High-throughput Toxicity Testing Research Articles

Predictive value of the ToxCast/Tox21 high throughput toxicity screening data for approximating in vivo ecotoxicity endpoints and ecotoxicological risk in eco- surveillance applications

Ecotoxicology has long relied on assessing the hazard potential of chemicals through traditional in vivo testing methods to understand the possible risk exposure could pose to ecological taxa. In the past decade, the development of non-animal new approach methods (NAMs) for assessing chemical hazard and risk has quickly grown. These methods are often cheaper and faster than traditional toxicity testing, and thus are amenable to high-throughput toxicity testing (HTT), resulting in large datasets. The ToxCast/Tox21 HTT programs have produced in vitro data for thousands of chemicals covering a large space of biological activity. The relevance of these data to in vivo mammalian toxicity has been much explored. Interest has also grown in using these data to evaluate the risk of environmental exposures to taxa of ecological importance such as fish, aquatic invertebrates, etc.; particularly for the purpose of estimating the risk of exposure from real-world complex mixtures. Understanding the relationship and relative sensitivity of NAMs versus standardized ecotoxicological whole organism models is a key component of performing reliable read-across from mammalian in vitro data to ecotoxicological in vivo data. In this work, we explore the relationship between in vivo ecotoxicity data from several publicly available databases and the ToxCast/Tox21 data. We also performed several case studies in which we compare how using different ecotoxicity datasets, whether traditional or ToxCast-based, affects risk conclusions based on exposure to complex mixtures derived from existing large-scale chemical monitoring data. Generally, predictive value of ToxCast data for traditional in vivo endpoints (EPs) was poor (r ≤ 0.3). Risk conclusions, including identification of different chemical risk drivers and prioritized monitoring sites, were different when using HTT data vs. traditional in vivo data.

Harnessing Human Pluripotent Stem Cell-Derived Pancreatic In Vitro Models for High-Throughput Toxicity Testing and Diabetes Drug Discovery.

The long-standing goals in diabetes research are to improve β-cell survival, functionality and increase β-cell mass. Current strategies to manage diabetes progression are still not ideal for sustained maintenance of normoglycemia, thereby increasing demand for the development of novel drugs. Available pancreatic cell lines, cadaveric islets, and their culture methods and formats, either 2D or 3D, allow for multiple avenues of experimental design to address diverse aims in the research setting. More specifically, these pancreatic cells have been employed in toxicity testing, diabetes drug screens, and with careful curation, can be optimized for use in efficient high-throughput screenings (HTS). This has since spearheaded the understanding of disease progression and related mechanisms, as well as the discovery of potential drug candidates which could be the cornerstone for diabetes treatment. This book chapter will touch on the pros and cons of the most widely used pancreatic cells, including the more recent human pluripotent stem cell-derived pancreatic cells, and HTS strategies (cell models, design, readouts) that can be used for the purpose of toxicity testing and diabetes drug discovery.

In vitro airway models from mice, rhesus macaques, and humans maintain species differences in xenobiotic metabolism and cellular responses to naphthalene.

The translational value of high-throughput toxicity testing will depend on pharmacokinetic validation. Yet, popular in vitro airway epithelia models were optimized for structure and mucociliary function without considering the bioactivation or detoxification capabilities of lung-specific enzymes. This study evaluated xenobiotic metabolism maintenance within differentiated air-liquid interface (ALI) airway epithelial cell cultures (human bronchial; human, rhesus, and mouse tracheal), isolated airway epithelial cells (human, rhesus, and mouse tracheal; rhesus bronchial), and ex vivo microdissected airways (rhesus and mouse) by measuring gene expression, glutathione content, and naphthalene metabolism. Glutathione levels and detoxification gene transcripts were measured after 1-h exposure to 80 µM naphthalene (a bioactivated toxicant) or reactive naphthoquinone metabolites. Glutathione and glutathione-related enzyme transcript levels were maintained in ALI cultures from all species relative to source tissues, while cytochrome P450 monooxygenase gene expression declined. Notable species differences among the models included a 40-fold lower total glutathione content for mouse ALI trachea cells relative to human and rhesus; a higher rate of naphthalene metabolism in mouse ALI cultures for naphthalene-glutathione formation (100-fold over rhesus) and naphthalene-dihydrodiol production (10-fold over human); and opposite effects of 1,2-naphthoquinone exposure in some models-glutathione was depleted in rhesus tissue but rose in mouse ALI samples. The responses of an immortalized bronchial cell line to naphthalene and naphthoquinones were inconsistent with those of human ALI cultures. These findings of preserved species differences and the altered balance of phase I and phase II xenobiotic metabolism among the characterized in vitro models should be considered for future pulmonary toxicity testing.

Co-culture of human alveolar epithelial (A549) and macrophage (THP-1) cells to study the potential toxicity of ambient PM2.5: a comparison of growth under ALI and submerged conditions.

Fine particulate matter (PM2.5) in the ambient atmosphere is strongly associated with detrimental health effects. However, these particles from various sources and regions are unlikely equally toxic. While animal studies are impractical for high-throughput toxicity testing, appropriate in vitro models are urgently needed. Co-culture of A549 and THP-1 macrophages grown at air-liquid interface (ALI) or under submerged conditions was exposed to same concentrations of ambient PM2.5 to provide accurate comparisons between culture methods. Following 24-h incubation with PM2.5 collected in Harbin in China, biological endpoints being investigated include cytotoxicity, reactive oxygen species (ROS) levels and pro-inflammatory mediators. The co-culture grown under submerged condition demonstrated a significant increase in ROS levels and all tested pro-inflammatory indicators [interleukin (IL)-1β, IL-6, IL-8 and tumor necrosis factor-α] in mRNA expression and released protein levels. Similar but a declining response trend was observed using the same PM2.5 incubation after grown at ALI. We further observed a significant increase of PM2.5-induced phosphorylation of p38 MAPK and activation of NF-κB p65 in a dose-dependent trend for co-cultures grown under submerged condition. These results provide important implications that culture conditions (ALI versus submerged) can induce different extents of biological responses to ambient PM2.5; the co-culture grown at ALI is less likely to produce false-positive results than submerged culture. Hence, culture conditions should be discussed when comparing in vitro methods used for high-throughput PM2.5 toxicity assessment in future.

Drug Discovery Applications: A Customized Digital Microfluidic Biochip Architecture/CAD Flow

Digital Microfluidic Biochips (DMFBs) have significant potential to accelerate a wide range of drug discovery applications, including high-throughput screening, toxicity testing, and drug designing and development. On the other hand, the conventional approach for drug discovery is very time-consuming and error prone. For these applications, current DMFB architectures should be customized to speed up the drug discovery processes and reduce the cost and error of these reactions. Because many drug-related assays repetitively and concurrently use some operations, we developed a new DMFB architecture and the corresponding CAD flow for drug discovery applications. This architecture can accelerate the process by parallelizing the operations, decreasing the area and costs, and improving the execution time of bioassays.

A Chemical Category-Based Prioritization Approach for Selecting 75 Per- and Polyfluoroalkyl Substances (PFAS) for Tiered Toxicity and Toxicokinetic Testing.

Summary:Per- and polyfluoroalkyl substances (PFASs) are a group of fluorinated substances of interest to researchers, regulators, and the public due to their widespread presence in the environment. A few PFASs have comparatively extensive amounts of human epidemiological, exposure, and experimental animal toxicity data (e.g., perfluorooctanoic acid), whereas little toxicity and exposure information exists for much of the broader set of PFASs. Given that traditional approaches to generate toxicity information are resource intensive, new approach methods, including in vitro high-throughput toxicity (HTT) testing, are being employed to inform PFAS hazard characterization and further (in vivo) testing. The U.S. Environmental Protection Agency (EPA) and the National Toxicology Program (NTP) are collaborating to develop a risk-based approach for conducting PFAS toxicity testing to facilitate PFAS human health assessments. This article describes the construction of a PFAS screening library and the process by which a targeted subset of 75 PFASs were selected. Multiple factors were considered, including interest to the U.S. EPA, compounds within targeted categories, structural diversity, exposure considerations, procurability and testability, and availability of existing toxicity data. Generating targeted HTT data for PFASs represents a new frontier for informing priority setting. https://doi.org/10.1289/EHP4555

Primary green turtle (Chelonia mydas) skin fibroblasts as an in vitro model for assessing genotoxicity and oxidative stress

Little is known about the effects of contaminants that accumulate in sea turtles. When in vivo exposure studies have ethical and logistical barriers, as is the case with sea turtles, in vitro tools can provide important information on the effects of contaminants. Several in vitro studies have assessed cytotoxicity of contaminants to sea turtles cells, however to gain a more refined mechanistic understanding of the effects of contaminants, sub-lethal effects also require investigation. Considering the complex mixture of contaminants that sea turtles are potentially exposed to, high throughput testing methods are necessary so that a large number of contaminants (and mixtures) can be rapidly tested. This study examined oxidative stress (reactive oxygen species production) and genotoxicity (micronucleus formation) in primary green turtle skin fibroblasts in response to 16 organic and inorganic contaminants found in coastal environments. Significant induction of oxidative stress was found with Cu, Co, Cr, and Hg. Significant effects on genotoxicity were found with Cu, Co, Cr, Hg, Pb and metolachlor. Effect concentrations from the bioassays were used in a simple risk assessment of turtles worldwide using accumulation values from the literature to identify populations at risk. Cu, Co, Cr and Hg were identified as posing the biggest threat to sea turtles. This study demonstrated the validity of using primary turtle cell cultures in the assessment of risk associated with a large number of contaminants using a high-throughput toxicity testing format.

Bayesian additive adaptive basis tensor product models for modeling high dimensional surfaces: an application to high-throughput toxicity testing.

Many modern datasets are sampled with error from complex high-dimensional surfaces. Methods such as tensor product splines or Gaussian processes are effective and well suited for characterizing a surface in two or three dimensions, but they may suffer from difficulties when representing higher dimensional surfaces. Motivated by high throughput toxicity testing where observed dose-response curves are cross sections of a surface defined by a chemical's structural properties, a model is developed to characterize this surface to predict untested chemicals' dose-responses. This manuscript proposes a novel approach that models the multidimensional surface as a sum of learned basis functions formed as the tensor product of lower dimensional functions, which are themselves representable by a basis expansion learned from the data. The model is described and a Gibbs sampling algorithm is proposed. The approach is investigated in a simulation study and through data taken from the US EPA's ToxCast high throughput toxicity testing platform.

High-throughput toxicity testing of chemicals and mixtures in organotypic multi-cellular cultures of primary human hepatic cells

High-throughput screening (HTS) of liver toxicants can bridge the gap in understanding adverse effects of chemicals on humans. Toxicity testing of mixtures is time consuming and expensive, since the number of possible combinations increases exponentially with the number of chemicals. The combination of organotypic culture models (OCMs) and HTS assays can lead to the rapidly evaluation of chemical toxicity in a cost and time-effective manner while prioritizing chemicals that warrant additional investigation. We describe the design, assembly and toxicant response of multi-cellular hepatic organotypic culture models comprised of primary human or rat cells assembled in 96-well plates (denoted as μOCMs). These models were assembled using automated procedures that did not affect hepatocyte function or viability, rendering them ideal for large-scale toxicity evaluations. Rat μOCMs were assembled to obtain insights into deviations from human toxicity. Four test chemicals (acetaminophen, ethanol, isoniazid, and perfluorooctanoic acid) were added to the μOCMs individually or in mixtures. HTS assays were utilized to measure cell death, apoptosis, glutathione depletion, mitochondrial membrane damage, and cytochrome P450 2E1 activity. The μOCMs exhibited increased toxicant sensitivity compared to hepatocyte sandwich cultures. Synergistic and non-synergistic interactions were observed when the toxicants were added as mixtures. Specifically, chemical interactions in the μOCMs were manifested by changes in apoptosis and decreased glutathione. The μOCMs accurately predicted hepatotoxicity for individual and mixtures of toxicants, demonstrating their potential for large-scale toxicity evaluations in the future.

Creating a Structured AOP Knowledgebase via Ontology-Based Annotations.

The Adverse Outcome Pathway framework is increasingly used to integrate data generated based on traditional and emerging toxicity testing paradigms. As the number of AOP descriptions has increased, so has the need to define the AOP in computable terms. Herein, we present a comprehensive annotation of 172 AOPs housed in the AOP-Wiki as of December 4, 2016 using terms from existing biological ontologies. AOP Key Events (KEs) were assigned ontology terms using a concept called the Event Component, which consists of a Process, an Object, and an Action term, with each term originating from ontologies and other controlled vocabularies. Annotation of KEs with ontology classes from fourteen ontologies and controlled vocabularies resulted in a total of 685 KEs being annotated with a total of 809 Event Components. A set of seven conventions resulted, defining the annotation of KEs via Event Components. This expanded annotation of AOPs allows computational reasoners to aid in both AOP development and applications. In addition, the incorporation of explicit biological objects will reduce the time required for converting a qualitative AOP description into a conceptual model that can support computational modeling. As high throughput genomics becomes a more important part of the high throughput toxicity testing landscape, the new approaches described here for annotating key events will also promote the visualization and analysis of genomics data in an AOP context.

Investigating the application of a nitroreductase-expressing transgenic zebrafish line for high-throughput toxicity testing.

Nitroreductase enzymes are responsible for the reduction of nitro functional groups to amino functional groups, and are found in a range of animal models, zebrafish (Danio rerio) excluded. Transgenic zebrafish models have been developed for tissue-specific cell ablation, which use nitroreductase to ablate specific tissues or cell types following exposure to the non-toxic pro-drug metronidazole (MTZ). When metabolized by nitroreductase, MTZ produces a potent cytotoxin, which specifically ablates the tissue in which metabolism occurs. Uses, beyond tissue-specific cell ablation, are possible for the hepatocyte-specific Tg(l-fabp:CFP-NTR)s891 zebrafish line, including investigations of the role of nitroreductase in the toxicity of nitrated compounds. The hepatic ablation characteristics of this transgenic line were explored, in order to expand its potential uses. Embryos were exposed at 48, 72, or 96 hours post fertilization (hpf) to a range of MTZ concentrations, and the ablation profiles were compared. Ablation occurred at a 10-fold lower concentration than previously reported. Embryos were exposed to a selection of other compounds, with and without MTZ, in order to investigate alternative uses for this transgenic line. Test compounds were selected based on: their ability to undergo nitroreduction, known importance of hepatic metabolism to toxicity, and known pharmaceutical hepatotoxins. Selected compounds included nitrated polycyclic aromatic hydrocarbons (nitro-PAHs), the PAHs retene and benzo[a]pyrene, and the pharmaceuticals acetaminophen and flutamide. The results suggest a range of potential roles of the liver in the toxicity of these compounds, and highlight the additional uses of this transgenic model in toxicity testing.

Conceptual Framework To Extend Life Cycle Assessment Using Near-Field Human Exposure Modeling and High-Throughput Tools for Chemicals.

Life Cycle Assessment (LCA) is a decision-making tool that accounts for multiple impacts across the life cycle of a product or service. This paper presents a conceptual framework to integrate human health impact assessment with risk screening approaches to extend LCA to include near-field chemical sources (e.g., those originating from consumer products and building materials) that have traditionally been excluded from LCA. A new generation of rapid human exposure modeling and high-throughput toxicity testing is transforming chemical risk prioritization and provides an opportunity for integration of screening-level risk assessment (RA) with LCA. The combined LCA and RA approach considers environmental impacts of products alongside risks to human health, which is consistent with regulatory frameworks addressing RA within a sustainability mindset. A case study is presented to juxtapose LCA and risk screening approaches for a chemical used in a consumer product. The case study demonstrates how these new risk screening tools can be used to inform toxicity impact estimates in LCA and highlights needs for future research. The framework provides a basis for developing tools and methods to support decision making on the use of chemicals in products.

Environmental surveillance and monitoring--The next frontiers for high-throughput toxicology.

High-throughput toxicity testing technologies along with the World Wide Web are revolutionizing both generation of and access to data regarding the biological activities that chemicals can elicit when they interact with specific proteins, genes, or other targets in the body of an organism. To date, however, most of the focus has been on the application of such data to assessment of individual chemicals. The authors suggest that environmental surveillance and monitoring represent the next frontiers for high-throughput toxicity testing. Resources already exist in curated databases of chemical-biological interactions, including highly standardized quantitative dose-response data generated from nascent high-throughput toxicity testing programs such as ToxCast and Tox21, to link chemicals detected through environmental analytical chemistry to known biological activities. The emergence of the adverse outcome pathway framework and the associated knowledge base for linking molecular-level or pathway-level perturbations of biological systems to adverse outcomes traditionally considered in risk assessment and regulatory decision-making through a series of measurable biological changes provides a critical link between activity and hazard. Furthermore, environmental samples can be directly analyzed via high-throughput toxicity testing platforms to provide an unprecedented breadth of biological activity characterization that integrates the effects of all compounds present in a mixture, whether known or not. Novel application of these chemical-biological interaction data provides an opportunity to transform scientific characterization of potential hazards associated with exposure to complex mixtures of environmental contaminants.

Accelerating Adverse Outcome Pathway Development Using Publicly Available Data Sources.

The adverse outcome pathway (AOP) concept links molecular perturbations with organism and population-level outcomes to support high-throughput toxicity (HTT) testing. International efforts are underway to define AOPs and store the information supporting these AOPs in a central knowledge base; however, this process is currently labor-intensive and time-consuming. Publicly available data sources provide a wealth of information that could be used to define computationally predicted AOPs (cpAOPs), which could serve as a basis for creating expert-derived AOPs in a much more efficient way. Computational tools for mining large datasets provide the means for extracting and organizing the information captured in these public data sources. Using cpAOPs as a starting point for expert-derived AOPs should accelerate AOP development. Coupling this with tools to coordinate and facilitate the expert development efforts will increase the number and quality of AOPs produced, which should play a key role in advancing the adoption of HTT testing, thereby reducing the use of animals in toxicity testing and greatly increasing the number of chemicals that can be tested.

Adverse Outcome Pathways-Organizing Toxicological Information to Improve Decision Making.

The number of chemicals for which environmental regulatory decisions are required far exceeds the current capacity for toxicity testing. High-throughput screening commonly used for drug discovery has the potential to increase this capacity. The adverse outcome pathway (AOP) concept has emerged as a framework for connecting high-throughput toxicity testing (HTT) and other results to potential impacts on human and wildlife populations. As a result of international efforts, the AOP development process is now well-defined and efforts are underway to broaden the participation through outreach and training. One key principle is that AOPs represent the chemical-agnostic portions of pathways to increase the generalizability of their application from early key events to overt toxicity. The closely related mode of action framework extends the AOP as needed when evaluating the potential risk of a specific chemical. This in turn enables integrated approaches to testing and assessment (IATA), which incorporate results of assays at various levels of biologic organization such as in silico; HTT; chemical-specific aspects including absorption, distribution, metabolism, and excretion (ADME); and an AOP describing the biologic basis of toxicity. Thus, it is envisaged that provision of limited information regarding both the AOP for critical effects and the ADME for any chemical associated with any adverse outcome would allow for the development of IATA and permit more detailed AOP and ADME research, where higher precision is needed based on the decision context.

Incorporating population variability and susceptible subpopulations into dosimetry for high-throughput toxicity testing.

Momentum is growing worldwide to use in vitro high-throughput screening (HTS) to evaluate human health effects of chemicals. However, the integration of dosimetry into HTS assays and incorporation of population variability will be essential before its application in a risk assessment context. Previously, we employed in vitro hepatic metabolic clearance and plasma protein binding data with in vitro in vivo extrapolation (IVIVE) modeling to estimate oral equivalent doses, or daily oral chemical doses required to achieve steady-state blood concentrations (Css) equivalent to media concentrations having a defined effect in an in vitro HTS assay. In this study, hepatic clearance rates of selected ToxCast chemicals were measured in vitro for 13 cytochrome P450 and five uridine 5'-diphospho-glucuronysyltransferase isozymes using recombinantly expressed enzymes. The isozyme-specific clearance rates were then incorporated into an IVIVE model that captures known differences in isozyme expression across several life stages and ethnic populations. Comparison of the median Css for a healthy population against the median or the upper 95th percentile for more sensitive populations revealed differences of 1.3- to 4.3-fold or 3.1- to 13.1-fold, respectively. Such values may be used to derive chemical-specific human toxicokinetic adjustment factors. The IVIVE model was also used to estimate subpopulation-specific oral equivalent doses that were directly compared with subpopulation-specific exposure estimates. This study successfully combines isozyme and physiologic differences to quantitate subpopulation pharmacokinetic variability. Incorporation of these values with dosimetry and in vitro bioactivities provides a viable approach that could be employed within a high-throughput risk assessment framework.

UCLA’s Molecular Screening Shared Resource: Enhancing Small Molecule Discovery with Functional Genomics and New Technology

The Molecular Screening Shared Resource (MSSR) offers a comprehensive range of leading-edge high throughput screening (HTS) services including drug discovery, chemical and functional genomics, and novel methods for nano and environmental toxicology. The MSSR is an open access environment with investigators from UCLA as well as from the entire globe. Industrial clients are equally welcome as are non-profit entities. The MSSR is a fee-for-service entity and does not retain intellectual property. In conjunction with the Center for Environmental Implications of Nanotechnology, the MSSR is unique in its dedicated and ongoing efforts towards high throughput toxicity testing of nanomaterials. In addition, the MSSR engages in technology development eliminating bottlenecks from the HTS workflow and enabling novel assays and readouts currently not available.

Toxicity Testing in the 21st Century: Using the New Toxicity Testing Paradigm to Create a Taxonomy of Adverse Effects

Distinguishing adaptive from adverse responses is fundamental to understanding toxicity and to implementing regulatory guidelines that are protective of human health. However, what we consider to be an adverse effect may change over time as the cultural acceptance of risk alters and new knowledge and insight accumulate. The fact that the identification of an adverse effect is subject to change is obvious, necessary, and uncomfortable. In this commentary, a framework for defining adverse effects is proposed for the emerging paradigm of toxicity testing in the 21st century-a paradigm that focuses on human cells, in vitro approaches, toxicity pathways, and high-throughput techniques. The traditional meaning of an adverse effect as a change at the organismal level is not compatible with this new system of toxicity testing. Instead, based on the experience of accident investigators, we propose that a Toxicological Factors Analysis and Classification System will use the database resulting from the high-throughput toxicity testing of the future to develop a Taxonomy of Adverse Effects. Similar to an accident, predisposing "latent failures" identified within categories of the toxicant response database will be associated with the "active failure" of an adverse effect.

Abstracts

The U.S. Environmental Protection Agency (EPA), National Toxicology Program (NTP), and National Institutes of Health (NIH) Chemical Genomics Center (NCGC) have complementary research programs designed to improve chemical toxicity evaluations by developing high throughput screening (HTS) methods that evaluate the impact of environmental chemicals on key toxicity pathways. These federal partners are coordinating an extension of the EPA’s ToxCast program, the NTP’s HTS initiative, and the NCGC’s Molecular Libraries Initiative into a collaborative research program focused on identifying toxicity pathways and developing in vitro assays to characterize the ability of chemicals to perturb those pathways. The goal is to develop new paradigm for high throughput toxicity testing that collects mechanistic and quantitative data from in vitro assays measuring chemical modulation of biological processes involved in the progression to toxicity. As toxicity pathways are identified, the in vitro assays can be optimized for comparison to in vivo animal studies, and for predicting effects in humans. Subsequent computational modeling of toxicity pathway responses and appropriate chemical dosimetry will need to be developed to make these predictions relevant for human health risk assessment. This work was reviewed by EPA and approved for publication but does not necessarily reflect official Agency policy. Index Terms: Toxicogenomics, High Throughput Screening/Testing, EPA ToxCast, Chemical Risk Assessment