. Several novel outcomes were also noted including the Wnt potentiating activities of rotenone and the antifolate class of drugs, and the anti-angiogenic activity of cetaben.