Quantitative High-Throughput Screening for Chemical Toxicity in a Population-Based In Vitro Model

University of North Carolina, Chapel Hill, North Carolina 27599, USA.
Toxicological Sciences (Impact Factor: 3.85). 01/2012; 126(2):578-88. DOI: 10.1093/toxsci/kfs023
Source: PubMed


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.

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    • "Combined in vitro and computational approaches have been proposed to characterize toxicokinetic variability (Wetmore et al. 2013), but these are limited to first-order kinetics and characterization of variability in parent compound dosimetry. Other in vitro approaches to evaluating the extent of and molecular mechanisms for interindividual variability using genetically diverse cell lines have also been proposed (Lock et al. 2012; O’Shea et al. 2011). However, these and other in vitro approaches that do not capture the complexity of whole body toxicokinetics would not be successful for compounds such as TCE. "
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    ABSTRACT: Quantitative estimation of toxicokinetic variability in the human population is a persistent challenge in risk assessment of environmental chemicals. Traditionally, inter-individual differences in the population are accounted for by default assumptions or, in rare cases, are based on human toxicokinetic data. To evaluate the utility of genetically diverse mouse strains for estimating toxicokinetic population variability for risk assessment, using trichloroethylene (TCE) metabolism as a case study. We used data on oxidative and glutathione conjugation metabolism of TCE in 16 inbred and one hybrid mouse strains to calibrate and extend existing physiologically-based pharmacokinetic (PBPK) models. We added one-compartment models for glutathione metabolites and a two-compartment model for dichloroacetic acid (DCA). A Bayesian population analysis of interstrain variability was used to quantify variability in TCE metabolism. Concentration-time profiles for TCE metabolism to oxidative and glutathione conjugation metabolites varied across strains. Median predictions for the metabolic flux through oxidation was less variable (5-fold range) than that through glutathione conjugation (10-fold range). For oxidative metabolites, median predictions of trichloroacetic acid production was less variable (2-fold range) than DCA production (5-fold range), although uncertainty bounds for DCA exceeded the predicted variability. Population PBPK modeling of genetically diverse mouse strains can provide useful quantitative estimates of toxicokinetic population variability. When extrapolated to lower doses more relevant to environmental exposures, mouse population-derived variability estimates for TCE metabolism closely matched population variability estimates previously derived from human toxicokinetic studies with TCE, highlighting the utility of mouse interstrain metabolism studies for addressing toxicokinetic variability.
    Environmental Health Perspectives 02/2014; 122(5). DOI:10.1289/ehp.1307623 · 7.98 Impact Factor
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    • "Caspase 3/7 activity, a marker of apoptosis, and intracellular ATP, a measure of cell viability, were the end points evaluated. qHTS screening in the genetically defined population produced robust results, allowing for cross-compound, -assay, and -individual comparisons (Lock et al. 2012). The generation of high-quality qHTS in vitro cytotoxicity data for these genetically defined cell lines on a large library of compounds demonstrated the potential of this methodology to assess the degree of interindividual variability in toxicity and to explore its genetic determinants. "
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    ABSTRACT: Background: In 2008, the National Institute of Environmental Health Sciences/National Toxicology Program, the U.S. Environmental Protection Agency’s National Center for Computational Toxicology, and the National Human Genome Research Institute/National Institutes of Health Chemical Genomics Center entered into an agreement on “high throughput screening, toxicity pathway profiling, and biological interpretation of findings.” In 2010, the U.S. Food and Drug Administration (FDA) joined the collaboration, known informally as Tox21. Objectives: The Tox21 partners agreed to develop a vision and devise an implementation strategy to shift the assessment of chemical hazards away from traditional experimental animal toxicology studies to one based on target-specific, mechanism-based, biological observations largely obtained using in vitro assays. Discussion: Here we outline the efforts of the Tox21 partners up to the time the FDA joined the collaboration, describe the approaches taken to develop the science and technologies that are currently being used, assess the current status, and identify problems that could impede further progress as well as suggest approaches to address those problems. Conclusion: Tox21 faces some very difficult issues. However, we are making progress in integrating data from diverse technologies and end points into what is effectively a systems-biology approach to toxicology. This can be accomplished only when comprehensive knowledge is obtained with broad coverage of chemical and biological/toxicological space. The efforts thus far reflect the initial stage of an exceedingly complicated program, one that will likely take decades to fully achieve its goals. However, even at this stage, the information obtained has attracted the attention of the international scientific community, and we believe these efforts foretell the future of toxicology.
    Environmental Health Perspectives 04/2013; 121(7). DOI:10.1289/ehp.1205784 · 7.98 Impact Factor
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    • "For examples, Wiesner et al. demonstrated that a novel antimalarial drug fosmidomycin had both in vitro and in vivo synergic effect with clindamycin [10]; Nguyen et al. reported that triple combination of amantadine, ribavirin, and oseltamivir was highly active and synergistic against drug resistant influenza virus strains in vitro [11]. However, as we know for any medicinal herb, they might contain hundreds of ingredients, thus it is unfeasible to screen all possible drug combinations for all possible indications, although high-throughput screening was possible to determine drug combinations [12], it is also much expensive. Another drawback of the existing methods is that these “blind” approaches including molecular biology are costly and time consuming. "
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    ABSTRACT: Background. Clinical trials reveal that multiherb prescriptions of herbal medicine often exhibit pharmacological and therapeutic superiority in comparison to isolated single constituents. However, the synergistic mechanisms underlying this remain elusive. To address this question, a novel systems biology model integrating oral bioavailability and drug-likeness screening, target identification, and network pharmacology method has been constructed and applied to four clinically widely used herbs Radix Astragali Mongolici, Radix Puerariae Lobatae, Radix Ophiopogonis Japonici, and Radix Salviae Miltiorrhiza which exert synergistic effects of combined treatment of cardiovascular disease (CVD). Results. The results show that the structural properties of molecules in four herbs have substantial differences, and each herb can interact with significant target proteins related to CVD. Moreover, the bioactive ingredients from different herbs potentially act on the same molecular target (multiple-drug-one-target) and/or the functionally diverse targets but with potentially clinically relevant associations (multiple-drug-multiple-target-one-disease). From a molecular/systematic level, this explains why the herbs within a concoction could mutually enhance pharmacological synergy on a disease. Conclusions. The present work provides a new strategy not only for the understanding of pharmacological synergy in herbal medicine, but also for the rational discovery of potent drug/herb combinations that are individually subtherapeutic.
    Evidence-based Complementary and Alternative Medicine 11/2012; 2012:519031. DOI:10.1155/2012/519031 · 1.88 Impact Factor
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