Mapping Interindividual Variability of Toxicodynamics Using High-Throughput Transcriptomics and Primary Human Hepatocytes from Fifty Donors.

BACKGROUND: Understanding the variability across the human population with respect to toxicodynamic responses after exposure to chemicals, such as environmental toxicants or drugs, is essential to define safety factors for risk assessment to protect the entire population. Activation of cellular stress response pathways are early adverse outcome pathway (AOP) key events of chemical-induced toxicity and would elucidate the estimation of population variability of toxicodynamic responses. OBJECTIVES: We aimed to map the variability in cellular stress response activation in a large panel of primary human hepatocyte (PHH) donors to aid in the quantification of toxicodynamic interindividual variability to derive safety uncertainty factors. METHODS: High-throughput transcriptomics of over 8,000 samples in total was performed covering a panel of 50 individual PHH donors upon 8 to 24 h exposure to broad concentration ranges of four different toxicological relevant stimuli: tunicamycin for the unfolded protein response (UPR), diethyl maleate for the oxidative stress response (OSR), cisplatin for the DNA damage response (DDR), and tumor necrosis factor alpha (TNFα) for NF-κB signaling. Using a population mixed-effect framework, the distribution of benchmark concentrations (BMCs) and maximum fold change were modeled to evaluate the influence of PHH donor panel size on the correct estimation of interindividual variability for the various stimuli. RESULTS: Transcriptome mapping allowed the investigation of the interindividual variability in concentration-dependent stress response activation, where the average of BMCs had a maximum difference of 864-, 13-, 13-, and 259-fold between different PHHs for UPR, OSR, DDR, and NF-κB signaling-related genes, respectively. Population modeling revealed that small PHH panel sizes systematically underestimated the variance and gave low probabilities in estimating the correct human population variance. Estimated toxicodynamic variability factors of stress response activation in PHHs based on this dataset ranged between 1.6 and 6.3. DISCUSSION: Overall, by combining high-throughput transcriptomics and population modeling, improved understanding of interindividual variability in chemical-induced activation of toxicity relevant stress pathways across the human population using a large panel of plated cryopreserved PHHs was established, thereby contributing toward increasing the confidence of in vitro-based prediction of adverse responses, in particular hepatotoxicity. https://doi.org/10.1289/EHP11891.

The Tox21 10K Compound Library: Collaborative Chemistry Advancing Toxicology.

Since 2009, the Tox21 project has screened ∼8500 chemicals in more than 70 high-throughput assays, generating upward of 100 million data points, with all data publicly available through partner websites at the United States Environmental Protection Agency (EPA), National Center for Advancing Translational Sciences (NCATS), and National Toxicology Program (NTP). Underpinning this public effort is the largest compound library ever constructed specifically for improving understanding of the chemical basis of toxicity across research and regulatory domains. Each Tox21 federal partner brought specialized resources and capabilities to the partnership, including three approximately equal-sized compound libraries. All Tox21 data generated to date have resulted from a confluence of ideas, technologies, and expertise used to design, screen, and analyze the Tox21 10K library. The different programmatic objectives of the partners led to three distinct, overlapping compound libraries that, when combined, not only covered a diversity of chemical structures, use-categories, and properties but also incorporated many types of compound replicates. The history of development of the Tox21 "10K" chemical library and data workflows implemented to ensure quality chemical annotations and allow for various reproducibility assessments are described. Cheminformatics profiling demonstrates how the three partner libraries complement one another to expand the reach of each individual library, as reflected in coverage of regulatory lists, predicted toxicity end points, and physicochemical properties. ToxPrint chemotypes (CTs) and enrichment approaches further demonstrate how the combined partner libraries amplify structure-activity patterns that would otherwise not be detected. Finally, CT enrichments are used to probe global patterns of activity in combined ToxCast and Tox21 activity data sets relative to test-set size and chemical versus biological end point diversity, illustrating the power of CT approaches to discern patterns in chemical-activity data sets. These results support a central premise of the Tox21 program: A collaborative merging of programmatically distinct compound libraries would yield greater rewards than could be achieved separately.

Utility of Extrapolating Human S1500+ Genes to the Whole Transcriptome: Tunicamycin Case Study.

The TempO-Seq S1500+ platform(s), now available for human, mouse, rat, and zebrafish, measures a discrete number of genes that are representative of biological and pathway co-regulation across the entire genome in a given species. While measurement of these genes alone provides a direct assessment of gene expression activity, extrapolating expression values to the whole transcriptome (~26 000 genes in humans) can estimate measurements of non-measured genes of interest and increases the power of pathway analysis algorithms by using a larger background gene expression space. Here, we use data from primary hepatocytes of 54 donors that were treated with the endoplasmic reticulum (ER) stress inducer tunicamycin and then measured on the human S1500+ platform containing ~3000 representative genes. Measurements for the S1500+ genes were then used to extrapolate expression values for the remaining human transcriptome. As a case study of the improved downstream analysis achieved by extrapolation, the "measured only" and "whole transcriptome" (measured + extrapolated) gene sets were compared. Extrapolation increased the number of significant genes by 49%, bringing to the forefront many that are known to be associated with tunicamycin exposure. The extrapolation procedure also correctly identified established tunicamycin-related functional pathways reflected by coordinated changes in interrelated genes while maintaining the sample variability observed from the "measured only" genes. Extrapolation improved the gene- and pathway-level biological interpretations for a variety of downstream applications, including differential expression analysis, gene set enrichment pathway analysis, DAVID keyword analysis, Ingenuity Pathway Analysis, and NextBio correlated compound analysis. The extrapolated data highlight the role of metabolism/metabolic pathways, the ER, immune response, and the unfolded protein response, each of which are key activities associated with tunicamycin exposure that were unrepresented or underrepresented in one or more of the analyses of the original "measured only" dataset. Furthermore, the inclusion of the extrapolated genes raised "tunicamycin" from third to first upstream regulator in Ingenuity Pathway Analysis and from sixth to second most correlated compound in NextBio analysis. Therefore, our case study suggests an approach to extend and enhance data from the S1500+ platform for improved insight into biological mechanisms and functional outcomes of diseases, drugs, and other perturbations.

Comparison of Normalization Methods for Analysis of TempO-Seq Targeted RNA Sequencing Data.

Analysis of bulk RNA sequencing (RNA-Seq) data is a valuable tool to understand transcription at the genome scale. Targeted sequencing of RNA has emerged as a practical means of assessing the majority of the transcriptomic space with less reliance on large resources for consumables and bioinformatics. TempO-Seq is a templated, multiplexed RNA-Seq platform that interrogates a panel of sentinel genes representative of genome-wide transcription. Nuances of the technology require proper preprocessing of the data. Various methods have been proposed and compared for normalizing bulk RNA-Seq data, but there has been little to no investigation of how the methods perform on TempO-Seq data. We simulated count data into two groups (treated vs. untreated) at seven-fold change (FC) levels (including no change) using control samples from human HepaRG cells run on TempO-Seq and normalized the data using seven normalization methods. Upper Quartile (UQ) performed the best with regard to maintaining FC levels as detected by a limma contrast between treated vs. untreated groups. For all FC levels, specificity of the UQ normalization was greater than 0.84 and sensitivity greater than 0.90 except for the no change and +1.5 levels. Furthermore, K-means clustering of the simulated genes normalized by UQ agreed the most with the FC assignments [adjusted Rand index (ARI) = 0.67]. Despite having an assumption of the majority of genes being unchanged, the DESeq2 scaling factors normalization method performed reasonably well as did simple normalization procedures counts per million (CPM) and total counts (TCs). These results suggest that for two class comparisons of TempO-Seq data, UQ, CPM, TC, or DESeq2 normalization should provide reasonably reliable results at absolute FC levels ≥2.0. These findings will help guide researchers to normalize TempO-Seq gene expression data for more reliable results.

Evaluation of 5-day In Vivo Rat Liver and Kidney With High-throughput Transcriptomics for Estimating Benchmark Doses of Apical Outcomes.

A 5-day in vivo rat model was evaluated as an approach to estimate chemical exposures that may pose minimal risk by comparing benchmark dose (BMD) values for transcriptional changes in the liver and kidney to BMD values for toxicological endpoints from traditional toxicity studies. Eighteen chemicals, most having been tested by the National Toxicology Program in 2-year bioassays, were evaluated. Some of these chemicals are potent hepatotoxicants (eg, DE71, PFOA, and furan) in rodents, some exhibit toxicity but have minimal hepatic effects (eg, acrylamide and α,ß-thujone), and some exhibit little overt toxicity (eg, ginseng and milk thistle extract) based on traditional toxicological evaluations. Male Sprague Dawley rats were exposed once daily for 5 consecutive days by oral gavage to 8-10 dose levels for each chemical. Liver and kidney were collected 24 h after the final exposure and total RNA was assayed using high-throughput transcriptomics (HTT) with the rat S1500+ platform. HTT data were analyzed using BMD Express 2 to determine transcriptional gene set BMD values. BMDS was used to determine BMD values for histopathological effects from chronic or subchronic toxicity studies. For many of the chemicals, the lowest transcriptional BMDs from the 5-day assays were within a factor of 5 of the lowest histopathological BMDs from the toxicity studies. These data suggest that using HTT in a 5-day in vivo rat model provides reasonable estimates of BMD values for traditional apical endpoints. This approach may be useful to prioritize chemicals for further testing while providing actionable data in a timely and cost-effective manner.

KRAS-retroviral fusion transcripts and gene amplification in arsenic-transformed, human prostate CAsE-PE cancer cells.

CAsE-PE cells are an arsenic-transformed, human prostate epithelial line containing oncogenic mutations in KRAS compared to immortalized, normal KRAS parent cells, RWPE-1. We previously reported increased copy number of mutated KRAS in CAsE-PE cells, suggesting gene amplification. Here, KRAS flanking genomic and transcriptomic regions were sequenced in CAsE-PE cells for insight into KRAS amplification. Comparison of DNA-Seq and RNA-Seq showed increased reads from background aligning to all KRAS exons in CAsE-PE cells, while a uniform DNA-Seq read distribution occurred in RWPE-1 cells with normal transcript expression. We searched for KRAS fusions in DNA and RNA sequencing data finding a portion of reads aligning to KRAS and viral sequence. After generation of cDNA from total RNA, short and long KRAS probes were generated to hybridize cDNA and KRAS enriched fragments were PacBio sequenced. More KRAS reads were captured from CAsE-PE cDNA versus RWPE-1 by each probe set. Only CAsE-PE cDNA showed KRAS viral fusion transcripts, primarily mapping to LTR and endogenous retrovirus sequences on either 5'- or 3'-ends of KRAS. Most KRAS viral fusion transcripts contained 4 to 6 exons but some PacBio sequences were in unusual orientations, suggesting viral insertions within the gene body. Additionally, conditioned media was extracted for potential retroviral particles. RNA-Seq of culture media isolates identified KRAS retroviral fusion transcripts in CAsE-PE media only. Truncated KRAS transcripts suggested multiple retroviral integration sites occurred within the KRAS gene producing KRAS retroviral fusions of various lengths. Findings suggest activation of endogenous retroviruses in arsenic carcinogenesis should be explored.

DNA damage responses in murine Pre-B cells with genetic deficiencies in damage response genes.

DNA damage can be generated in multiple ways from genotoxic and physiologic sources. Genotoxic damage is known to disrupt cellular functions and is lethal if not repaired properly. We compare the transcriptional programs activated in response to genotoxic DNA damage induced by ionizing radiation (IR) in abl pre-B cells from mice deficient in DNA damage response (DDR) genes Atm, Mre11, Mdc1, H2ax, 53bp1, and DNA-PKcs. We identified a core IR-specific transcriptional response that occurs in abl pre-B cells from WT mice and compared the response of the other genotypes to the WT response. We also identified genotype specific responses and compared those to each other. The WT response includes many processes involved in lymphocyte development and immune response, as well as responses associated with the molecular mechanisms of cancer, such as TP53 signaling. As expected, there is a range of similarity in transcriptional profiles in comparison to WT cells, with Atm-/- cells being the most different from the core WT DDR and Mre11 hypomorph (Mre11A/A) cells also very dissimilar to WT and other genotypes. For example, NF-kB-related signaling and CD40 signaling are deficient in both Atm-/- and Mre11A/A cells, but present in all other genotypes. In contrast, IR-induced TP53 signaling is seen in the Mre11A/A cells, while these responses are not seen in the Atm-/- cells. By examining the similarities and differences in the signaling pathways in response to IR when specific genes are absent, our results further illustrate the contribution of each gene to the DDR. The microarray gene expression data discussed in this paper have been deposited in NCBI's Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo/) and are accessible under accession number GSE116388.

Development of a Zebrafish S1500+ Sentinel Gene Set for High-Throughput Transcriptomics.

Sentinel gene sets have been developed with the purpose of maximizing the information from targeted transcriptomic platforms. We recently described the development of an S1500+ sentinel gene set, which was built for the human transcriptome, utilizing a data- and knowledge-driven hybrid approach to select a small subset of genes that optimally capture transcriptional diversity, correlation with other genes based on large-scale expression profiling, and known pathway annotation within the human genome. While this detailed bioinformatics approach for gene selection can in principle be applied to other species, the reliability of the resulting gene set depends on availability of a large body of transcriptomics data. For the model organism zebrafish, we aimed to create a similar sentinel gene set (Zf S1500+ gene set); however, there is insufficient standardized expression data in the public domain to train the gene correlation model. Therefore, our strategy was to use human-zebrafish ortholog mapping of the human S1500+ genes and nominations from experts in the zebrafish scientific community. In this study, we present the bioinformatics curation and refinement process to produce the final Zf S1500+ gene set, explore whole transcriptome extrapolation using this gene set, and assess pathway-level inference. This gene set will add value to targeted high-throughput transcriptomics in zebrafish for toxicogenomic screening and other research domains.

Arsenite malignantly transforms human prostate epithelial cells in vitro by gene amplification of mutated KRAS.

Inorganic arsenic is an environmental human carcinogen of several organs including the urinary tract. RWPE-1 cells are immortalized, non-tumorigenic, human prostate epithelia that become malignantly transformed into the CAsE-PE line after continuous in vitro exposure to 5µM arsenite over a period of months. For insight into in vitro arsenite transformation, we performed RNA-seq for differential gene expression and targeted sequencing of KRAS. We report >7,000 differentially expressed transcripts in CAsE-PE cells compared to RWPE-1 cells at >2-fold change, q<0.05 by RNA-seq. Notably, KRAS expression was highly elevated in CAsE-PE cells, with pathway analysis supporting increased cell proliferation, cell motility, survival and cancer pathways. Targeted DNA sequencing of KRAS revealed a mutant specific allelic imbalance, 'MASI', frequently found in primary clinical tumors. We found high expression of a mutated KRAS transcript carrying oncogenic mutations at codons 12 and 59 and many silent mutations, accompanied by lower expression of a wild-type allele. Parallel cultures of RWPE-1 cells retained a wild-type KRAS genotype. Copy number analysis and sequencing showed amplification of the mutant KRAS allele. KRAS is expressed as two splice variants, KRAS4a and KRAS4b, where variant 4b is more prevalent in normal cells compared to greater levels of variant 4a seen in tumor cells. 454 Roche sequencing measured KRAS variants in each cell type. We found KRAS4a as the predominant transcript variant in CAsE-PE cells compared to KRAS4b, the variant expressed primarily in RWPE-1 cells and in normal prostate, early passage, primary epithelial cells. Overall, gene expression data were consistent with KRAS-driven proliferation pathways found in spontaneous tumors and malignantly transformed cell lines. Arsenite is recognized as an important environmental carcinogen, but it is not a direct mutagen. Further investigations into this in vitro transformation model will focus on genomic events that cause arsenite-mediated mutation and overexpression of KRAS in CAsE-PE cells.

The Power of Resolution: Contextualized Understanding of Biological Responses to Liver Injury Chemicals Using High-throughput Transcriptomics and Benchmark Concentration Modeling.

Prediction of human response to chemical exposures is a major challenge in both pharmaceutical and toxicological research. Transcriptomics has been a powerful tool to explore chemical-biological interactions, however, limited throughput, high-costs, and complexity of transcriptomic interpretations have yielded numerous studies lacking sufficient experimental context for predictive application. To address these challenges, we have utilized a novel high-throughput transcriptomics (HTT) platform, TempO-Seq, to apply the interpretive power of concentration-response modeling with exposures to 24 reference compounds in both differentiated and non-differentiated human HepaRG cell cultures. Our goals were to (1) explore transcriptomic characteristics distinguishing liver injury compounds, (2) assess impacts of differentiation state of HepaRG cells on baseline and compound-induced responses (eg, metabolically-activated), and (3) identify and resolve reference biological-response pathways through benchmark concentration (BMC) modeling. Study data revealed the predictive utility of this approach to identify human liver injury compounds by their respective BMCs in relation to human internal exposure plasma concentrations, and effectively distinguished drug analogs with varied associations of human liver injury (eg, withdrawn therapeutics trovafloxacin and troglitazone). Impacts of cellular differentiation state (proliferated vs differentiated) were revealed on baseline drug metabolizing enzyme expression, hepatic receptor signaling, and responsiveness to metabolically-activated toxicants (eg, cyclophosphamide, benzo(a)pyrene, and aflatoxin B1). Finally, concentration-response modeling enabled efficient identification and resolution of plausibly-relevant biological-response pathways through their respective pathway-level BMCs. Taken together, these findings revealed HTT paired with differentiated in vitro liver models as an effective tool to model, explore, and interpret toxicological and pharmacological interactions.

BMDExpress 2: enhanced transcriptomic dose-response analysis workflow.

SUMMARY: A new version (version 2) of the genomic dose-response analysis software, BMDExpress, has been created. The software addresses the increasing use of transcriptomic dose-response data in toxicology, drug design, risk assessment and translational research. In this new version, we have implemented additional statistical filtering options (e.g. Williams' trend test), curve fitting models, Linux and Macintosh compatibility and support for additional transcriptomic platforms with up-to-date gene annotations. Furthermore, we have implemented extensive data visualizations, on-the-fly data filtering, and a batch-wise analysis workflow. We have also significantly re-engineered the code base to reflect contemporary software engineering practices and streamline future development. The first version of BMDExpress was developed in 2007 to meet an unmet demand for easy-to-use transcriptomic dose-response analysis software. Since its original release, however, transcriptomic platforms, technologies, pathway annotations and quantitative methods for data analysis have undergone a large change necessitating a significant re-development of BMDExpress. To that end, as of 2016, the National Toxicology Program assumed stewardship of BMDExpress. The result is a modernized and updated BMDExpress 2 that addresses the needs of the growing toxicogenomics user community. AVAILABILITY AND IMPLEMENTATION: BMDExpress 2 is available at https://github.com/auerbachs/BMDExpress-2/releases. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Detection and Prioritization of Developmentally Neurotoxic and/or Neurotoxic Compounds Using Zebrafish.

The standard methods for toxicity testing using rodent models cannot keep pace with the increasing number of chemicals in our environment due to time and resource limitations. Hence, there is an unmet need for fast, sensitive, and cost-effective alternate models to reliably predict toxicity. As part of Tox21 Phase III's effort, a 90-compound library was created and made available to researchers to screen for neurotoxicants using novel technology and models. The chemical library was evaluated in zebrafish in a dose-range finding test for embryo-toxicity (ie, mortality or morphological alterations induced by each chemical). In addition, embryos exposed to the lowest effect level and nonobservable effect level were used to measure the internal concentration of the chemicals within the embryos by bioanalysis. Finally, considering the lowest effect level as the highest testing concentration, a functional assay was performed based on locomotor activity alteration in response to light-dark changes. The quality control chemicals included in the library, ie, negative controls and replicated chemicals, indicate that the assays performed were reliable. The use of analytical chemistry pointed out the importance of measuring chemical concentration inside embryos, and in particular, in the case of negative chemicals to avoid false negative classification. Overall, the proposed approach presented a good sensitivity and supports the inclusion of zebrafish assays as a reliable, relevant, and efficient screening tool to identify, prioritize, and evaluate chemical toxicity.

Screening for Developmental Neurotoxicity at the National Toxicology Program: The Future Is Here.

The National Toxicology Program (NTP) receives requests to evaluate chemicals with potential to cause adverse health effects, including developmental neurotoxicity (DNT). Some recent requests have included classes of chemicals such as flame retardants, polycyclic aromatic compounds, perfluoroalkyl substances, and bisphenol A analogs with approximately 20-50 compounds per class, many of which include commercial mixtures. However, all the compounds within a class cannot be tested using traditional DNT animal testing guideline studies due to resource and time limitations. Hence, a rapid and biologically relevant screening approach is required to prioritize compounds for further in vivo testing. Because neurodevelopment is a complex process involving multiple distinct cellular processes, one assay will unlikely address the complexity. Hence, the NTP sought to characterize a battery of in vitro and alternative animal assays to quantify chemical effects on a variety of neurodevelopmental processes. A culmination of this effort resulted in a NTP-hosted collaborative project with approximately 40 participants spanning across domains of academia, industry, government, and regulatory agencies; collaborators presented data on cell-based assays and alternative animal models that was generated using a targeted set of compounds provided by the NTP. The NTP analyzed the assay results using benchmark concentration (BMC) modeling to be able to compare results across the divergent assays. The results were shared with the contributing researchers on a private web application during the workshop, and are now publicly available. This article highlights the overview and goals of the project, and describes the NTP's approach in creating the chemical library, development of NTPs data analysis strategy, and the structure of the web application. Finally, we discuss key issues with emphasis on the utility of this approach, and knowledge gaps that need to be addressed for its use in regulatory decision making.

A Comparison of the TempO-Seq S1500+ Platform to RNA-Seq and Microarray Using Rat Liver Mode of Action Samples.

The TempO-SeqTM platform allows for targeted transcriptomic analysis and is currently used by many groups to perform high-throughput gene expression analysis. Herein we performed a comparison of gene expression characteristics measured using 45 purified RNA samples from the livers of rats exposed to chemicals that fall into one of five modes of action (MOAs). These samples have been previously evaluated using AffymetrixTM rat genome 230 2.0 microarrays and Illumina® whole transcriptome RNA-Seq. Comparison of these data with TempO-Seq analysis using the rat S1500+ beta gene set identified clear differences in the platforms related to signal to noise, root mean squared error, and/or sources of variability. Microarray and TempO-Seq captured the most variability in terms of MOA and chemical treatment whereas RNA-Seq had higher noise and larger differences between samples within a MOA. However, analysis of the data by hierarchical clustering, gene subnetwork connectivity and biological process representation of MOA-varying genes revealed that the samples clearly grouped by treatment as opposed to gene expression platform. Overall these findings demonstrate that the results from the TempO-Seq platform are consistent with findings on other more established approaches for measuring the genome-wide transcriptome.

Toxicity profiling of flame retardants in zebrafish embryos using a battery of assays for developmental toxicity, neurotoxicity, cardiotoxicity and hepatotoxicity toward human relevance.

Following the voluntary phase-out of brominated flame retardants (BFRs) due to their environmental persistence and toxicity, the organophosphorus flame retardants (OPFRs) are emerging replacements. However, there is limited information on the potential human health effects of the OPFRs. Zebrafish embryos are a viable vertebrate model organism with many advantages for high throughput testing toward human hazard assessment. We utilized zebrafish embryos to assess developmental toxicity, neurotoxicity, cardiotoxicity and hepatotoxicity, of eight replacement OPFRs: (triphenyl phosphate [TPHP], isopropylated phenyl phosphate [IPP], 2-ethylhexyl diphenyl phosphate [EHDP], tert-butylated phenyl diphenyl phosphate [BPDP], trimethyl phenyl phosphate [TMPP], isodecyl diphenyl phosphate [IDDP], tris(1,3-dichloroisopropyl) phosphate [TDCIPP], and tris(2-chloroethyl) phosphate [TCEP]) and two BFRs (3,3',5,5'- tetrabromobisphenol A [TBBPA] and 2,2'4,4'-brominated diphenyl ether [BDE-47]). To determine potential effects on teratogenicity, embryos were exposed to flame retardants (FRs) at 4 h post fertilization (hpf) to 4 days post fertilization (dpf) and morphological alterations and corresponding survival were evaluated at 2 and 4 dpf. Internal concentrations were measured in larvae used in this assay by liquid chromatography-mass spectrometry. Locomotor activity was assessed in larvae treated for 48 h (from 3 dpf to 5 dpf), followed by hepatotoxicity evaluation. Finally, alterations in heart rate and rhythmicity were assessed to determine cardiotoxicity in 48 hpf embryos exposed to compounds for 3 h. Results suggest that several OPFRs (BPDP, EHDP; IPP, TMPP; TPHP and TDCIPP) produced adverse effects in multiple target organs at concentrations comparable to the two BFRs. As these OPFRs have the capacity to disrupt an integrated vertebrate model, they potentially have the capacity to affect mammalian biology. Then, we compared the lowest effective levels (LEL) in zebrafish with estimated or measured human plasma concentrations using biomonitoring data (human plasma, breast milk, handwipe samples and house dust) and a high throughput toxicokinetic (HTTK) model. Results indicate that for some compounds, the nominal LELs were within the range of human exposures, while internal LELs in zebrafish are above internal exposures in humans. These findings demonstrate the value of the zebrafish model as a relevant screening tool and support the need for further hazard characterization of the OPFRs.

Comprehensive Analyses and Prioritization of Tox21 10K Chemicals Affecting Mitochondrial Function by in-Depth Mechanistic Studies.

BACKGROUND: A central challenge in toxicity testing is the large number of chemicals in commerce that lack toxicological assessment. In response, the Tox21 program is re-focusing toxicity testing from animal studies to less expensive and higher throughput in vitro methods using target/pathway-specific, mechanism-driven assays. OBJECTIVES: Our objective was to use an in-depth mechanistic study approach to prioritize and characterize the chemicals affecting mitochondrial function. METHODS: We used a tiered testing approach to prioritize for more extensive testing 622 compounds identified from a primary, quantitative high-throughput screen of 8,300 unique small molecules, including drugs and industrial chemicals, as potential mitochondrial toxicants by their ability to significantly decrease the mitochondrial membrane potential (MMP). Based on results from secondary MMP assays in HepG2 cells and rat hepatocytes, 34 compounds were selected for testing in tertiary assays that included formation of reactive oxygen species (ROS), upregulation of p53 and nuclear erythroid 2-related factor 2/antioxidant response element (Nrf2/ARE), mitochondrial oxygen consumption, cellular Parkin translocation, and larval development and ATP status in the nematode Caenorhabditis elegans. RESULTS: A group of known mitochondrial complex inhibitors (e.g., rotenone) and uncouplers (e.g., chlorfenapyr), as well as potential novel complex inhibitors and uncouplers, were detected. From this study, we identified four not well-characterized potential mitochondrial toxicants (lasalocid, picoxystrobin, pinacyanol, and triclocarban) that merit additional in vivo characterization. CONCLUSIONS: The tier-based approach for identifying and mechanistically characterizing mitochondrial toxicants can potentially reduce animal use in toxicological testing. https://doi.org/10.1289/EHP2589.

The US Federal Tox21 Program: A strategic and operational plan for continued leadership.

The traditional approaches to toxicity testing have posed multiple challenges for evaluating the safety of commercial chemicals, pesticides, food additives/contaminants, and medical products.The challenges include number of chemicals that need to be tested, time and resource intensive nature of traditional toxicity tests, and unexpected adverse effects that occur in pharmaceutical clinical trials despite the extensive toxicological testing.Over a decade ago, the U.S. Environmental Protection Agency (EPA), National Toxicology Program (NTP), National Center for Advancing Translational Sciences (NCATS), and the Food and Drug Administration (FDA) formed a federal consortium for "Toxicology in the 21st Century" (Tox21) with a focus on developing and evaluating in vitro high-throughput screening (HTS) methods for hazard identification and providing mechanistic insights.The Tox21 consortium generated data on thousands of pharmaceuticals and datapoor chemicals, developed better understanding of the limits and applications of in vitro methods, and enabled incorporation of HTS data into regulatory decisions. To more broadly address the challenges in toxicology, Tox21 has developed a new strategic and operational plan that expands the focus of its research activities. The new focus areas include developing an expanded portfolio of alternative test systems, addressing technical limitations of in vitrotest systems, curating legacy in vivo toxicity testing data, establishing scientific confidence in the in vitrotest systems, and refining alternative methods for characterizing pharmacokinetics and in vitro assay disposition.The new Tox21 strategic and operational plan addresses key challenges to advance toxicology testing and will benefit both the organizations involved and the toxicology community.

A hybrid gene selection approach to create the S1500+ targeted gene sets for use in high-throughput transcriptomics.

Changes in gene expression can help reveal the mechanisms of disease processes and the mode of action for toxicities and adverse effects on cellular responses induced by exposures to chemicals, drugs and environment agents. The U.S. Tox21 Federal collaboration, which currently quantifies the biological effects of nearly 10,000 chemicals via quantitative high-throughput screening(qHTS) in in vitro model systems, is now making an effort to incorporate gene expression profiling into the existing battery of assays. Whole transcriptome analyses performed on large numbers of samples using microarrays or RNA-Seq is currently cost-prohibitive. Accordingly, the Tox21 Program is pursuing a high-throughput transcriptomics (HTT) method that focuses on the targeted detection of gene expression for a carefully selected subset of the transcriptome that potentially can reduce the cost by a factor of 10-fold, allowing for the analysis of larger numbers of samples. To identify the optimal transcriptome subset, genes were sought that are (1) representative of the highly diverse biological space, (2) capable of serving as a proxy for expression changes in unmeasured genes, and (3) sufficient to provide coverage of well described biological pathways. A hybrid method for gene selection is presented herein that combines data-driven and knowledge-driven concepts into one cohesive method. Our approach is modular, applicable to any species, and facilitates a robust, quantitative evaluation of performance. In particular, we were able to perform gene selection such that the resulting set of "sentinel genes" adequately represents all known canonical pathways from Molecular Signature Database (MSigDB v4.0) and can be used to infer expression changes for the remainder of the transcriptome. The resulting computational model allowed us to choose a purely data-driven subset of 1500 sentinel genes, referred to as the S1500 set, which was then augmented using a knowledge-driven selection of additional genes to create the final S1500+ gene set. Our results indicate that the sentinel genes selected can be used to accurately predict pathway perturbations and biological relationships for samples under study.

Correction: Real-time cell toxicity profiling of Tox21 10K compounds reveals cytotoxicity dependent toxicity pathway linkage.

[This corrects the article DOI: 10.1371/journal.pone.0177902.].