The future of toxicity testing: a focus on in vitro methods using a quantitative high-throughput screening platform

Mapping Proteome-Wide Targets of Environmental Chemicals Using Reactivity-Based Chemoproteomic Platforms

We are exposed to a growing number of chemicals in our environment, most of which have not been characterized in terms of their toxicological potential or mechanisms. Here, we employ a chemoproteomic platform to map the cysteine reactivity of environmental chemicals using reactivity-based probes to mine for hyper-reactive hotspots across the proteome. We show that environmental contaminants such as monomethylarsonous acid and widely used pesticides such as chlorothalonil and chloropicrin possess common reactivity with a distinct set of proteins. Many of these proteins are involved in key metabolic processes, suggesting that these targets may be particularly sensitive to environmental electrophiles. We show that the widely used fungicide chlorothalonil specifically inhibits several metabolic enzymes involved in fatty acid metabolism and energetics, leading to dysregulated lipid metabolism in mice. Our results underscore the utility of using reactivity-based chemoproteomic platforms to uncover novel mechanistic insights into the toxicity of environmental chemicals.

Editor's Highlight: Analysis of the Effects of Cell Stress and Cytotoxicity on In Vitro Assay Activity Across a Diverse Chemical and Assay Space

Chemical toxicity can arise from disruption of specific biomolecular functions or through more generalized cell stress and cytotoxicity-mediated processes. Here, responses of 1060 chemicals including pharmaceuticals, natural products, pesticidals, consumer, and industrial chemicals across a battery of 815 in vitro assay endpoints from 7 high-throughput assay technology platforms were analyzed in order to distinguish between these types of activities. Both cell-based and cell-free assays showed a rapid increase in the frequency of responses at concentrations where cell stress/cytotoxicity responses were observed in cell-based assays. Chemicals that were positive on at least 2 viability/cytotoxicity assays within the concentration range tested (typically up to 100 μM) activated a median of 12% of assay endpoints whereas those that were not cytotoxic in this concentration range activated 1.3% of the assays endpoints. The results suggest that activity can be broadly divided into: (1) specific biomolecular interactions against one or more targets (eg, receptors or enzymes) at concentrations below which overt cytotoxicity-associated activity is observed; and (2) activity associated with cell stress or cytotoxicity, which may result from triggering specific cell stress pathways, chemical reactivity, physico-chemical disruption of proteins or membranes, or broad low-affinity non-covalent interactions. Chemicals showing a greater number of specific biomolecular interactions are generally designed to be bioactive (pharmaceuticals or pesticidal active ingredients), whereas intentional food-use chemicals tended to show the fewest specific interactions. The analyses presented here provide context for use of these data in ongoing studies to predict in vivo toxicity from chemicals lacking extensive hazard assessment.

Application of a Dual-Arm Robot in Complex Sample Preparation and Measurement Processes

Automation systems with applied robotics have already been established in industrial applications for many years. In the field of life sciences, a comparable high level of automation can be found in the areas of bioscreening and high-throughput screening. Strong deficits still exist in the development of flexible and universal fully automated systems in the field of analytical measurement. Reasons are the heterogeneous processes with complex structures, which include sample preparation and transport, analytical measurements using complex sensor systems, and suitable data analysis and evaluation. Furthermore, the use of nonstandard sample vessels with various shapes and volumes results in an increased complexity. The direct use of existing automation solutions from bioscreening applications is not possible. A flexible automation system for sample preparation, analysis, and data evaluation is presented in this article. It is applied for the determination of cholesterol in biliary endoprosthesis using gas chromatography-mass spectrometry (GC-MS). A dual-arm robot performs both transport and active manipulation tasks to ensure human-like operation. This general robotic concept also enables the use of manual laboratory devices and equipment and is thus suitable in areas with a high standardization grade.

A Quantitative Toxicogenomics Assay for High-throughput and Mechanistic Genotoxicity Assessment and Screening of Environmental Pollutants

The ecological and health concern of mutagenicity and carcinogenicity potentially associated with an overwhelmingly large and ever-increasing number of chemicals demands for cost-effective and feasible method for genotoxicity screening and risk assessment. This study proposed a genotoxicity assay using GFP-tagged yeast reporter strains, covering 38 selected protein biomarkers indicative of all the seven known DNA damage repair pathways. The assay was applied to assess four model genotoxic chemicals, eight environmental pollutants and four negative controls across six concentrations. Quantitative molecular genotoxicity end points were derived based on dose response modeling of a newly developed integrated molecular effect quantifier, Protein Effect Level Index (PELI). The molecular genotoxicity end points were consistent with multiple conventional in vitro genotoxicity assays, as well as with in vivo carcinogenicity assay results. Further more, the proposed genotoxicity end point PELI values quantitatively correlated with both comet assay in human cell and carcinogenicity potency assay in mice, providing promising evidence for linking the molecular disturbance measurements to adverse outcomes at a biological relevant level. In addition, the high-resolution DNA damaging repair pathway alternated protein expression profiles allowed for chemical clustering and classification. This toxicogenomics-based assay presents a promising alternative for fast, efficient and mechanistic genotoxicity screening and assessment of drugs, foods, and environmental contaminants.

In silico toxicology: computational methods for the prediction of chemical toxicity

Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models. WIREs Comput Mol Sci 2016, 6:147-172. doi: 10.1002/wcms.1240 For further resources related to this article, please visit the WIREs website.

Environmental Chemical Assessment in Clinical Practice: Unveiling the Elephant in the Room

A growing body of evidence suggests chemicals present in air, water, soil, food, building materials and household products are toxicants that contribute to the many chronic diseases typically seen in routine medical practice. Yet, despite calls from numerous organisations to provide clinicians with more training and awareness in environmental health, there are multiple barriers to the clinical assessment of toxic environmental exposures. Recent developments in the fields of systems biology, innovative breakthroughs in biomedical research encompassing the "-omics" fields, and advances in mobile sensing, peer-to-peer networks and big data, provide tools that future clinicians can use to assess environmental chemical exposures in their patients. There is also a need for concerted action at all levels, including actions by individual patients, clinicians, medical educators, regulators, government and non-government organisations, corporations and the wider civil society, to understand the "exposome" and minimise the extent of toxic exposures on current and future generations. Clinical environmental chemical risk assessment may provide a bridge between multiple disciplines that uses new technologies to herald in a new era in personalised medicine that unites clinicians, patients and civil society in the quest to understand and master the links between the environment and human health.

Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization

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.

Thermo-responsive polymer aided spheroid culture in cryogel based platform for high throughput drug screening

A versatile and widely applicable cryogel-based high throughput platform for spheroid culture in the presence of a thermo-responsive polymer and drug screening.

A Quantitative High-Throughput Screening Data Analysis Pipeline for Activity Profiling

The US Tox21 program has developed in vitro assays to test large collections of environmental chemicals in a quantitative high-throughput screening (qHTS) format, using triplicate 15-dose titrations to generate over 50 million data points to date. Counter screens are also employed to minimize interferences from non-target-specific assay artifacts, such as compound auto fluorescence and cytotoxicity. New data analysis approaches are needed to integrate these data and characterize the activities observed from these assays. Here, we describe a complete analysis pipeline that evaluates these qHTS data for technical quality in terms of signal reproducibility. We integrate signals from repeated assay runs, primary readouts, and counter screens to produce a final call on on-target compound activity.

Analysis of the ToxCast Chemical-Assay Space Using the Comparative Toxicogenomics Database

Many studies have attempted to predict in vivo hazards based on the ToxCast in vitro assay results with the goal of using these predictions to prioritize compounds for conventional toxicity testing. Most of these conventional studies rely on in vivo end points observed using preclinical species (e.g., mice and rats). Although the preclinical animal studies provide valuable insights, there can often be significant disconnects between these studies and safety concerns in humans. One way to address these concerns, for an admittedly more limited set of compounds, is to explore relationships between the in vitro data from human cell lines and observations from human related studies. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org ) is a rich source of data linking chemicals to human diseases/adverse events and pathways. In this study we explored the relationships between ToxCast chemicals, their ToxCast in vitro test results, and their annotations of human disease/adverse event end points as captured in the CTD database. We mined these associations to identify potentially interesting, statistically significant in vitro assay and in vivo toxicity correlations. To the best of our knowledge, this is one of the first studies analyzing the relationships between the ToxCast in vitro assays results and the CTD disease/adverse event end point annotations. The in vitro profiles identified in this analysis may prove useful for prioritizing compounds for toxicity testing, suggesting mechanisms of toxicity, and forecasting potential in vivo human drug induced injury.

Effect-based trigger values for in vitro bioassays: Reading across from existing water quality guideline values

Cell-based bioassays are becoming increasingly popular in water quality assessment. The new generations of reporter-gene assays are very sensitive and effects are often detected in very clean water types such as drinking water and recycled water. For monitoring applications it is therefore imperative to derive trigger values that differentiate between acceptable and unacceptable effect levels. In this proof-of-concept paper, we propose a statistical method to read directly across from chemical guideline values to trigger values without the need to perform in vitro to in vivo extrapolations. The derivation is based on matching effect concentrations with existing chemical guideline values and filtering out appropriate chemicals that are responsive in the given bioassays at concentrations in the range of the guideline values. To account for the mixture effects of many chemicals acting together in a complex water sample, we propose bioanalytical equivalents that integrate the effects of groups of chemicals with the same mode of action that act in a concentration-additive manner. Statistical distribution methods are proposed to derive a specific effect-based trigger bioanalytical equivalent concentration (EBT-BEQ) for each bioassay of environmental interest that targets receptor-mediated toxicity. Even bioassays that are indicative of the same mode of action have slightly different numeric trigger values due to differences in their inherent sensitivity. The algorithm was applied to 18 cell-based bioassays and 11 provisional effect-based trigger bioanalytical equivalents were derived as an illustrative example using the 349 chemical guideline values protective for human health of the Australian Guidelines for Water Recycling. We illustrate the applicability using the example of a diverse set of water samples including recycled water. Most recycled water samples were compliant with the proposed triggers while wastewater effluent would not have been compliant with a few. The approach is readily adaptable to any water type and guideline or regulatory framework and can be expanded from the protection goal of human health to environmental protection targets. While this work constitutes a proof of principle, the applicability remains limited at present due to insufficient experimental bioassay data on individual regulated chemicals and the derived effect-based trigger values are of course only provisional. Once the experimental database is expanded and made more robust, the proposed effect-based trigger values may provide guidance in a regulatory context.

In vitro bioassays to evaluate complex chemical mixtures in recycled water

With burgeoning population and diminishing availability of freshwater resources, the world continues to expand the use of alternative water resources for drinking, and the quality of these sources has been a great concern for the public as well as public health professionals. In vitro bioassays are increasingly being used to enable rapid, relatively inexpensive toxicity screening that can be used in conjunction with analytical chemistry data to evaluate water quality and the effectiveness of water treatment. In this study, a comprehensive bioassay battery consisting of 36 bioassays covering 18 biological endpoints was applied to screen the bioactivity of waters of varying qualities with parallel treatments. Samples include wastewater effluent, ultraviolet light (UV) and/or ozone advanced oxidation processed (AOP) recycled water, and infiltrated recycled groundwater. Based on assay sensitivity and detection frequency in the samples, several endpoints were highlighted in the battery, including assays for genotoxicity, mutagenicity, estrogenic activity, glucocorticoid activity, arylhydrocarbon receptor activity, oxidative stress response, and cytotoxicity. Attenuation of bioactivity was found to be dependent on the treatment process and bioassay endpoint. For instance, ozone technology significantly removed oxidative stress activity, while UV based technologies were most efficient for the attenuation of glucocorticoid activity. Chlorination partially attenuated genotoxicity and greatly decreased herbicidal activity, while groundwater infiltration efficiently attenuated most of the evaluated bioactivity with the exception of genotoxicity. In some cases, bioactivity (e.g., mutagenicity, genotoxicity, and arylhydrocarbon receptor) increased following water treatment, indicating that transformation products of water treatment may be a concern. Furthermore, several types of bioassays with the same endpoint were compared in this study, which could help guide the selection of optimized methods in future studies. Overall, this research indicates that a battery of bioassays can be used to support decision-making on the application of advanced water treatment processes for removal of bioactivity.

A Quantitative Approach to Screen for Nephrotoxic Compounds In Vitro

Nephrotoxicity due to drugs and environmental chemicals accounts for significant patient mortality and morbidity, but there is no high throughput in vitro method for predictive nephrotoxicity assessment. We show that primary human proximal tubular epithelial cells (HPTECs) possess characteristics of differentiated epithelial cells rendering them desirable to use in such in vitro systems. To identify a reliable biomarker of nephrotoxicity, we conducted multiplexed gene expression profiling of HPTECs after exposure to six different concentrations of nine human nephrotoxicants. Only overexpression of the gene encoding heme oxygenase-1 (HO-1) significantly correlated with increasing dose for six of the compounds, and significant HO-1 protein deregulation was confirmed with each of the nine nephrotoxicants. Translatability of HO-1 increase across species and platforms was demonstrated by computationally mining two large rat toxicogenomic databases for kidney tubular toxicity and by observing a significant increase in HO-1 after toxicity using an ex vivo three-dimensional microphysiologic system (kidney-on-a-chip). The predictive potential of HO-1 was tested using an additional panel of 39 mechanistically distinct nephrotoxic compounds. Although HO-1 performed better (area under the curve receiver-operator characteristic curve [AUC-ROC]=0.89) than traditional endpoints of cell viability (AUC-ROC for ATP=0.78; AUC-ROC for cell count=0.88), the combination of HO-1 and cell count further improved the predictive ability (AUC-ROC=0.92). We also developed and optimized a homogenous time-resolved fluorescence assay to allow high throughput quantitative screening of nephrotoxic compounds using HO-1 as a sensitive biomarker. This cell-based approach may facilitate rapid assessment of potential nephrotoxic therapeutics and environmental chemicals.

Photodynamic therapy in colorectal cancer treatment--The state of the art in preclinical research

BACKGROUND

Photodynamic therapy (PDT) is used in many different oncologic fields. Also in gastroenterology, where have been a few attempts to treat both the premalignant lesion and advanced colorectal cancer (CRC). This review aims to give a general overview of preclinical photodynamic studies related to CRC cells and animal studies of photodynamic effects related to CRC treatment to emphasize their potential in study of PDT mechanism, safety and efficiency to translate these results into clinical benefit in CRC treatment.

MATERIALS AND METHOD

Literature on in vitro preclinical photodynamic studies related to CRC cells and animal studies of photodynamic effects related to CRC treatment with the fallowing medical subject headings search terms: colorectal cancer, photodynamic therapy, photosensitizer(s), in vitro, cell culture(s), in vivo, animal experiment(s). The articles were selected by their relevance to the topic.

RESULTS

The majority of preclinical studies concerning possibility of PDT application in colon and rectal cancer is focused on phototoxic action of photosensitizers toward cultured colorectal tumor cells in vitro. The purposes of animal experiments are usually elucidation of mechanisms of observed photodynamic effects in scale of organism, estimation of PDT safety and efficiency and translation of these results into clinical benefit.

CONCLUDING REMARKS

In vitro photodynamic studies and animal experiments can be useful for studies of mechanisms and efficiency of photodynamic method as a start point on PDT clinical research. The primary disadvantage of in vitro experiments is a risk of over-interpretation of their results during extrapolation to the entire CRC.

Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: focus on the cancer hallmark of tumor angiogenesis

One of the important 'hallmarks' of cancer is angiogenesis, which is the process of formation of new blood vessels that are necessary for tumor expansion, invasion and metastasis. Under normal physiological conditions, angiogenesis is well balanced and controlled by endogenous proangiogenic factors and antiangiogenic factors. However, factors produced by cancer cells, cancer stem cells and other cell types in the tumor stroma can disrupt the balance so that the tumor microenvironment favors tumor angiogenesis. These factors include vascular endothelial growth factor, endothelial tissue factor and other membrane bound receptors that mediate multiple intracellular signaling pathways that contribute to tumor angiogenesis. Though environmental exposures to certain chemicals have been found to initiate and promote tumor development, the role of these exposures (particularly to low doses of multiple substances), is largely unknown in relation to tumor angiogenesis. This review summarizes the evidence of the role of environmental chemical bioactivity and exposure in tumor angiogenesis and carcinogenesis. We identify a number of ubiquitous (prototypical) chemicals with disruptive potential that may warrant further investigation given their selectivity for high-throughput screening assay targets associated with proangiogenic pathways. We also consider the cross-hallmark relationships of a number of important angiogenic pathway targets with other cancer hallmarks and we make recommendations for future research. Understanding of the role of low-dose exposure of chemicals with disruptive potential could help us refine our approach to cancer risk assessment, and may ultimately aid in preventing cancer by reducing or eliminating exposures to synergistic mixtures of chemicals with carcinogenic potential.

Isotonic Regression Based-Method in Quantitative High-Throughput Screenings for Genotoxicity

Quantitative high-throughput screenings (qHTSs) for genotoxicity are conducted as part of comprehensive toxicology screening projects. The most widely used method is to compare the dose-response data of a wild-type and DNA repair gene knockout mutants, using model-fitting to the Hill equation (HE). However, this method performs poorly when the observed viability does not fit the equation well, as frequently happens in qHTS. More capable methods must be developed for qHTS where large data variations are unavoidable. In this study, we applied an isotonic regression (IR) method and compared its performance with HE under multiple data conditions. When dose-response data were suitable to draw HE curves with upper and lower asymptotes and experimental random errors were small, HE was better than IR, but when random errors were big, there was no difference between HE and IR. However, when the drawn curves did not have two asymptotes, IR showed better performance (p < 0.05, exact paired Wilcoxon test) with higher specificity (65% in HE vs. 96% in IR). In summary, IR performed similarly to HE when dose-response data were optimal, whereas IR clearly performed better in suboptimal conditions. These findings indicate that IR would be useful in qHTS for comparing dose-response data.

A fast Resazurin-based live viability assay is equivalent to the MTT-test in the KeratinoSens assay

The KeratinoSens™ assay was the first cell-based in vitro test in the skin sensitisation adverse outcome pathway to be endorsed by an ECVAM statement. It includes a cell viability assessment, which serves two purposes: It forms part of the prediction model to exclude false-positive irritants and cytotoxicity provides some information on sensitizer potency of chemicals, which can feed into a multivariate potency model. In the KeratinoSens™ protocol, Nrf2-dependent luciferase induction and the MTT-viability assay are performed in parallel plates. Resazurin-based viability assays do not require cell lysis and are compatible with luciferase measurements in the same cells. Here, we performed detailed comparison of the tetrazolium-based MTT assay and the PrestoBlue® assay on 35 reference chemicals tested in the full KeratinoSens™ protocol. Log-transformed IC50 and IC30 values measured with both methods correlate with an R(2) of 0.97 and 0.95. A single chemical showed divergent results and analysis by four different viability assays indicated the PrestoBlue® read-out to be correct. The new more rapid and resource efficient approach has clear advantages: Dose-response curves show lower variability and the two endpoints are measured on the same cells. This approach is a valid addition to or replacement of the MTT-readout in the KeratinoSens™ assay and it is recommended as a general tool for luciferase-based reporter assays.

Profiling of the Tox21 chemical collection for mitochondrial function to identify compounds that acutely decrease mitochondrial membrane potential

BACKGROUND

Mitochondrial dysfunction has been implicated in the pathogenesis of a variety of disorders including cancer, diabetes, and neurodegenerative and cardiovascular diseases. Understanding whether different environmental chemicals and druglike molecules impact mitochondrial function represents an initial step in predicting exposure-related toxicity and defining a possible role for such compounds in the onset of various diseases.

OBJECTIVES

We sought to identify individual chemicals and general structural features associated with changes in mitochondrial membrane potential (MMP).

METHODS

We used a multiplexed [two end points in one screen; MMP and adenosine triphosphate (ATP) content] quantitative high throughput screening (qHTS) approach combined with informatics tools to screen the Tox21 library of 10,000 compounds (~ 8,300 unique chemicals) at 15 concentrations each in triplicate to identify chemicals and structural features that are associated with changes in MMP in HepG2 cells.

RESULTS

Approximately 11% of the compounds (913 unique compounds) decreased MMP after 1 hr of treatment without affecting cell viability (ATP content). In addition, 309 compounds decreased MMP over a concentration range that also produced measurable cytotoxicity [half maximal inhibitory concentration (IC50) in MMP assay/IC50 in viability assay ≤ 3; p < 0.05]. More than 11% of the structural clusters that constitute the Tox21 library (76 of 651 clusters) were significantly enriched for compounds that decreased the MMP.

CONCLUSIONS

Our multiplexed qHTS approach allowed us to generate a robust and reliable data set to evaluate the ability of thousands of drugs and environmental compounds to decrease MMP. The use of structure-based clustering analysis allowed us to identify molecular features that are likely responsible for the observed activity.

Intersection of toxicogenomics and high throughput screening in the Tox21 program: an NIEHS perspective

Humans are exposed to thousands of chemicals with inadequate toxicological data. Advances in computational toxicology, robotic high throughput screening (HTS), and genome-wide expression have been integrated into the Tox21 program to better predict the toxicological effects of chemicals. Tox21 is a collaboration among US government agencies initiated in 2008 that aims to shift chemical hazard assessment from traditional animal toxicology to target-specific, mechanism-based, biological observations using in vitro assays and lower organism models. HTS uses biocomputational methods for probing thousands of chemicals in in vitro assays for gene-pathway response patterns predictive of adverse human health outcomes. In 1999, NIEHS began exploring the application of toxicogenomics to toxicology and recent advances in NextGen sequencing should greatly enhance the biological content obtained from HTS platforms. We foresee an intersection of new technologies in toxicogenomics and HTS as an innovative development in Tox21. Tox21 goals, priorities, progress, and challenges will be reviewed.

Cross-species toxicogenomic analyses and phenotypic anchoring in response to groundwater low-level pollution

Background

Comparison of toxicogenomic data facilitates the identification of deregulated gene patterns and maximizes health risk prediction in human.

Results

Here, we performed phenotypic anchoring on the effects of acute exposure to low-grade polluted groundwater using mouse and zebrafish. Also, we evaluated two windows of chronic exposure in mouse, starting in utero and at the end of lactation. Bioinformatic analysis of livers microarray data showed that the number of deregulated biofunctions and pathways is higher after acute exposure, compared to the chronic one. It also revealed specific profiles of altered gene expression in all treatments, pointing to stress response/mitochondrial pathways as major players of environmental toxicity. Of note, dysfunction of steroid hormones was also predicted by bioinformatic analysis and verified in both models by traditional approaches, serum estrogens measurement and vitellogenin mRNA determination in mice and zebrafish, respectively.

Conclusions

In our report, phenotypic anchoring in two vertebrate model organisms highlights the toxicity of low-grade pollution, with varying susceptibility based on exposure window. The overlay of zebrafish and mice deregulated pathways, more than single genes, is useful in risk identification from chemicals implicated in the observed effects.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1067) contains supplementary material, which is available to authorized users.

Effects of toluene, acrolein and vinyl chloride on motor activity of Drosophila melanogaster

The data generated by current high-throughput assays for chemical toxicity require information to link effects at molecular targets to adverse outcomes in whole animals. In addition, more efficient methods for testing volatile chemicals are needed. Here we begin to address these issues by determining the utility of measuring behavioral responses of Drosophila melanogaster to airborne volatile organic compounds (VOCs) as a potential model system for discovering adverse outcome pathways and as a method to test for toxicity. In these experiments, we measured motor activity in male and female flies to determine concentration-effect functions for three VOCs that differ in their mode of action: toluene, a narcotic; acrolein, an irritant; and vinyl chloride, a hepatocarcinogen. These experiments were conducted in Flyland, an outbred population of flies derived from 40 lines of the Drosophila Genetics Reference Panel (DGRP) (Mackay et al., 2012), in preparation for subsequent experiments with individual lines of the DGRP. Systematic, concentration-related changes in activity were observed with toluene, but not with acrolein; high concentrations of vinyl chloride reduced activity by a small amount. Despite higher activity levels in males than in females under control conditions, the sexes were equally sensitive to toluene. Transient increases in activity at the onset and offset of exposure to toluene and vinyl chloride suggested that the flies detected changes in air quality at concentrations that did not persistently suppress activity. The effects and potency of toluene are consistent with those observed in rodents. The lack of clear concentration-related changes in response to acrolein and vinyl chloride shows limitations of this method is for screening toxicity attributed to VOCs. This abstract does not reflect U.S. EPA policy.

Big data in chemical toxicity research: the use of high-throughput screening assays to identify potential toxicants

High-throughput screening (HTS) assays that measure the in vitro toxicity of environmental compounds have been widely applied as an alternative to in vivo animal tests of chemical toxicity. Current HTS studies provide the community with rich toxicology information that has the potential to be integrated into toxicity research. The available in vitro toxicity data is updated daily in structured formats (e.g., deposited into PubChem and other data-sharing web portals) or in an unstructured way (papers, laboratory reports, toxicity Web site updates, etc.). The information derived from the current toxicity data is so large and complex that it becomes difficult to process using available database management tools or traditional data processing applications. For this reason, it is necessary to develop a big data approach when conducting modern chemical toxicity research. In vitro data for a compound, obtained from meaningful bioassays, can be viewed as a response profile that gives detailed information about the compound's ability to affect relevant biological proteins/receptors. This information is critical for the evaluation of complex bioactivities (e.g., animal toxicities) and grows rapidly as big data in toxicology communities. This review focuses mainly on the existing structured in vitro data (e.g., PubChem data sets) as response profiles for compounds of environmental interest (e.g., potential human/animal toxicants). Potential modeling and mining tools to use the current big data pool in chemical toxicity research are also described.

Big data in chemical toxicity research: the use of high-throughput screening assays to identify potential toxicants

High-throughput screening (HTS) assays that measure the in vitro toxicity of environmental compounds have been widely applied as an alternative to in vivo animal tests of chemical toxicity. Current HTS studies provide the community with rich toxicology information that has the potential to be integrated into toxicity research. The available in vitro toxicity data is updated daily in structured formats (e.g., deposited into PubChem and other data-sharing web portals) or in an unstructured way (papers, laboratory reports, toxicity Web site updates, etc.). The information derived from the current toxicity data is so large and complex that it becomes difficult to process using available database management tools or traditional data processing applications. For this reason, it is necessary to develop a big data approach when conducting modern chemical toxicity research. In vitro data for a compound, obtained from meaningful bioassays, can be viewed as a response profile that gives detailed information about the compound's ability to affect relevant biological proteins/receptors. This information is critical for the evaluation of complex bioactivities (e.g., animal toxicities) and grows rapidly as big data in toxicology communities. This review focuses mainly on the existing structured in vitro data (e.g., PubChem data sets) as response profiles for compounds of environmental interest (e.g., potential human/animal toxicants). Potential modeling and mining tools to use the current big data pool in chemical toxicity research are also described.

Transcriptomic characterization of C57BL/6 mouse embryonic stem cell differentiation and its modulation by developmental toxicants

The Tox21 program calls for transforming toxicology testing from traditional in vivo tests to less expensive and higher throughput in vitro methods. In developmental toxicology, a spectrum of alternative methods including cell line based tests has been developed. In particular, embryonic stem cells (ESCs) have received widespread attention as a promising alternative model for developmental toxicity assessment. Here, we characterized gene expression changes during mouse ESC differentiation and their modulation by developmental toxicants. C57BL/6 ESCs were allowed to differentiate spontaneously and RNA of vehicle controls was collected at 0, 24, 48, 72, 96, 120 and 168 h after embryoid body (EB) formation; RNA of compound-exposed EBs were collected at 24 h. Samples were hybridized to Affymetrix Mouse Gene 2.0 ST Array; using stringent cut-off criteria of Bonferroni-adjusted p<0.05 and fold change >2.0, a total of 1996 genes were found differentially expressed among the vehicle controls at different time points. Gene ontology (GO) analysis showed these regulated genes were mostly involved in differentiation-related processes such as development, morphogenesis, metabolism, cell differentiation, cell organization and biogenesis, embryonic development, and reproduction. Biomarkers of all three germ layers or of their derivative early cell types were identified in the gene list. Principal component analysis (PCA) based on these genes showed that the unexposed vehicle controls appeared in chronological order in the PCA plot, and formed a differentiation track when connected. Cultures exposed to thalidomide, monobutyl phthalate, or valproic acid deviated significantly from the differentiation track, manifesting the capacity of the differentiation track to identify the modulating effects of diverse developmental toxicants. The differentiation track defined in this study may be further exploited as a baseline for developmental toxicity testing, with compounds causing significant deviation from the differentiation track being predicted as potential developmental toxicants.

Environmental side effects of pharmaceutical cocktails: what we know and what we should know

Cocktails of pharmaceuticals are released in the environment after human consumption and due to the incomplete removal at the wastewater treatment plants. Pharmaceuticals are considered as contaminants of emerging concern and, a plethora of journal articles addressing their possible adverse effects have been published during the past 20 years. The emphasis during the early years of research within this field, was on the assessment of acute effects of pharmaceuticals applied singly, leading to results regarding their environmental risk, potentially not realistic or relevant to the actual environmental conditions. Only recently has the focus been shifted to chronic exposure and to the assessment of cocktail effects. To this end, this review provides an up-to-date compilation of 57 environmental and human toxicology studies published during 2000-2014 dealing with the adverse effects of pharmaceutical mixtures. The main challenges regarding the design of experiments and the analysis of the results regarding the effects of pharmaceutical mixtures to different biological systems are presented and discussed herein. The gaps of knowledge are critically reviewed highlighting specific future research needs and perspectives.

Quantitative in vitro-to-in vivo extrapolation in a high-throughput environment

High-throughput in vitro toxicity screening provides an efficient way to identify potential biological targets for environmental and industrial chemicals while conserving limited testing resources. However, reliance on the nominal chemical concentrations in these in vitro assays as an indicator of bioactivity may misrepresent potential in vivo effects of these chemicals due to differences in clearance, protein binding, bioavailability, and other pharmacokinetic factors. Development of high-throughput in vitro hepatic clearance and protein binding assays and refinement of quantitative in vitro-to-in vivo extrapolation (QIVIVE) methods have provided key tools to predict xenobiotic steady state pharmacokinetics. Using a process known as reverse dosimetry, knowledge of the chemical steady state behavior can be incorporated with HTS data to determine the external in vivo oral exposure needed to achieve internal blood concentrations equivalent to those eliciting bioactivity in the assays. These daily oral doses, known as oral equivalents, can be compared to chronic human exposure estimates to assess whether in vitro bioactivity would be expected at the dose-equivalent level of human exposure. This review will describe the use of QIVIVE methods in a high-throughput environment and the promise they hold in shaping chemical testing priorities and, potentially, high-throughput risk assessment strategies.

Identification of thyroid hormone receptor active compounds using a quantitative high-throughput screening platform

To adapt the use of GH3.TRE-Luc reporter gene cell line for a quantitative high-throughput screening (qHTS) platform, we miniaturized the reporter gene assay to a 1536-well plate format. 1280 chemicals from the Library of Pharmacologically Active Compounds (LOPAC) and the National Toxicology Program (NTP) 1408 compound collection were analyzed to identify potential thyroid hormone receptor (TR) agonists and antagonists. Of the 2688 compounds tested, eight scored as potential TR agonists when the positive hit cut-off was defined at ≥10% efficacy, relative to maximal triiodothyronine (T₃) induction, and with only one of those compounds reaching ≥20% efficacy. One common class of compounds positive in the agonist assays were retinoids such as all-trans retinoic acid, which are likely acting via the retinoid-X receptor, the heterodimer partner with the TR. Five potential TR antagonists were identified, including the antiallergy drug tranilast and the anxiolytic drug SB 205384 but also some cytotoxic compounds like 5-fluorouracil. None of the inactive compounds were structurally related to T₃, nor had been reported elsewhere to be thyroid hormone disruptors, so false negatives were not detected. None of the low potency (>100µM) TR agonists resembled T₃ or T₄, thus these may not bind directly in the ligand-binding pocket of the receptor. For TR agonists, in the qHTS, a hit cut-off of ≥20% efficacy at 100 µM may avoid identification of positives with low or no physiological relevance. The miniaturized GH3.TRE-Luc assay offers a promising addition to the in vitro test battery for endocrine disruption, and given the low percentage of compounds testing positive, its high-throughput nature is an important advantage for future toxicological screening.

The utility of behavioral studies for aquatic toxicology testing: a meta-analysis

Behavioral responses have been applied for decades as tools for aquatic toxicity testing, but have received far less attention than studies assessing lethality, development or reproduction. With improved visual and non-visual assessment tools and increased knowledge of the importance of behavior for organism health and fitness, interest in behavioral analysis has increased in recent years. However, to our knowledge there has never been a quantitative assessment of the available techniques for organismal toxicity testing, so it is not clear whether behavioral studies represent valuable additions to environmental monitoring. We performed a meta-analysis comparing the relative sensitivities and average durations of behavioral studies to those assessing acute lethality, development and reproduction. Results demonstrate that the average duration of behavioral studies is consistently less than developmental or reproductive studies, and that behavioral endpoints are generally more sensitive than those assessing development or reproduction. We found effect sizes to be lower but power to be higher in behavioral and reproductive studies compared to studies assessing development, which likely relates to low sample sizes commonly used in developmental studies. Overall, we conclude that behavioral studies are comparatively fast and sensitive, and therefore warrant further attention as tools for assessing the toxicological effects of environmental contaminants. We suggest that research aimed at developing and optimizing techniques for behavioral analysis could prove extremely useful to the field of toxicology, but that future work must be directed at determining what specific behaviors are most sensitive to various classes of contaminants, and at understanding the relevance of changes to discrete behaviors for influencing organismal and population-level health and fitness.

Insulin resistance and environmental pollutants: experimental evidence and future perspectives

BACKGROUND

The metabolic disruptor hypothesis postulates that environmental pollutants may be risk factors for metabolic diseases. Because insulin resistance is involved in most metabolic diseases and current health care prevention programs predominantly target insulin resistance or risk factors thereof, a critical analysis of the role of pollutants in insulin resistance might be important for future management of metabolic diseases.

OBJECTIVES

We aimed to critically review the available information linking pollutant exposure to insulin resistance and to open the discussion on future perspectives for metabolic disruptor identification and prioritization strategies.

METHODS

We searched PubMed and Web of Science for experimental studies reporting on linkages between environmental pollutants and insulin resistance and identified a total of 23 studies as the prime literature.

DISCUSSION

Recent studies specifically designed to investigate the effect of pollutants on insulin sensitivity show a potential causation of insulin resistance. Based on these studies, a summary of viable test systems and end points can be composed, allowing insight into what is missing and what is needed to create a standardized insulin resistance toxicity testing strategy.

CONCLUSIONS

It is clear that current research predominantly relies on top-down identification of insulin resistance-inducing metabolic disruptors and that the development of dedicated in vitro or ex vivo screens to allow animal sparing and time- and cost-effective bottom-up screening is a major future research need.

Non-monotonic dose responses in studies of endocrine disrupting chemicals: bisphenol a as a case study

Non-monotonic dose response curves (NMDRCs) have been demonstrated for natural hormones and endocrine disrupting chemicals (EDCs) in a variety of biological systems including cultured cells, whole organ cultures, laboratory animals and human populations. The mechanisms responsible for these NMDRCs are well known, typically related to the interactions between the ligand (hormone or EDC) and a hormone receptor. Although there are hundreds of examples of NMDRCs in the EDC literature, there are claims that they are not 'common enough' to influence the use of high-to-low dose extrapolations in risk assessments. Here, we chose bisphenol A (BPA), a well-studied EDC, to assess the frequency of non-monotonic responses. Our results indicate that NMDRCs are common in the BPA literature, occurring in greater than 20% of all experiments and in at least one endpoint in more than 30% of all studies we examined. We also analyzed the types of endpoints that produce NMDRCs in vitro and factors related to study design that influence the ability to detect these kinds of responses. Taken together, these results provide strong evidence for NMDRCs in the EDC literature, specifically for BPA, and question the current risk assessment practice where 'safe' low doses are predicted from high dose exposures.

The Tox21 robotic platform for the assessment of environmental chemicals--from vision to reality

Since its establishment in 2008, the US Tox21 inter-agency collaboration has made great progress in developing and evaluating cellular models for the evaluation of environmental chemicals as a proof of principle. Currently, the program has entered its production phase (Tox21 Phase II) focusing initially on the areas of modulation of nuclear receptors and stress response pathways. During Tox21 Phase II, the set of chemicals to be tested has been expanded to nearly 10,000 (10K) compounds and a fully automated screening platform has been implemented. The Tox21 robotic system combined with informatics efforts is capable of screening and profiling the collection of 10K environmental chemicals in triplicate in a week. In this article, we describe the Tox21 screening process, compound library preparation, data processing, and robotic system validation.

Profiling 976 ToxCast chemicals across 331 enzymatic and receptor signaling assays

Understanding potential health risks is a significant challenge due to the large numbers of diverse chemicals with poorly characterized exposures and mechanisms of toxicities. The present study analyzes 976 chemicals (including failed pharmaceuticals, alternative plasticizers, food additives, and pesticides) in Phases I and II of the U.S. EPA's ToxCast project across 331 cell-free enzymatic and ligand-binding high-throughput screening (HTS) assays. Half-maximal activity concentrations (AC50) were identified for 729 chemicals in 256 assays (7,135 chemical-assay pairs). Some of the most commonly affected assays were CYPs (CYP2C9 and CYP2C19), transporters (mitochondrial TSPO, norepinephrine, and dopaminergic), and GPCRs (aminergic). Heavy metals, surfactants, and dithiocarbamate fungicides showed promiscuous but distinctly different patterns of activity, whereas many of the pharmaceutical compounds showed promiscuous activity across GPCRs. Literature analysis confirmed >50% of the activities for the most potent chemical-assay pairs (54) but also revealed 10 missed interactions. Twenty-two chemicals with known estrogenic activity were correctly identified for the majority (77%), missing only the weaker interactions. In many cases, novel findings for previously unreported chemical-target combinations clustered with known chemical-target interactions. Results from this large inventory of chemical-biological interactions can inform read-across methods as well as link potential targets to molecular initiating events in adverse outcome pathways for diverse toxicities.

Profiling 976 ToxCast chemicals across 331 enzymatic and receptor signaling assays

Understanding potential health risks is a significant challenge due to the large numbers of diverse chemicals with poorly characterized exposures and mechanisms of toxicities. The present study analyzes 976 chemicals (including failed pharmaceuticals, alternative plasticizers, food additives, and pesticides) in Phases I and II of the U.S. EPA's ToxCast project across 331 cell-free enzymatic and ligand-binding high-throughput screening (HTS) assays. Half-maximal activity concentrations (AC50) were identified for 729 chemicals in 256 assays (7,135 chemical-assay pairs). Some of the most commonly affected assays were CYPs (CYP2C9 and CYP2C19), transporters (mitochondrial TSPO, norepinephrine, and dopaminergic), and GPCRs (aminergic). Heavy metals, surfactants, and dithiocarbamate fungicides showed promiscuous but distinctly different patterns of activity, whereas many of the pharmaceutical compounds showed promiscuous activity across GPCRs. Literature analysis confirmed >50% of the activities for the most potent chemical-assay pairs (54) but also revealed 10 missed interactions. Twenty-two chemicals with known estrogenic activity were correctly identified for the majority (77%), missing only the weaker interactions. In many cases, novel findings for previously unreported chemical-target combinations clustered with known chemical-target interactions. Results from this large inventory of chemical-biological interactions can inform read-across methods as well as link potential targets to molecular initiating events in adverse outcome pathways for diverse toxicities.

Prediction of human genes and diseases targeted by xenobiotics using predictive toxicogenomic-derived models (PTDMs)

New technologies for systems-level determinants of human exposure to drugs, industrial chemicals, pesticides, and other environmental agents provide an invaluable opportunity to extend the understanding of human health and potential environmental hazards. We report here the development of a new computational-systems toxicology framework, called predictive toxicogenomics-derived models (PTDMs). PTDMs integrate three networks of chemical-gene interactions (CGIs), chemical-disease associations (CDAs) and gene-disease associations (GDAs) to infer chemical hazard profiles, identify exposure data gaps and to incorporate genes and disease networks into chemical safety evaluations. Three comprehensive networks addressing CGI, CDA and GDA extracted from the comparative toxicogenomics database (CTD) were constructed. The areas under the receiver operating characteristics curve ranged from 0.85 to 0.97 and were yielded using our methodology using a 10-fold cross validation by a simulation carried out 100 times. As the illustrated examples show, we predicted new potential target genes and diseases for bisphenol A and aspirin. The molecular hypothesis and experimental evidence from published literature for these predictions were provided. The results demonstrated that our method has potential applications for chemical profiling in human health exposure and environmental hazard assessment.

Relative impact of incorporating pharmacokinetics on predicting in vivo hazard and mode of action from high-throughput in vitro toxicity assays

The use of high-throughput in vitro assays has been proposed to play a significant role in the future of toxicity testing. In this study, rat hepatic metabolic clearance and plasma protein binding were measured for 59 ToxCast phase I chemicals. Computational in vitro-to-in vivo extrapolation was used to estimate the daily dose in a rat, called the oral equivalent dose, which would result in steady-state in vivo blood concentrations equivalent to the AC 50 or lowest effective concentration (LEC) across more than 600 ToxCast phase I in vitro assays. Statistical classification analysis was performed using either oral equivalent doses or unadjusted AC 50 /LEC values for the in vitro assays to predict the in vivo effects of the 59 chemicals. Adjusting the in vitro assays for pharmacokinetics did not improve the ability to predict in vivo effects as either a discrete (yes or no) response or a low effect level (LEL) on a continuous dose scale. Interestingly, a comparison of the in vitro assay with the lowest oral equivalent dose with the in vivo endpoint with the lowest LEL suggested that the lowest oral equivalent dose may provide a conservative estimate of the point of departure for a chemical in a dose-response assessment. Furthermore, comparing the oral equivalent doses for the in vitro assays with the in vivo dose range that resulted in adverse effects identified more coincident in vitro assays across chemicals than expected by chance, suggesting that the approach may also be used to identify potential molecular initiating events leading to adversity.

Perspectives on validation of high-throughput assays supporting 21st century toxicity testing

In vitro high-throughput screening (HTS) assays are seeing increasing use in toxicity testing. HTS assays can simultaneously test many chemicals but have seen limited use in the regulatory arena, in part because of the need to undergo rigorous, time-consuming formal validation. Here we discuss streamlining the validation process, specifically for prioritization applications. By prioritization, we mean a process in which less complex, less expensive, and faster assays are used to prioritize which chemicals are subjected first to more complex, expensive, and slower guideline assays. Data from the HTS prioritization assays is intended to provide a priori evidence that certain chemicals have the potential to lead to the types of adverse effects that the guideline tests are assessing. The need for such prioritization approaches is driven by the fact that there are tens of thousands of chemicals to which people are exposed, but the yearly throughput of most guideline assays is small in comparison. The streamlined validation process would continue to ensure the reliability and relevance of assays for this application. We discuss the following practical guidelines: (1) follow current validation practice to the extent possible and practical; (2) make increased use of reference compounds to better demonstrate assay reliability and relevance; (3) de-emphasize the need for cross-laboratory testing; and (4) implement a web-based, transparent, and expedited peer review process.

From QSAR to QSIIR: searching for enhanced computational toxicology models

Quantitative structure activity relationship (QSAR) is the most frequently used modeling approach to explore the dependency of biological, toxicological, or other types of activities/properties of chemicals on their molecular features. In the past two decades, QSAR modeling has been used extensively in drug discovery process. However, the predictive models resulted from QSAR studies have limited use for chemical risk assessment, especially for animal and human toxicity evaluations, due to the low predictivity of new compounds. To develop enhanced toxicity models with independently validated external prediction power, novel modeling protocols were pursued by computational toxicologists based on rapidly increasing toxicity testing data in recent years. This chapter reviews the recent effort in our laboratory to incorporate the biological testing results as descriptors in the toxicity modeling process. This effort extended the concept of QSAR to quantitative structure in vitro-in vivo relationship (QSIIR). The QSIIR study examples provided in this chapter indicate that the QSIIR models that based on the hybrid (biological and chemical) descriptors are indeed superior to the conventional QSAR models that only based on chemical descriptors for several animal toxicity endpoints. We believe that the applications introduced in this review will be of interest and value to researchers working in the field of computational drug discovery and environmental chemical risk assessment.

Water quality assessment using the AREc32 reporter gene assay indicative of the oxidative stress response pathway

The reporter gene assay AREc32 is based on the induction of the Nrf2 mediated oxidative stress response pathway in the human breast cancer cell line MCF7, where eight copies of the antioxidant response element (ARE) are linked to a reporter gene encoding for luciferase. The Nrf2-ARE pathway is responsive to many chemicals that cause oxidative stress, among them a large number of pesticides and skin irritants. We adopted and validated the AREc32 bioassay for water quality testing. tert-Butylhydroquinone served as the positive control, phenol as the negative control and other reactive chemicals were assessed for their specificity. An environmentally relevant reference chemical, benzo(a)pyrene was the most potent inducer of all tested chemicals. The concentration causing an induction ratio (IR) of 1.5 (EC(IR1.5)) was chosen as the effect benchmark value. The assay was applied to 21 water samples ranging from sewage to drinking water, including secondary treatment and various tertiary treatment options (ozonation, biologically activated carbon filtration, membrane filtration, reverse osmosis, advanced oxidation, chlorination, chloramination). The samples were enriched by solid phase extraction. In most samples the oxidative stress response was far more sensitive than cytotoxicity. The primary and secondary treated effluent exceeded the effect threshold IR 1.5 at a relative enrichment factor (REF) of 1, i.e., the native samples were active. All tertiary treated samples were less potent and their EC(IR1.5) lay between REF 1 and 10. The Nrf2 pathway was induced at a REF of approximately 10 for surface waters and drinking water, and above this enrichment cytotoxicity took over in most samples and quenched the induction. The blank (ultrapure water run through the sample enrichment process) was cytotoxic at an REF of 100, which is the limit of concentrations range that can be evaluated. Treatment typically decreased both the cytotoxicity and oxidative stress response apart from drinking water treatment where chlorination caused an increase in oxidative stress response, presumably due to the formation of disinfection by-products. This study demonstrates the relevance and applicability of the oxidative stress response pathway for water quality monitoring.