Concentration-dependent transcriptome of zebrafish embryo for environmental chemical assessment

Mechanistic information is essential to screen and predict the adverse effects of a large number of chemicals during early-life exposure. Concentration-dependent omics can capture the extent of perturbations of biological pathways or processes and provide information on the mechanism of toxicity. However, the application of concentration-dependent transcriptome to assess the developmental toxicity of environmental chemicals is still limited. Here, twelve chemicals representing five different modes of action (MOAs) were tested by the concentration-dependent reduced zebrafish transcriptome approach (CRZT) in combination with a phenotype-based high content screen (PHCS). The responsiveness, sensitivity and mechanistic differentiation of CRZT were validated in comparison with PHCS. First, PHCS identified 10 chemicals with obvious embryotoxicity (LD₅₀ range: 2.11-70.68 μM), while the potencies of the biological pathways perturbed by 12 chemicals (POD_path20 range: 0.002-2.1 μM) were demonstrated by CRZT. Second, although the potency of the transcriptome perturbations was positively correlated with lethality (LD₅₀) (R² = 0.64, P-value < 0.05) for most tested chemicals, BbF was non-embryotoxic but was the most potent on the perturbance of biological pathways. Finally, the profiles of the perturbed biological processes and the transcriptome potency (POD_path20) captured by CRZT could effectively classify most chemicals corresponding to their known MOAs. In summary, CRZT could significantly improve testing the developmental toxicity of environmental chemicals.

A Review of Recent Advances in Benchmark Dose Methodology

In this review, recent methodological developments for the benchmark dose (BMD) methodology are summarized. Specifically, we introduce the advances for the main steps in BMD derivation: selecting the procedure for defining a BMD from a predefined benchmark response (BMR), setting a BMR, selecting a dose-response model, and estimating the corresponding BMD lower limit (BMDL). Although the last decade has shown major progress in the development of BMD methodology, there is still room for improvement. Remaining challenges are the implementation of new statistical methods in user-friendly software and the lack of consensus about how to derive the BMDL.

Use cases, best practice and reporting standards for metabolomics in regulatory toxicology

Metabolomics is a widely used technology in academic research, yet its application to regulatory science has been limited. The most commonly cited barrier to its translation is lack of performance and reporting standards. The MEtabolomics standaRds Initiative in Toxicology (MERIT) project brings together international experts from multiple sectors to address this need. Here, we identify the most relevant applications for metabolomics in regulatory toxicology and develop best practice guidelines, performance and reporting standards for acquiring and analysing untargeted metabolomics and targeted metabolite data. We recommend that these guidelines are evaluated and implemented for several regulatory use cases.

DRomics: A Turnkey Tool to Support the Use of the Dose-Response Framework for Omics Data in Ecological Risk Assessment

Omics approaches (e.g., transcriptomics, metabolomics) are promising for ecological risk assessment (ERA) since they provide mechanistic information and early warning signals. A crucial step in the analysis of omics data is the modeling of concentration-dependency which may have different trends including monotonic (e.g., linear, exponential) or biphasic (e.g., U shape, bell shape) forms. The diversity of responses raises challenges concerning detection and modeling of significant responses and effect concentration (EC) derivation. Furthermore, handling high-throughput data sets is time-consuming and requires effective and automated processing routines. Thus, we developed an open source tool (DRomics, available as an R-package and as a web-based service) which, after elimination of molecular responses (e.g., gene expressions from microarrays) with no concentration-dependency and/or high variability, identifies the best model for concentration-response curve description. Subsequently, an EC (e.g., a benchmark dose) is estimated from each curve, and curves are classified based on their model parameters. This tool is especially dedicated to manage data obtained from an experimental design favoring a great number of tested doses rather than a great number of replicates and also to handle properly monotonic and biphasic trends. The tool finally provides restitution for a table of results that can be directly used to perform ERA approaches.

Using Various Nonlinear Response Surfaces for Mathematical Description of the Type of Combined Toxicity

The article considers the problem of characterizing the type of combined action produced by a mixture of toxic substances with the help of nonlinear response functions. Most attention is given to second-order models: the linear model with a cross-term and the quadratic model. General propositions are formulated based on the data on combined toxicity patterns previously obtained by the Ekaterinburg nanotoxicology team in animal experiments and analyzed with the help of the linear model with a cross-term. It is shown now that the quadratic model features these general characteristics in full measure, but interpretation of combined toxicity types based on isobolograms obtained by the quadratic model is more difficult. This suggests that where both models ensure a comparable quality of combined toxicity type identification, it would be enough to use the linear model with a cross-term.

Benchmark Dose Modeling of In Vitro Genotoxicity Data: a Reanalysis

The methods of applied genetic toxicology are changing from qualitative hazard identification to quantitative risk assessment. Recently, quantitative analysis with point of departure (PoD) metrics and benchmark dose (BMD) modeling have been applied to in vitro genotoxicity data. Two software packages are commonly used for BMD analysis. In previous studies, we performed quantitative dose-response analysis by using the PROAST software to quantitatively evaluate the mutagenicity of four piperidine nitroxides with various substituent groups on the 4-position of the piperidine ring and six cigarette whole smoke solutions (WSSs) prepared by bubbling machine-generated whole smoke. In the present study, we reanalyzed the obtained genotoxicity data by using the EPA's BMD software (BMDS) to evaluate the inter-platform quantitative agreement of the estimates of genotoxic potency. We calculated the BMDs for 10%, 50%, and 100% (i.e., a two-fold increase), and 200% increases over the concurrent vehicle controls to achieve better discrimination of the dose-responses, along with their BMDLs (the lower 95% confidence interval of the BMD) and BMDUs (the upper 95% confidence interval of the BMD). The BMD values and rankings estimated in this study by using the EPA's BMDS were reasonably similar to those calculated in our previous studies by using PROAST. These results indicated that both software packages were suitable for dose-response analysis using the mouse lymphoma assay and that the BMD modeling results from these software packages produced comparable rank orders of the mutagenic potency.

Statistical relationship between metabolic decomposition and chemical uptake predicts bioconcentration factor data for diverse chemical exposures

BACKGROUND

A challenge of in vitro to in vivo extrapolation (IVIVE) is to predict the physical state of organisms exposed to chemicals in the environment from in vitro exposure assay data. Although toxicokinetic modeling approaches promise to bridge in vitro screening data with in vivo effects, they are often encumbered by a need for redesign or re-parameterization when applied to different tissues or chemicals.

RESULTS

We demonstrate a parameterization of reverse toxicokinetic (rTK) models developed for the adult zebrafish (Danio rerio) based upon particle swarm optimizations (PSO) of the chemical uptake and degradation rates that predict bioconcentration factors (BCF) for a broad range of chemicals. PSO reveals a relationship between chemical uptake and decomposition parameter values that predicts chemical-specific BCF values with moderate statistical agreement to a limited yet diverse chemical dataset, and all without a need to retrain the model to new data.

CONCLUSIONS

The presented model requires only the octanol-water partitioning ratio to predict BCFs to a fidelity consistent with existing QSAR models. This success begs re-evaluation of the modeling assumptions; specifically, it suggests that chemical uptake into arterial blood may be limited by transport across gill membranes (diffusion) rather than by counter-current flow between gill lamellae (convection). Therefore, more detailed molecular modeling of aquatic respiration may further improve predictive accuracy of the rTK approach.

2,3,7,8-Tetrachlorodibenzo-p-dioxin dose-dependently increases bone mass and decreases marrow adiposity in juvenile mice

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) and other aryl hydrocarbon receptor (AhR) agonists have been shown to regulate bone development and remodeling in a species-, ligand-, and age-specific manner, however the underlying mechanisms remain poorly understood. In this study, we characterized the effect of 0.01-30 μg/kg TCDD on the femoral morphology of male and female juvenile mice orally gavaged every 4 days for 28 days and used RNA-Seq to investigate gene expression changes associated with the resultant phenotype. Micro-computed tomography revealed that TCDD dose-dependently increased trabecular bone volume fraction (BVF) 2.9- and 3.3-fold in male and female femurs, respectively. Decreased serum tartrate-resistant acid phosphatase (TRAP) levels, combined with a reduced osteoclast surface to bone surface ratio and repression of femoral proteases (cathepsin K, matrix metallopeptidase 13), suggests that TCDD impaired bone resorption. Increased osteoblast counts at the trabecular bone surface were consistent with a reciprocal reduction in the number of bone marrow adipocytes, suggesting AhR activation may direct mesenchymal stem cell differentiation towards osteoblasts rather than adipocytes. Notably, femoral expression of transmembrane glycoprotein NMB (Gpnmb; osteoactivin), a positive regulator of osteoblast differentiation and mineralization, was dose-dependently induced up to 18.8-fold by TCDD. Moreover, increased serum levels of 1,25-dihydroxyvitamin D3 were in accordance with the renal induction of 1α-hydroxylase Cyp27b1 and may contribute to impaired bone resorption. Collectively, the data suggest AhR activation tipped the bone remodeling balance towards bone formation, resulting in increased bone mass with reduced marrow adiposity.

Omics Advances in Ecotoxicology

Toxic substances in the environment generate adverse effects at all levels of biological organization from the molecular level to community and ecosystem. Given this complexity, it is not surprising that ecotoxicologists have struggled to address the full consequences of toxic substance release at ecosystem level, due to the limits of observational and experimental tools to reveal the changes in deep structure at different levels of organization. -Omics technologies, consisting of genomics and ecogenomics, have the power to reveal, in unprecedented detail, the cellular processes of an individual or biodiversity of a community in response to environmental change with high sample/observation throughput. This represents a historic opportunity to transform the way we study toxic substances in ecosystems, through direct linkage of ecological effects with the systems biology of organisms. Three recent examples of -omics advance in the assessment of toxic substances are explored here: (1) the use of functional genomics in the discovery of novel molecular mechanisms of toxicity of chemicals in the environment; (2) the development of laboratory pipelines of dose-dependent, reduced transcriptomics to support high-throughput chemical testing at the biological pathway level; and (3) the use of eDNA metabarcoding approaches for assessing chemical effects on biological communities in mesocosm experiments and through direct observation in field monitoring. -Omics advances in ecotoxicological studies not only generate new knowledge regarding mechanisms of toxicity and environmental effect, improving the relevance and immediacy of laboratory toxicological assessment, but can provide a wholly new paradigm for ecotoxicology by linking ecological models to mechanism-based, systems biology approaches.

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD)-elicited effects on bile acid homeostasis: Alterations in biosynthesis, enterohepatic circulation, and microbial metabolism

2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is a persistent environmental contaminant which elicits hepatotoxicity through activation of the aryl hydrocarbon receptor (AhR). Male C57BL/6 mice orally gavaged with TCDD (0.01–30 µg/kg) every 4 days for 28 days exhibited bile duct proliferation and pericholangitis. Mass spectrometry analysis detected a 4.6-fold increase in total hepatic bile acid levels, despite the coordinated repression of genes involved in cholesterol and primary bile acid biosynthesis including Cyp7a1. Specifically, TCDD elicited a >200-fold increase in taurolithocholic acid (TLCA), a potent G protein-coupled bile acid receptor 1 (GPBAR1) agonist associated with bile duct proliferation. Increased levels of microbial bile acid metabolism loci (bsh, baiCD) are consistent with accumulation of TLCA and other secondary bile acids. Fecal bile acids decreased 2.8-fold, suggesting enhanced intestinal reabsorption due to induction of ileal transporters (Slc10a2, Slc51a) and increases in whole gut transit time and intestinal permeability. Moreover, serum bile acids were increased 45.4-fold, consistent with blood-to-hepatocyte transporter repression (Slco1a1, Slc10a1, Slco2b1, Slco1b2, Slco1a4) and hepatocyte-to-blood transporter induction (Abcc4, Abcc3). These results suggest that systemic alterations in enterohepatic circulation, as well as host and microbiota bile acid metabolism, favor bile acid accumulation that contributes to AhR-mediated hepatotoxicity.

Comparison of Points of Departure for Health Risk Assessment Based on High-Throughput Screening Data

BACKGROUND

The National Research Council's vision for toxicity testing in the 21st century anticipates that points of departure (PODs) for establishing human exposure guidelines in future risk assessments will increasingly be based on in vitro high-throughput screening (HTS) data.

OBJECTIVES

The aim of this study was to compare different PODs for HTS data. Specifically, benchmark doses (BMDs) were compared to the signal-to-noise crossover dose (SNCD), which has been suggested as the lowest dose applicable as a POD.

METHODS

Hill models were fit to > 10,000 in vitro concentration-response curves, obtained for > 1,400 chemicals tested as part of the U.S. Tox21 Phase I effort. BMDs and lower confidence limits on the BMDs (BMDLs) corresponding to extra effects (i.e., changes in response relative to the maximum response) of 5%, 10%, 20%, 30%, and 40% were estimated for > 8,000 curves, along with BMDs and BMDLs corresponding to additional effects (i.e., absolute changes in response) of 5%, 10%, 15%, 20%, and 25%. The SNCD, defined as the dose where the ratio between the additional effect and the difference between the upper and lower bounds of the two-sided 90% confidence interval on absolute effect was 1, 0.67, and 0.5, respectively, was also calculated and compared with the BMDLs.

RESULTS

The BMDL₄₀, BMDL₂₅, and BMDL₁₈, defined in terms of extra effect, corresponded to the SNCD_1.0, SNCD_0.67, and SNCD_0.5, respectively, at the median. Similarly, the BMDL₂₅, BMDL₁₇, and BMDL₁₃, defined in terms of additional effect, corresponded to the SNCD_1.0, SNCD_0.67, and SNCD_0.5, respectively, at the median.

CONCLUSIONS

The SNCD may serve as a reference level that guides the determination of standardized BMDs for risk assessment based on HTS concentration-response data. The SNCD may also have application as a POD for low-dose extrapolation.

A framework for the use of single-chemical transcriptomics data in predicting the hazards associated with complex mixtures of polycyclic aromatic hydrocarbons

The assumption of additivity applied in the risk assessment of environmental mixtures containing carcinogenic polycyclic aromatic hydrocarbons (PAHs) was investigated using transcriptomics. MutaTMMouse were gavaged for 28 days with three doses of eight individual PAHs, two defined mixtures of PAHs, or coal tar, an environmentally ubiquitous complex mixture of PAHs. Microarrays were used to identify differentially expressed genes (DEGs) in lung tissue collected 3 days post-exposure. Cancer-related pathways perturbed by the individual or mixtures of PAHs were identified, and dose–response modeling of the DEGs was conducted to calculate gene/pathway benchmark doses (BMDs). Individual PAH-induced pathway perturbations (the median gene expression changes for all genes in a pathway relative to controls) and pathway BMDs were applied to models of additivity [i.e., concentration addition (CA), generalized concentration addition (GCA), and independent action (IA)] to generate predicted pathway-specific dose–response curves for each PAH mixture. The predicted and observed pathway dose–response curves were compared to assess the sensitivity of different additivity models. Transcriptomics-based additivity calculation showed that IA accurately predicted the pathway perturbations induced by all mixtures of PAHs. CA did not support the additivity assumption for the defined mixtures; however, GCA improved the CA predictions. Moreover, pathway BMDs derived for coal tar were comparable to BMDs derived from previously published coal tar-induced mouse lung tumor incidence data. These results suggest that in the absence of tumor incidence data, individual chemical-induced transcriptomics changes associated with cancer can be used to investigate the assumption of additivity and to predict the carcinogenic potential of a mixture.

Animal-Free Chemical Safety Assessment

The exponential growth of the Internet of Things and the global popularity and remarkable decline in cost of the mobile phone is driving the digital transformation of medical practice. The rapidly maturing digital, non-medical world of mobile (wireless) devices, cloud computing and social networking is coalescing with the emerging digital medical world of omics data, biosensors and advanced imaging which offers the increasingly realistic prospect of personalized medicine. Described as a potential “seismic” shift from the current “healthcare” model to a “wellness” paradigm that is predictive, preventative, personalized and participatory, this change is based on the development of increasingly sophisticated biosensors which can track and measure key biochemical variables in people. Additional key drivers in this shift are metabolomic and proteomic signatures, which are increasingly being reported as pre-symptomatic, diagnostic and prognostic of toxicity and disease. These advancements also have profound implications for toxicological evaluation and safety assessment of pharmaceuticals and environmental chemicals. An approach based primarily on human in vivo and high-throughput in vitro human cell-line data is a distinct possibility. This would transform current chemical safety assessment practice which operates in a human “data poor” to a human “data rich” environment. This could also lead to a seismic shift from the current animal-based to an animal-free chemical safety assessment paradigm.

Quantitative analysis of the relative mutagenicity of five chemical constituents of tobacco smoke in the mouse lymphoma assay

Quantifying health-related biological effects, like genotoxicity, could provide a way of distinguishing between tobacco products. In order to develop tools for using genotoxicty data to quantitatively evaluate the risk of tobacco products, we tested five carcinogens found in cigarette smoke, 4-aminobiphenyl (4-ABP), benzo[a]pyrene (BaP), cadmium (in the form of CdCl2), 2-amino-3,4-dimethyl-3H-imidazo[4,5-f]quinoline (MeIQ) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), in the mouse lymphoma assay (MLA). The resulting mutagenicity dose responses were analyzed by various quantitative approaches and their strengths and weaknesses for distinguishing responses in the MLA were evaluated. L5178Y/Tk (+/-) 3.7.2C mouse lymphoma cells were treated with four to seven concentrations of each chemical for 4h. Only CdCl2 produced a positive response without metabolic activation (S9); all five chemicals produced dose-dependent increases in cytotoxicity and mutagenicity with S9. The lowest dose exceeding the global evaluation factor, the benchmark dose producing a 10%, 50%, 100% or 200% increase in the background frequency (BMD10, BMD50, BMD100 and BMD200), the no observed genotoxic effect level (NOGEL), the lowest observed genotoxic effect level (LOGEL) and the mutagenic potency expressed as a mutant frequency per micromole of chemical, were calculated for all the positive responses. All the quantitative metrics had similar rank orders for the agents' ability to induce mutation, from the most to least potent as CdCl2(-S9) > BaP(+S9) > CdCl2(+S9) > MeIQ(+S9) > 4-ABP(+S9) > NNK(+S9). However, the metric values for the different chemical responses (i.e. the ratio of the greatest value to the least value) for the different chemicals ranged from 16-fold (BMD10) to 572-fold (mutagenic potency). These results suggest that data from the MLA are capable of discriminating the mutagenicity of various constituents of cigarette smoke, and that quantitative analyses are available that can be useful in distinguishing between the exposure responses.

2,3,7,8-Tetrachlorodibenzo-p-Dioxin Alters Lipid Metabolism and Depletes Immune Cell Populations in the Jejunum of C57BL/6 Mice

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a potent aryl hydrocarbon receptor agonist that elicits dose-dependent hepatic fat accumulation and inflammation that can progress to steatohepatitis. To investigate intestine-liver interactions that contribute to TCDD-elicited steatohepatitis, we examined the dose-dependent effects of TCDD (0.01, 0.03, 0.1, 0.3, 1, 3, 10, or 30 µg/kg) on jejunal epithelial gene expression in C57BL/6 mice orally gavaged every 4 days for 28 days. Agilent 4x44K whole-genome microarray analysis of the jejunal epithelium identified 439 differentially expressed genes (|fold change| ≥ 1.5, P1(t) ≥ 0.999) across 1 or more doses, many related to lipid metabolism and immune system processes. TCDD-elicited differentially expressed genes were associated with lipolysis, fatty acid/cholesterol absorption and transport, the Kennedy pathway, and retinol metabolism, consistent with increased hepatic fat accumulation. Moreover, several major histocompatibility complex (MHC) class II genes (H2-Aa, H2-Ab1, H2-DMb1, Cd74) were repressed, coincident with decreased macrophage and dendritic cell levels in the lamina propria, suggesting migration of antigen-presenting cells out of the intestine. In contrast, hepatic RNA-Seq analysis identified increased expression of MHC class II genes, as well as chemokines and chemokine receptors involved in macrophage recruitment (Ccr1, Ccr5, Ccl5, Cx3cr1), consistent with hepatic F4/80 labeling and macrophage infiltration into the liver. Collectively, these results suggest TCDD elicits changes that support hepatic lipid accumulation, macrophage migration, and the progression of hepatic steatosis to steatohepatitis.

Atrazine-Mediated Disruption of Steroidogenesis in BLTK1 Murine Leydig Cells

Atrazine (ATR) is a broad-spectrum triazine herbicide that disrupts steroidogenesis resulting in reproductive and developmental toxicity at high doses. Mouse BLTK1 Leydig cells were used as a steroidogenic model to investigate the effects of ATR on testosterone (T) biosynthesis. Induction of steroidogenesis by 3 ng/ml recombinant human chorionic gonadotropin (rhCG) induced intracellular 3',5' cyclic adenosine monophosphate (cAMP) approximately 20-fold and T approximately 3-fold at 4 h. Co-treatment with 300 μM ATR super-induced cAMP levels 100-fold yet antagonized rhCG-mediated induction of T approximately 20% at 4 h. ATR inhibited cAMP-specific phosphodiesterase (cPDE) with an IC50 of ≥98 μM, suggesting cPDE inhibition contributes to the super-induction of cAMP. However, concentrations of up to 3 mM db-cAMP did not antagonize rhCG induction of T levels, suggesting cAMP super-induction alone does not decrease T biosynthesis. Western analysis of cAMP-activated protein kinase A (PKA) target proteins identified ATR-mediated concentration-dependent alterations in phosphorylation including phospho-CREB. These results suggest the cPDE inhibition by ATR and super-induction of cAMP are independent of effects on T levels, and that altered phosphorylation of key steroidogenic regulatory proteins may underlie ATR-mediated disruption of steroidogenesis.

High-throughput concentration-response analysis for omics datasets

Omics-based methods are increasingly used in current ecotoxicology. Therefore, a large number of observations for various toxic substances and organisms are available and may be used for identifying modes of action, adverse outcome pathways, or novel biomarkers. For these purposes, good statistical analysis of toxicogenomic data is vital. In contrast to established ecotoxicological techniques, concentration-response modeling is rarely used for large datasets. Instead, statistical hypothesis testing is prevalent, which provides only a limited scope for inference. The present study therefore applied automated concentration-response modeling for 3 different ecotoxicotranscriptomic and ecotoxicometabolomic datasets. The modeling process was performed by simultaneously applying 9 different regression models, representing distinct mechanistic, toxicological, and statistical ideas that result in different curve shapes. The best-fitting models were selected by using Akaike's information criterion. The linear and exponential models represented the best data description for more than 50% of responses. Models generating U-shaped curves were frequently selected for transcriptomic signals (30%), and sigmoid models were identified as best fit for many metabolomic signals (21%). Thus, selecting the models from an array of different types seems appropriate, because concentration-response functions may vary because of the observed response type, and they also depend on the compound, the organism, and the investigated concentration and exposure duration range. The application of concentration-response models can help to further tap the potential of omics data and is a necessary step for quantitative mixture effect assessment at the molecular response level.

Metabolic Effect Level Index Links Multivariate Metabolic Fingerprints to Ecotoxicological Effect Assessment

A major goal of ecotoxicology is the prediction of adverse outcomes for populations from sensitive and early physiological responses. A snapshot of the physiological state of an organism can be provided by metabolic fingerprints. However, to inform chemical risk assessment, multivariate metabolic fingerprints need to be converted to readable end points suitable for effect estimation and comparison. The concentration- and time-dependent responsiveness of metabolic fingerprints to the PS-II inhibitor isoproturon was investigated by use of a Myriophyllum spicatum bioassay. Hydrophilic and lipophilic leaf extracts were analyzed with gas chromatography-mass spectrometry (GC-MS) and preprocessed with XCMS. Metabolic changes were aggregated in the quantitative metabolic effect level index (MELI), allowing effect estimation from Hill-based concentration-response models. Hereby, the most sensitive response on the concentration scale was revealed by the hydrophilic MELI, followed by photosynthetic efficiency and, 1 order of magnitude higher, by the lipophilic MELI and shoot length change. In the hydrophilic MELI, 50% change compares to 30% inhibition of photosynthetic efficiency and 10% inhibition of dry weight change, indicating effect development on different response levels. In conclusion, aggregated metabolic fingerprints provide quantitative estimates and span a broad response spectrum, potentially valuable for establishing adverse outcome pathways of chemicals in environmental risk assessment.

RNA-Seq versus oligonucleotide array assessment of dose-dependent TCDD-elicited hepatic gene expression in mice

BACKGROUND

Dose-dependent differential gene expression provides critical information required for regulatory decision-making. The lower costs associated with RNA-Seq have made it the preferred technology for transcriptomic analysis. However, concordance between RNA-Seq and microarray analyses in dose response studies has not been adequately vetted.

RESULTS

We compared the hepatic transcriptome of C57BL/6 mice following gavage with sesame oil vehicle, 0.01, 0.03, 0.1, 0.3, 1, 3, 10, or 30 μg/kg TCDD every 4 days for 28 days using Illumina HiSeq RNA-Sequencing (RNA-Seq) and Agilent 4 × 44 K microarrays using the same normalization and analysis approach. RNA-Seq and microarray analysis identified a total of 18,063 and 16,403 genes, respectively, that were expressed in the liver. RNA-Seq analysis for differentially expressed genes (DEGs) varied dramatically depending on the P1(t) cut-off while microarray results varied more based on the fold change criteria, although responses strongly correlated. Verification by WaferGen SmartChip QRTPCR revealed that RNA-Seq had a false discovery rate of 24% compared to 54% for microarray analysis. Dose-response modeling of RNA-Seq and microarray data demonstrated similar point of departure (POD) and ED50 estimates for common DEGs.

CONCLUSIONS

There was a strong correspondence between RNA-Seq and Agilent array transcriptome profiling when using the same samples and analysis strategy. However, RNA-Seq provided superior quantitative data, identifying more genes and DEGs, as well as qualitative information regarding identity and annotation for dose response modeling in support of regulatory decision-making.

Toxicity mechanisms identification via gene set enrichment analysis of time-series toxicogenomics data: impact of time and concentration

The advance in high-throughput "toxicogenomics" technologies, which allows for concurrent monitoring of cellular responses globally upon exposure to chemical toxicants, presents promises for next-generation toxicity assessment. It is recognized that cellular responses to toxicants have a highly dynamic nature, and exhibit both temporal complexity and dose-response shifts. Most current gene enrichment or pathway analysis lack the recognition of the inherent correlation within time series data, and may potentially miss important pathways or yield biased and inconsistent results that ignore dynamic patterns and time-sensitivity. In this study, we investigated the application of two score metrics for GSEA (gene set enrichment analysis) to rank the genes that consider the temporal gene expression profile. One applies a novel time series CPCA (common principal components analysis) to generate scores for genes based on their contributions to the common temporal variation among treatments for a given chemical at different concentrations. Another one employs an integrated altered gene expression quantifier-TELI (transcriptional effect level index) that integrates altered gene expression magnitude over the exposure time. By comparing the GSEA results using two different ranking metrics for examining the dynamic responses of reporter cells treated with various dose levels of three model toxicants, mitomycin C, hydrogen peroxide, and lead nitrate, the analysis identified and revealed different toxicity mechanisms of these chemicals that exhibit chemical-specific, as well as time-aware and dose-sensitive nature. The ability, advantages, and disadvantages of varying ranking metrics were discussed. These findings support the notion that toxicity bioassays should account for the cells' complex dynamic responses, thereby implying that both data acquisition and data analysis should look beyond simple traditional end point responses.

A framework for the next generation of risk science

OBJECTIVES

In 2011, the U.S. Environmental Protection Agency initiated the NexGen project to develop a new paradigm for the next generation of risk science.

METHODS

The NexGen framework was built on three cornerstones: the availability of new data on toxicity pathways made possible by fundamental advances in basic biology and toxicological science, the incorporation of a population health perspective that recognizes that most adverse health outcomes involve multiple determinants, and a renewed focus on new risk assessment methodologies designed to better inform risk management decision making.

RESULTS

The NexGen framework has three phases. Phase I (objectives) focuses on problem formulation and scoping, taking into account the risk context and the range of available risk management decision-making options. Phase II (risk assessment) seeks to identify critical toxicity pathway perturbations using new toxicity testing tools and technologies, and to better characterize risks and uncertainties using advanced risk assessment methodologies. Phase III (risk management) involves the development of evidence-based population health risk management strategies of a regulatory, economic, advisory, community-based, or technological nature, using sound principles of risk management decision making.

CONCLUSIONS

Analysis of a series of case study prototypes indicated that many aspects of the NexGen framework are already beginning to be adopted in practice.

Current perspectives on the use of alternative species in human health and ecological hazard assessments

BACKGROUND

Traditional animal toxicity tests can be time and resource intensive, thereby limiting the number of chemicals that can be comprehensively tested for potential hazards to humans and/or to the environment.

OBJECTIVE

We compared several types of data to demonstrate how alternative models can be used to inform both human and ecological risk assessment.

METHODS

We reviewed and compared data derived from high throughput in vitro assays to fish reproductive tests for seven chemicals. We investigated whether human-focused assays can be predictive of chemical hazards in the environment. We examined how conserved pathways enable the use of nonmammalian models, such as fathead minnow, zebrafish, and Xenopus laevis, to understand modes of action and to screen for chemical risks to humans.

RESULTS

We examined how dose-dependent responses of zebrafish embryos exposed to flusilazole can be extrapolated, using pathway point of departure data and reverse toxicokinetics, to obtain human oral dose hazard values that are similar to published mammalian chronic toxicity values for the chemical. We also examined how development/safety data for human health can be used to help assess potential risks of pharmaceuticals to nontarget species in the environment.

DISCUSSION

Using several examples, we demonstrate that pathway-based analysis of chemical effects provides new opportunities to use alternative models (nonmammalian species, in vitro tests) to support decision making while reducing animal use and associated costs.

CONCLUSIONS

These analyses and examples demonstrate how alternative models can be used to reduce cost and animal use while being protective of both human and ecological health.

System-based identification of toxicity pathways associated with multi-walled carbon nanotube-induced pathological responses

The fibrous shape and biopersistence of multi-walled carbon nanotubes (MWCNT) have raised concern over their potential toxicity after pulmonary exposure. As in vivo exposure to MWCNT produced a transient inflammatory and progressive fibrotic response, this study sought to identify significant biological processes associated with lung inflammation and fibrosis pathology data, based upon whole genome mRNA expression, bronchoaveolar lavage scores, and morphometric analysis from C57BL/6J mice exposed by pharyngeal aspiration to 0, 10, 20, 40, or 80 μg MWCNT at 1, 7, 28, or 56 days post-exposure. Using a novel computational model employing non-negative matrix factorization and Monte Carlo Markov Chain simulation, significant biological processes with expression similar to MWCNT-induced lung inflammation and fibrosis pathology data in mice were identified. A subset of genes in these processes was determined to be functionally related to either fibrosis or inflammation by Ingenuity Pathway Analysis and was used to determine potential significant signaling cascades. Two genes determined to be functionally related to inflammation and fibrosis, vascular endothelial growth factor A (vegfa) and C-C motif chemokine 2 (ccl2), were confirmed by in vitro studies of mRNA and protein expression in small airway epithelial cells exposed to MWCNT as concordant with in vivo expression. This study identified that the novel computational model was sufficient to determine biological processes strongly associated with the pathology of lung inflammation and fibrosis and could identify potential toxicity signaling pathways and mechanisms of MWCNT exposure which could be used for future animal studies to support human risk assessment and intervention efforts.

Comparative analysis of temporal and dose-dependent TCDD-elicited gene expression in human, mouse, and rat primary hepatocytes

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD)-elicited time- and dose-dependent differential gene expression was compared in human, mouse, and rat primary hepatocytes. Comprehensive time course (10 nM TCDD or dimethyl sulfoxide vehicle control for 1, 2, 4, 8, 12, 24, and 48h) studies identified 495, 2305, and 711 differentially expressed orthologous genes in human, mouse, and rat hepatocytes, respectively. However, only 16 orthologs were differentially expressed across all three species, with the majority of orthologs exhibiting species-specific expression (399 human, 2097 mouse, and 533 rat), consistent with species-specific expression reported in other in vitro and in vivo comparative studies. TCDD also elicited the dose-dependent induction of 397 human, 100 mouse, and 443 rat genes at 12h and 615 human, 426 mouse, and 314 rat genes at 24h. Comparable EC50 values were obtained for AhR battery genes including Cyp1a1 (0.1 nM human, 0.05 nM mouse, 0.08 nM rat at 24h) and Tiparp (0.97 nM human, 0.63 nM mouse, 0.14 nM rat at 12h). Overrepresented functions and pathways included amino acid metabolism in humans, immune response in mice, and energy homeostasis in rats. Differentially expressed genes functionally associated with lipid transport, processing, and metabolism were overrepresented in all three species but exhibited species-specific expression consistent with the induction of hepatic steatosis in mice but not in rats following a single oral gavage of TCDD. Furthermore, human primary hepatocytes showed lipid accumulation following 48h of treatment with TCDD, suggesting that AhR-mediated steatosis in mice more closely resembles human hepatic fat accumulation compared with that in rats. Collectively, these results suggest that species-specific gene expression profiles mediate the species-specific effects of TCDD despite the conservation of the AhR and its signaling mechanism.

Toxicogenomic approaches in developmental toxicology testing

The emergence of toxicogenomic applications provides new tools to characterize, classify, and potentially predict teratogens. However, due to the vast number of experimental and statistical procedural steps, toxicogenomic studies are challenging. Here, we guide researchers through the basic framework of conducting toxicogenomic investigations in the field of developmental toxicology, providing examples of biological and technical factors that may influence response and interpretation. Furthermore, we review current, diverse applications of toxicogenomic-based approaches in teratology testing, including exposure-response characterization (dose and duration), chemical classification studies, and cross-model comparisons study designs. This review is intended to guide scientists through the challenging and complex structure of conducting toxicogenomic analyses, while considering the many applications of using toxicogenomics in study designs and the future of these types of "omics" approaches in developmental toxicology.

Comparative toxicogenomic analysis of oral Cr(VI) exposure effects in rat and mouse small intestinal epithelia

Continuous exposure to high concentrations of hexavalent chromium [Cr(VI)] in drinking water results in intestinal tumors in mice but not rats. Concentration-dependent gene expression effects were evaluated in female F344 rat duodenal and jejunal epithelia following 7 and 90 days of exposure to 0.3-520 mg/L (as sodium dichromate dihydrate, SDD) in drinking water. Whole-genome microarrays identified 3269 and 1815 duodenal, and 4557 and 1534 jejunal differentially expressed genes at 8 and 91 days, respectively, with significant overlaps between the intestinal segments. Functional annotation identified gene expression changes associated with oxidative stress, cell cycle, cell death, and immune response that were consistent with reported changes in redox status and histopathology. Comparative analysis with B6C3F1 mouse data from a similarly designed study identified 2790 differentially expressed rat orthologs in the duodenum compared to 5013 mouse orthologs at day 8, and only 1504 rat and 3484 mouse orthologs at day 91. Automated dose-response modeling resulted in similar median EC₅₀s in the rodent duodenal and jejunal mucosae. Comparative examination of differentially expressed genes also identified divergently regulated orthologs. Comparable numbers of differentially expressed genes were observed at equivalent Cr concentrations (μg Cr/g duodenum). However, mice accumulated higher Cr levels than rats at ≥ 170 mg/L SDD, resulting in a ~2-fold increase in the number of differentially expressed genes. These qualitative and quantitative differences in differential gene expression, which correlate with differences in tissue dose, likely contribute to the disparate intestinal tumor outcomes.

BLTK1 murine Leydig cells: a novel steroidogenic model for evaluating the effects of reproductive and developmental toxicants

Leydig cells are the primary site of androgen biosynthesis in males. Several environmental toxicants target steroidogenesis resulting in both developmental and reproductive effects including testicular dysgenesis syndrome. The aim of this study was to evaluate the effect of several structurally diverse endocrine disrupting compounds (EDCs) on steroidogenesis in a novel BLTK1 murine Leydig cell model. We demonstrate that BLTK1 cells possess a fully functional steroidogenic pathway that produces low basal levels of testosterone (T) and express all the necessary steroidogenic enzymes including Star, Cyp11a1, Cyp17a1, Hsd3b1, Hsd17b3, and Srd5a1. Recombinant human chorionic gonadotropin (rhCG) and forskolin (FSK) elicited concentration- and time-dependent induction of 3',5'-cyclic adenosine monophosphate, progesterone (P), and T, as well as the differential expression of Star, Hsd3b6, Hsd17b3, and Srd5a1 messenger RNA levels. The evaluation of several structurally diverse male reproductive toxicants including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), atrazine, prochloraz, triclosan, monoethylhexyl phthalate (MEHP), glyphosate, and RDX in BLTK1 cells suggests different modes of action perturb steroidogenesis. For example, prochloraz and triclosan antifungals reduced rhCG induction of T, consistent with published in vivo data but did not alter basal T levels. In contrast, atrazine and MEHP elicited modest induction of basal T but antagonized rhCG-mediated induction of T levels, whereas TCDD, glyphosate, and RDX had no effect on basal or rhCG induction of T in BLTK1 cells. These results suggest that BLTK1 cells maintain rhCG-inducible steroidogenesis and are a viable in vitro Leydig cell model to evaluate the effects of EDCs on steroidogenesis. This model can also be used to elucidate the different mechanisms underlying toxicant-mediated disruption of steroidogenesis.

Concentration-response concept in ecotoxicoproteomics: effects of different phenanthrene concentrations to the zebrafish (Danio rerio) embryo proteome

Concentration-response experiments, based on the testing of less replicates in favour of more exposure concentrations, represent the typical design of choice applied in toxicological and ecotoxicological effect assessment studies using traditional endpoints such as lethality. However, to our knowledge this concept has not found implementation in the increasingly applied OMICS techniques studying thousands of molecular endpoints at the same time. The present study is among the first applying the concentration-response concept for an ecotoxicoproteomics study. The effects of six different concentrations in the low effect range (<LC₂₀) of the PAH phenanthrene to the proteome of the ecotoxicological vertebrate model zebrafish (Danio rerio) embryo were investigated (two replicates per concentration) after 5 days exposure. Proteomics analyses were performed on organism extracts using 2-DE DIGE. Protein abundance profiles of around 713 protein spots were studied. About one-third of the protein signals could be detected to show robust reactions correlating with stressor concentration. Within this group, 65 protein signals showed significant changes compared to controls already at 1% lethal concentration (LC₀₁). Interestingly, 28 proteins significantly reacted at very low concentrations (<LC₀₁) and showed an exposure concentration dependent regulation status. Characteristic protein spots were identified by mass spectrometry. With the results of the present study the utility and several benefits using a concentration-response approach in proteomics studies could be shown. These included (i) knowledge about and the ability to model concentration dependent dynamics of molecular endpoints, (ii) to gain information about sensitivity of the molecular response in comparison to traditional endpoints and (iii) to help selecting the most promising protein spots for further investigations such as protein identification and biomarker studies. Using this experimental design based on testing of several exposure concentrations and less replicates might provide a step forward in getting increased output from toxicoproteomics studies.

New perspectives for in vitro risk assessment of multiwalled carbon nanotubes: application of coculture and bioinformatics

Nanotechnology is a rapidly expanding field with wide application for industrial and medical use; therefore, understanding the toxicity of engineered nanomaterials is critical for their commercialization. While short-term in vivo studies have been performed to understand the toxicity profile of various nanomaterials, there is a current effort to shift toxicological testing from in vivo observational models to predictive and high-throughput in vitro models. However, conventional monoculture results of nanoparticle exposure are often disparate and not predictive of in vivo toxic effects. A coculture system of multiple cell types allows for cross-talk between cells and better mimics the in vivo environment. This review proposes that advanced coculture models, combined with integrated analysis of genome-wide in vivo and in vitro toxicogenomic data, may lead to development of predictive multigene expression-based models to better determine toxicity profiles of nanomaterials and consequent potential human health risk due to exposure to these compounds.

A review of toxicogenomic approaches in developmental toxicology

Over the past decade, the use of gene expression profiling (i.e., toxicogenomics or transcriptomics) has been established as the vanguard "omics" technology to investigate exposure-induced molecular changes that underlie the development of disease. As this technology quickly advances, researchers are striving to keep pace in grasping the complexity of toxicogenomic response while at the same time determine its applicability for the field of developmental toxicology. Initial studies suggest toxicogenomics to be a promising tool for multiple types of study designs, including exposure-response investigations (dose and duration), chemical classification, and model comparisons. In this review, we examine the use of toxicogenomics in developmental toxicology, discussing biological and technical factors that influence response and interpretation. Additionally, we provide a framework to guide toxicogenomic investigations in the field of developmental toxicology.

Chronic effects induced by ibuprofen on the freshwater bivalve Dreissena polymorpha

The sub-lethal effects induced by the non-steroidal anti-inflammatory drug ((NSAID) ibuprofen (IBU; ((±)-2-(p-isobutylphenyl) propionic acid))) were investigated using a battery of biomarkers on the freshwater bivalve Dreissena polymorpha. According to the results from a semi-static in vivo approach, mussels were exposed for 96 h to increasing levels of environmentally relevant IBU concentrations (0.2, 2 and 8 μg/l, corresponding to 1, 9 and 35 nM, respectively). Cyto-genotoxicity was evaluated via the single cell gel electrophoresis (SCGE) assay, the DNA diffusion assay, the micronucleus test (MN test) and lysosome membrane stability (Neutral Red Retention Assay) in mussel hemocytes. In addition, the activities of catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx) and the phase II detoxifying enzyme glutathione S-transferase (GST) were measured in the cytosolic fraction that was extracted from a pool of entire bivalves to determine whether the oxidative status was imbalanced. The biomarker battery pointed out a slight cyto-genotoxicity on zebra mussel hemocytes at the IBU concentration of 0.2 μg/l, with higher IBU concentrations able to significantly increase both genetic and cellular damage. In addition, IBU seems to have a considerable effect on the activities of antioxidant and detoxifying enzymes as shown in the exposed specimens' notable oxidative status imbalances.

Automated dose-response analysis and comparative toxicogenomic evaluation of the hepatic effects elicited by TCDD, TCDF, and PCB126 in C57BL/6 mice

The toxic equivalency factor (TEF) approach recommended by the World Health Organization is used to quantify dioxin-like exposure concentrations for mixtures of polychlorinated dibenzo-dioxins, -furans, and polychlorinated biphenyls (PCBs), including 2,3,7,8-tetrachlorodibenzofuran (TCDF) and 3,3',4,4',5-pentachlorobiphenyl (PCB126) relative to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Whole-genome microarrays were used to evaluate the hepatic gene expression potency of TCDF and PCB126 relative to TCDD with complementary histopathology, tissue level analysis, and ethoxyresorufin-O-deethylase (EROD) assay results. Immature ovariectomized C57BL/6 mice were gavaged with 0.001, 0.01, 0.03, 0.1, 0.3, 1, 3, 10, 30, 100, and 300 μg/kg TCDD and TEF-adjusted doses (TEF for TCDF and PCB126 is 0.1) of TCDF or PCB126 (1, 3, 10, 30, 100, 300, 1000, and 3000 μg/kg of TCDF or PCB126) or sesame oil vehicle and sacrificed 24 h post dose. In general, TCDD, TCDF, and PCB126 tissue levels, as well as histopathological effects, were comparable when comparing TEF-adjusted doses. Automated dose-response modeling (ToxResponse Modeler) of the microarray data identified 210 TCDF and 40 PCB126 genes that exhibited sigmoidal dose-response curves with comparable slopes when compared with TCDD. These similar responses were used to calculate a median TCDF gene expression relative potency (REP) of 0.06 and a median PCB126 gene expression REP of 0.02. REPs of 0.02 were also calculated for EROD induction for both compounds. Collectively, these data suggest that differences in the ability of the liganded aryl hydrocarbon receptor:AhR nuclear translocator complex to elicit differential hepatic gene expression, in addition to pharmacokinetic differences between ligands, influence their potency in immature ovariectomized C57BL/6 mice.

Effects of TCDD on the expression of nuclear encoded mitochondrial genes

Generation of mitochondrial reactive oxygen species (ROS) can be perturbed following exposure to environmental chemicals such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Reports indicate that the aryl hydrocarbon receptor (AhR) mediates TCDD-induced sustained hepatic oxidative stress by decreasing hepatic ATP levels and through hyperpolarization of the inner mitochondrial membrane. To further elucidate the effects of TCDD on the mitochondria, high-throughput quantitative real-time PCR (HTP-QRTPCR) was used to evaluate the expression of 90 nuclear genes encoding mitochondrial proteins involved in electron transport, oxidative phosphorylation, uncoupling, and associated chaperones. HTP-QRTPCR analysis of time course (30 microg/kg TCDD at 2, 4, 8, 12, 18, 24, 72, and 168 h) liver samples obtained from orally gavaged immature, ovariectomized C57BL/6 mice identified 54 differentially expressed genes (/fold change/ > 1.5 and P-value < 0.1). Of these, 8 exhibited a sigmoidal or exponential dose-response profile (0.03 to 300 microg/kg TCDD) at 4, 24 or 72 h. Dose-responsive genes encoded proteins associated with electron transport chain (ETC) complexes I (NADH dehydrogenase), III (cytochrome c reductase), IV (cytochrome c oxidase), and V (ATP synthase) and could be generally categorized as having proton gradient, ATP synthesis, and chaperone activities. In contrast, transcript levels of ETC complex II, succinate dehydrogenase, remained unchanged. Putative dioxin response elements were computationally found in the promoter regions of all 8 dose-responsive genes. This high-throughput approach suggests that TCDD alters the expression of genes associated with mitochondrial function which may contribute to TCDD-elicited mitochondrial toxicity.

Approaches to advancing quantitative human health risk assessment of environmental chemicals in the post-genomic era

The contribution of genomics and associated technologies to human health risk assessment for environmental chemicals has focused largely on elucidating mechanisms of toxicity, as discussed in other articles in this issue. However, there is interest in moving beyond hazard characterization to making more direct impacts on quantitative risk assessment (QRA)--i.e., the determination of toxicity values for setting exposure standards and cleanup values. We propose that the evolution of QRA of environmental chemicals in the post-genomic era will involve three, somewhat overlapping phases in which different types of approaches begin to mature. The initial focus (in Phase I) has been and continues to be on "augmentation" of weight of evidence--using genomic and related technologies qualitatively to increase the confidence in and scientific basis of the results of QRA. Efforts aimed towards "integration" of these data with traditional animal-based approaches, in particular quantitative predictors, or surrogates, for the in vivo toxicity data to which they have been anchored are just beginning to be explored now (in Phase II). In parallel, there is a recognized need for "expansion" of the use of established biomarkers of susceptibility or risk of human diseases and disorders for QRA, particularly for addressing the issues of cumulative assessment and population risk. Ultimately (in Phase III), substantial further advances could be realized by the development of novel molecular and pathway-based biomarkers and statistical and in silico models that build on anticipated progress in understanding the pathways of human diseases and disorders. Such efforts would facilitate a gradual "reorientation" of QRA towards approaches that more directly link environmental exposures to human outcomes.

PCB153-elicited hepatic responses in the immature, ovariectomized C57BL/6 mice: comparative toxicogenomic effects of dioxin and non-dioxin-like ligands

Polychlorinated biphenyls (PCBs) are ubiquitous contaminants found as complex mixtures of coplanar and non-coplanar congeners. The hepatic temporal and dose-dependent effects of the most abundant non-dioxin-like congener, 2,2',4,4',5,5'-hexachlorobiphenyl (PCB153), were examined in immature, ovariectomized C57BL/6 mice, and compared to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), the prototypical aryl hydrocarbon receptor (AhR) ligand. Animals were gavaged once with 300 mg/kg PCB153 or sesame oil vehicle and sacrificed 4, 12, 24, 72 or 168 h post dose. In the dose-response study, mice were gavaged with 1, 3, 10, 30, 100 or 300 mg/kg PCB153 or sesame oil for 24 h. Significant increases in relative liver weights were induced with 300 mg/kg PCB153 between 24 and 168 h, accompanied by slight vacuolization and hepatocellular hypertrophy. The hepatic differential expression of 186 and 177 genes was detected using Agilent 4 x 44 K microarrays in the time course (|fold change|> or =1.5, P1(t)> or =0.999) and dose-response (|fold change|> or =1.5, P1(t)> or =0.985) studies, respectively. Comparative analysis with TCDD suggests that the differential gene expression elicited by PCB153 was not mediated by the AhR. Furthermore, constitutive androstane and pregnane X receptor (CAR/PXR) regulated genes including Cyp2b10, Cyp3a11, Ces2, Insig2 and Abcc3 were dose-dependently induced by PCB153. Collectively, these results suggest that the hepatocellular effects elicited by PCB153 are qualitatively and quantitatively different from TCDD and suggestive of CAR/PXR regulation.

Automated dose-response analysis of the relative hepatic gene expression potency of TCDF in C57BL/6 mice

Toxic equivalency factors (TEFs) are assigned to dioxin-like chemicals based on relative potency (REP) values of individual adaptive and toxic responses compared to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Agilent 4x44K oligonucleotide microarrays were used to examine the hepatic gene expression potency of 2,3,7,8-tetrachlorodibenzofuran (TCDF), relative to TCDD with complementary histopathology, TCDD and TCDF tissue level analysis, and ethoxyresorufin-O-deethylase (EROD) assay data. Immature ovariectomized C57BL/6 mice were gavaged with 0.03, 0.1, 0.3, 1, 3, 10, 30, or 100 microg/kg TCDD, the World Health Organization TEF-adjusted doses (10 x TCDD dose) of TCDF (0.3, 1, 3, 10, 30, 100, or 300 microg/kg), or sesame oil vehicle and killed at 72 h. Two thousand two hundred eighty-eight and 1347 genes were differentially expressed (P1(t) > 0.90) at one or more doses by TCDD and TCDF, respectively. Automated dose-response modeling (ToxResponse Modeler) identified a total of 1027 and 837 genes with either a sigmoidal, exponential, linear, Gaussian, or quadratic dose-response relationship 72 h after treatment in TCDD and TCDF, respectively. Two hundred seventy genes exhibited a sigmoidal TCDD-induced dose-response (ED(50s) from 0.08 to 42.2 microg/kg) compared to only 179 sigmoidal responsive genes (ED(50s) from 0.74 to 299.9 microg/kg) elicited by TCDF. Of the 1027 TCDD dose-responsive genes, 654 were not examined further due to the lack of a dose response elicited by TCDF. Of the 373 genes that exhibited a TCDD and TCDF dose response, REPs were calculated for the 83 genes that exhibited comparable sigmoidal curve shapes and slopes. The median REP for these 83 genes was 0.10, with a maximum REP of 0.56 and a minimum of 0.01. REPs of 0.04 were also calculated for EROD and increase in relative liver weight (RLW) at 72 h. Collectively, the lower number of TCDF-induced genes compared to TCDD and the 0.04 REPs for EROD activity and increased RLW are not consistent with the TEF of 0.10 for the hepatotoxicity of TCDF in C57BL/6 mice at 72 h.