Recommended approaches in the application of toxicogenomics to derive points of departure for chemical risk assessment

Transcriptional Responses Reveal Similarities Between Preclinical Rat Liver Testing Systems

Toxicogenomics (TGx) is an important tool to gain an enhanced understanding of toxicity at the molecular level. Previously, we developed a pair ranking (PRank) method to assess in vitro to in vivo extrapolation (IVIVE) using toxicogenomic datasets from the Open Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System (TG-GATEs) database. With this method, we investiagted three important questions that were not addressed in our previous study: (1) is a 1-day in vivo short-term assay able to replace the 28-day standard and expensive toxicological assay? (2) are some biological processes more conservative across different preclinical testing systems than others? and (3) do these preclinical testing systems have the similar resolution in differentiating drugs by their therapeutic uses? For question 1, a high similarity was noted (PRank score = 0.90), indicating the potential utility of shorter term in vivo studies to predict outcome in longer term and more expensive in vivo model systems. There was a moderate similarity between rat primary hepatocytes and in vivo repeat-dose studies (PRank score = 0.71) but a low similarity (PRank score = 0.56) between rat primary hepatocytes and in vivo single dose studies. To address question 2, we limited the analysis to gene sets relevant to specific toxicogenomic pathways and we found that pathways such as lipid metabolism were consistently over-represented in all three assay systems. For question 3, all three preclinical assay systems could distinguish compounds from different therapeutic categories. This suggests that any noted differences in assay systems was biological process-dependent and furthermore that all three systems have utility in assessing drug responses within a certain drug class. In conclusion, this comparison of three commonly used rat TGx systems provides useful information in utility and application of TGx assays.

Population-based dose-response analysis of liver transcriptional response to trichloroethylene in mouse

Studies of gene expression are common in toxicology and provide important clues to mechanistic understanding of adverse effects of chemicals. Most prior studies have been performed in a single strain or cell line; however, gene expression is heavily influenced by the genetic background, and these genotype-expression differences may be key drivers of inter-individual variation in response to chemical toxicity. In this study, we hypothesized that the genetically diverse Collaborative Cross mouse population can be used to gain insight and suggest mechanistic hypotheses for the dose- and genetic background-dependent effects of chemical exposure. This hypothesis was tested using a model liver toxicant trichloroethylene (TCE). Liver transcriptional responses to TCE exposure were evaluated 24 h after dosing. Transcriptomic dose-responses were examined for both TCE and its major oxidative metabolite trichloroacetic acid (TCA). As expected, peroxisome- and fatty acid metabolism-related pathways were among the most dose-responsive enriched pathways in all strains. However, nearly half of the TCE-induced liver transcriptional perturbation was strain-dependent, with abundant evidence of strain/dose interaction, including in the peroxisomal signaling-associated pathways. These effects were highly concordant between the administered TCE dose and liver levels of TCA. Dose-response analysis of gene expression at the pathway level yielded points of departure similar to those derived from the traditional toxicology studies for both non-cancer and cancer effects. Mapping of expression-genotype-dose relationships revealed some significant associations; however, the effects of TCE on gene expression in liver appear to be highly polygenic traits that are challenging to positionally map. This study highlights the usefulness of mouse population-based studies in assessing inter-individual variation in toxicological responses, but cautions that genetic mapping may be challenging because of the complexity in gene exposure-dose relationships.

A Reduced Transcriptome Approach to Assess Environmental Toxicants Using Zebrafish Embryo Test

Omics approaches can monitor responses and alterations of biological pathways at genome-scale, which are useful to predict potential adverse effects by environmental toxicants. However, high throughput application of transcriptomics in chemical assessment is limited due to the high cost and lack of "standardized" toxicogenomic methods. Here, a reduced zebrafish transcriptome (RZT) approach was developed to represent the whole transcriptome and to profile bioactivity of chemical and environmental mixtures in zebrafish embryo. RZT gene set of 1637 zebrafish Entrez genes was designed to cover a wide range of biological processes, and to faithfully capture gene-level and pathway-level changes by toxicants compared with the whole transcriptome. Concentration-response modeling was used to calculate the effect concentrations (ECs) of DEGs and corresponding molecular pathways. To validate the RZT approach, quantitative analysis of gene expression by RNA-ampliseq technology was used to identify differentially expressed genes (DEGs) at 32 hpf following exposure to seven serial dilutions of reference chemical BPA (10-10E^-5μM) or each of four water samples ranging from wastewater to drinking water (relative enrichment factors 10-6.4 × 10^-4). The RZT-ampliseq-embryo approach was both sensitive and able to identify a wide spectrum of biological activities associated with BPA exposure. Water quality was benchmarked based on the sensitivity distribution curve of biological pathways detected using RZT-ampliseq-embryo. Finally, the most sensitive biological pathways were identified, including those linked with adverse reproductive outcomes, genotoxicity and development outcomes. RZT-ampliseq-embryo approach provides an efficient and cost-effective tool to prioritize toxicants based on responsiveness of biological pathways.

Differential Hepatic Gene Expression Profile of Male Fathead Minnows Exposed to Daily Varying Dose of Environmental Contaminants Individually and in Mixture

Environmental contaminants are known to impair reproduction, metabolism and development in wild life and humans. To investigate the mechanisms underlying adverse effects of contaminants, fathead minnows were exposed to a number of endocrine disruptive chemicals (EDCs) including Nonylphenol (NP), bisphenol-A (BPA), Di(2-ethylhexyl) phthalate (DEHP), and a mixture of the three chemicals for 21 days, followed by determination of the liver transcriptome by expression microarrays. Pathway analysis revealed a distinct mode of action for the individual chemicals and their mixture. The results showed expression changes in over 980 genes in response to exposure to these EDC contaminants individually and in mixture. Ingenuity Pathway core and toxicity analysis were used to identify the biological processes, pathways and the top regulators affected by these compounds. A number of canonical pathways were significantly altered, including cell cycle & proliferation, lipid metabolism, inflammatory, innate immune response, stress response, and drug metabolism. We identified 18 genes that were expressed in all individual and mixed treatments. Relevant candidate genes identified from expression microarray data were verified using quantitative PCR. We were also able to identify specific genes affected by NP, BPA, and DEHP individually, but were also affected by exposure to the mixture of the contaminants. Overall the results of this study provide novel information on the adverse health impact of contaminants tested based on pathway analysis of transcriptome data. Furthermore, the results identify a number of new biomarkers that can potentially be used for screening environmental contaminants.

A Pipeline for High-Throughput Concentration Response Modeling of Gene Expression for Toxicogenomics

Cell-based assays are an attractive option to measure gene expression response to exposure, but the cost of whole-transcriptome RNA sequencing has been a barrier to the use of gene expression profiling for in vitro toxicity screening. In addition, standard RNA sequencing adds variability due to variable transcript length and amplification. Targeted probe-sequencing technologies such as TempO-Seq, with transcriptomic representation that can vary from hundreds of genes to the entire transcriptome, may reduce some components of variation. Analyses of high-throughput toxicogenomics data require renewed attention to read-calling algorithms and simplified dose–response modeling for datasets with relatively few samples. Using data from induced pluripotent stem cell-derived cardiomyocytes treated with chemicals at varying concentrations, we describe here and make available a pipeline for handling expression data generated by TempO-Seq to align reads, clean and normalize raw count data, identify differentially expressed genes, and calculate transcriptomic concentration–response points of departure. The methods are extensible to other forms of concentration–response gene-expression data, and we discuss the utility of the methods for assessing variation in susceptibility and the diseased cellular state.

Editor's Highlight: Comparative Dose-Response Analysis of Liver and Kidney Transcriptomic Effects of Trichloroethylene and Tetrachloroethylene in B6C3F1 Mouse

Trichloroethylene (TCE) and tetrachloroethylene (PCE) are ubiquitous environmental contaminants and occupational health hazards. Recent health assessments of these agents identified several critical data gaps, including lack of comparative analysis of their effects. This study examined liver and kidney effects of TCE and PCE in a dose-response study design. Equimolar doses of TCE (24, 80, 240, and 800 mg/kg) or PCE (30, 100, 300, and 1000 mg/kg) were administered by gavage in aqueous vehicle to male B6C3F1/J mice. Tissues were collected 24 h after exposure. Trichloroacetic acid (TCA), a major oxidative metabolite of both compounds, was measured and RNA sequencing was performed. PCE had a stronger effect on liver and kidney transcriptomes, as well as greater concentrations of TCA. Most dose-responsive pathways were common among chemicals/tissues, with the strongest effect on peroxisomal β-oxidation. Effects on liver and kidney mitochondria-related pathways were notably unique to PCE. We performed dose-response modeling of the transcriptomic data and compared the resulting points of departure (PODs) to those for apical endpoints derived from long-term studies with these chemicals in rats, mice, and humans, converting to human equivalent doses using tissue-specific dosimetry models. Tissue-specific acute transcriptional effects of TCE and PCE occurred at human equivalent doses comparable to those for apical effects. These data are relevant for human health assessments of TCE and PCE as they provide data for dose-response analysis of the toxicity mechanisms. Additionally, they provide further evidence that transcriptomic data can be useful surrogates for in vivo PODs, especially when toxicokinetic differences are taken into account.

Benchmark Dose Modeling Estimates of the Concentrations of Inorganic Arsenic That Induce Changes to the Neonatal Transcriptome, Proteome, and Epigenome in a Pregnancy Cohort

Prenatal inorganic arsenic (iAs) exposure influences the expression of critical genes and proteins associated with adverse outcomes in newborns, in part through epigenetic mediators. The doses at which these genomic and epigenomic changes occur have yet to be evaluated in the context of dose-response modeling. The goal of the present study was to estimate iAs doses that correspond to changes in transcriptomic, proteomic, epigenomic, and integrated multi-omic signatures in human cord blood through benchmark dose (BMD) modeling. Genome-wide DNA methylation, microRNA expression, mRNA expression, and protein expression levels in cord blood were modeled against total urinary arsenic (U-tAs) levels from pregnant women exposed to varying levels of iAs. Dose-response relationships were modeled in BMDExpress, and BMDs representing 10% response levels were estimated. Overall, DNA methylation changes were estimated to occur at lower exposure concentrations in comparison to other molecular endpoints. Multi-omic module eigengenes were derived through weighted gene co-expression network analysis, representing co-modulated signatures across transcriptomic, proteomic, and epigenomic profiles. One module eigengene was associated with decreased gestational age occurring alongside increased iAs exposure. Genes/proteins within this module eigengene showed enrichment for organismal development, including potassium voltage-gated channel subfamily Q member 1 (KCNQ1), an imprinted gene showing differential methylation and expression in response to iAs. Modeling of this prioritized multi-omic module eigengene resulted in a BMD(BMDL) of 58(45) μg/L U-tAs, which was estimated to correspond to drinking water arsenic concentrations of 51(40) μg/L. Results are in line with epidemiological evidence supporting effects of prenatal iAs occurring at levels <100 μg As/L urine. Together, findings present a variety of BMD measures to estimate doses at which prenatal iAs exposure influences neonatal outcome-relevant transcriptomic, proteomic, and epigenomic profiles.

Applying 'omics technologies in chemicals risk assessment: Report of an ECETOC workshop

Prevailing knowledge gaps in linking specific molecular changes to apical outcomes and methodological uncertainties in the generation, storage, processing, and interpretation of 'omics data limit the application of 'omics technologies in regulatory toxicology. Against this background, the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) convened a workshop Applying 'omics technologies in chemicals risk assessment that is reported herein. Ahead of the workshop, multi-expert teams drafted frameworks on best practices for (i) a Good-Laboratory Practice-like context for collecting, storing and curating 'omics data; (ii) the processing of 'omics data; and (iii) weight-of-evidence approaches for integrating 'omics data. The workshop participants confirmed the relevance of these Frameworks to facilitate the regulatory applicability and use of 'omics data, and the workshop discussions provided input for their further elaboration. Additionally, the key objective (iv) to establish approaches to connect 'omics perturbations to phenotypic alterations was addressed. Generally, it was considered promising to strive to link gene expression changes and pathway perturbations to the phenotype by mapping them to specific adverse outcome pathways. While further work is necessary before gene expression changes can be used to establish safe levels of substance exposure, the ECETOC workshop provided important incentives towards achieving this goal.

Integration of the TGx-28.65 genomic biomarker with the flow cytometry micronucleus test to assess the genotoxicity of disperse orange and 1,2,4-benzenetriol in human TK6 cells

In vitro gene expression signatures to predict toxicological responses can provide mechanistic context for regulatory testing. We previously developed the TGx-28.65 genomic biomarker from a database of gene expression profiles derived from human TK6 cells exposed to 28 well-known compounds. The biomarker comprises 65 genes that can classify chemicals as DNA damaging or non-DNA damaging. In this study, we applied the TGx-28.65 genomic biomarker in parallel with the in vitro micronucleus (MN) assay to determine if two chemicals of regulatory interest at Health Canada, disperse orange (DO: the orange azo dye 3-[[4-[(4-Nitrophenyl)azo]phenyl] benzylamino]propanenitrile) and 1,2,4-benzenetriol (BT: a metabolite of benzene) are genotoxic or non-genotoxic. Both chemicals caused dose-dependent declines in relative survival and increases in apoptosis. A strong significant increase in MN induction was observed for all concentrations of BT; the top two concentrations of DO also caused a statistically significant increase in MN, but these increases were <2-fold above controls. TGx-28.65 analysis classified BT as genotoxic at all three concentrations and DO as genotoxic at the mid and high concentrations. Thus, although DO only caused a small increase in MN, this response was sufficient to induce a cellular DNA damage response. Benchmark dose modeling confirmed that BT is much more potent than DO. The results strongly suggest that follow-up work is required to assess whether DO and BT are also genotoxic in vivo. This is particularly important for DO, which may require metabolic activation by bacterial gut flora to fully induce its genotoxic potential. Our previously published data and this proof of concept study suggest that the TGx-28.65 genomic biomarker has the potential to add significant value to existing approaches used to assess genotoxicity.

High-Throughput Screening Data Interpretation in the Context of In Vivo Transcriptomic Responses to Oral Cr(VI) Exposure

The toxicity of hexavalent chromium [Cr(VI)] in drinking water has been studied extensively, and available in vivo and in vitro studies provide a robust dataset for application of advanced toxicological tools to inform the mode of action (MOA). This study aimed to contribute to the understanding of Cr(VI) MOA by evaluating high-throughput screening (HTS) data and other in vitro data relevant to Cr(VI), and comparing these findings to robust in vivo data, including transcriptomic profiles in target tissues. Evaluation of Tox21 HTS data for Cr(VI) identified 11 active assay endpoints relevant to the Ten Key Characteristics of Carcinogens (TKCCs) that have been proposed by other investigators. Four of these endpoints were related to TP53 (tumor protein 53) activation mapping to genotoxicity (KCC#2), and four were related to cell death/proliferation (KCC#10). HTS results were consistent with other in vitro data from the Comparative Toxicogenomics Database. In vitro responses were compared to in vivo transcriptomic responses in the most sensitive target tissue, the duodenum, of mice exposed to ≤ 180 ppm Cr(VI) for 7 and 90 days. Pathways that were altered both in vitro and in vivo included those relevant to cell death/proliferation. In contrast, pathways relevant to p53/DNA damage were identified in vitro but not in vivo. Benchmark dose modeling and phenotypic anchoring of in vivo transcriptomic responses strengthened the finding that Cr(VI) causes cell stress/injury followed by proliferation in the mouse duodenum at high doses. These findings contribute to the body of evidence supporting a non-mutagenic MOA for Cr(VI)-induced intestinal cancer.