Discriminating classes of developmental toxicants using gene expression profiling in the embryonic stem cell test

Transcriptome-based analysis of the toxic effects of aluminum chloride exposure on spermatocytes

Aluminum chloride (AlCl3) exposure is pervasive in our daily lives. Numerous studies have demonstrated that exposure to AlCl3 can lead to male reproductive toxicity. However, the precise mechanism of action remains unclear. The objective of this study is to investigate the mechanism of aluminum-induced toxicity by analyzing the alterations in the global transcriptome gene profile of mouse spermatocytes (GC-2spd cells) exposed to AlCl3. GC-2spd cells were exposed to concentrations of 0, 1, 2, and 4 mM AlCl3, and high-throughput mRNA-seq was performed to investigate the changes in the transcriptome after exposure to 4 mM AlCl3. Our findings indicate that exposure to AlCl3 led to an increase in oxidative stress, disrupted glutathione metabolism, reduced cell viability, and altered gene expression in mouse spermatocytes. Gene enrichment analysis revealed that the differentially expressed genes (DEGs) were associated with various biological functions such as mitochondrial inner membrane, response to oxidative stress. Furthermore, these DEGs were found to be enriched in pathways including proteasome, glutathione metabolism, oxidative phosphorylation, and Hif-1 signaling pathway. Real-time PCR and western blot were employed to validate the expression alterations of pivotal genes, and the outcomes exhibited concordance with the mRNA-seq findings. This study provides a theoretical basis for revealing the potential mechanism of male reproductive toxicity caused by aluminum exposure.

Molecular neural crest cell markers enable discrimination of organophosphates in the murine cardiac embryonic stem cell test

•

Organophosphates induced distinctive effects on neural crest cells within the ESTc.

•

Neural crest gene transcripts were of added value to the original ESTc read-out.

•

Mechanistic information adds value to the applicability of the ESTc.

The cardiac embryonic stem cell test (ESTc) originally used the differentiation of beating cardiomyocytes for embryotoxicity screenings of compounds. However, the ESTc consists of a heterogeneous cell population, including neural crest (NC) cells, which are important contributors to heart development in vivo. Molecular markers for NC cells were investigated to explore if this approach improved discrimination between structurally related chemicals, using the three organophosphates (OP): chlorpyrifos (CPF), malathion (MLT), and triphenyl phosphate (TPP). To decrease the test duration and to improve the objective quantification of the assay read-out, gene transcript biomarkers were measured on study day 4 instead of the traditional cardiomyocyte beating assessment at day 10. Gene expression profiling and immunocytochemistry were performed using markers for pluripotency, proliferation and cardiomyocyte and NC differentiation. Cell proliferation was also assessed by measurements of embryoid body (EB) size and total protein quantification (day 7). Exposure to the OPs resulted in similar patterns of inhibition of beating cardiomyocyte differentiation and of myosin protein expression on day 10. However, these three chemically related compounds induced distinctive effects on NC cell differentiation, indicated by changes in expression levels of the NC precursor (Msx2), NC marker (Ap2α), and epithelial to mesenchymal transition (EMT; Snai2) gene transcripts. This study shows that investigating NC markers can provide added value for ESTc outcome profiling and may enhance the applicability of this assay for the screening of structurally related test chemicals.

Evaluation of atrazine neurodevelopment toxicity in vitro-application of hESC-based neural differentiation model

Atrazine is one of the widely used herbicides in the world and most of the current researches on atrazine neurodevelopment toxicity have focused on rodents or zebrafish models in vivo, resulting in relatively high cost, time consumption, and lower translational value to identify its hazard for the developing brain. Major international initiatives have pushed forward to convert the traditional animal-based developmental toxicity tests to in vitro assays using human cells to detect and predict chemical health hazards. In this study, we presented a human neural differentiation model based on human embryonic stem cells (hESC) that can be used to test toxicity at different stages of neural differentiation in vitro. hESC were differentiated into neural stem cells (NSC) and then terminally differentiated towards mixed neurons and glial cells for 21 days. Cell survival, proliferation, cell cycle, apoptosis, and gene expression levels were examined. Our results demonstrated that atrazine inhibited the proliferation of hESC and NSC, and showed different toxic sensitivity on these two kinds of cells. Also, atrazine blocked the NSC cell cycle G1 phase via down-regulating CCND1, CDK2, and CDK4, with no obvious effect on apoptosis. In addition, atrazine curbed EB spontaneous differentiation and NSC-induced neurons and glia cells differentiation. Atrazine altered genes expression levels of PAX6, TUBB3, NCAM1, GFAP, TH, NR4A1, and GRIA1. From the data we obtained, we recognized that the dopaminergic system was not the only target of atrazine neurotoxicity, glutamatergic neurons and astrocytes were also adversely affected.

Neural crest related gene transcript regulation by valproic acid analogues in the cardiac embryonic stem cell test

In vivo, neural crest (NC) cells contribute critically to heart formation. The embryonic stem cells in the cardiac Embryonic Stem cell Test (ESTc) differentiate into a heterogeneous cell population including non-cardiomyocyte cells. The use of molecular biomarkers from different mechanistic pathways can refine quantitative embryotoxicity assessment. Gene expression levels representing different signalling pathways that could relate to beating cardiomyocyte formation were analysed at different time-points. Immunocytochemistry showed NC cells were present in the ESTc and RT-qPCR showed upregulation of NC related gene expression levels in a time-dependent manner. NC related genes were sensitive to VPA and its analogues 2-ethylhexanoic acid (EHA) and 2-ethylhexanol (EHOL) and indicated VPA as the most potent one. STITCH ('search tool for interactions of chemicals') analysis showed relationships between the examined signalling pathways and suggested additional candidate marker genes. Biomarkers from dedicated mechanistic pathways, e.g. NC differentiation, provide promising tools for monitoring specific effects in ESTc.

Transcriptome profiling and pathway analysis of the effects of mono-(2-ethylhexyl) phthalate in mouse Sertoli cells

Phthalates are confirmed to have toxic effects on the reproductive system and are likely to have further damaging actions in humans. The present study explored the molecular mechanisms of the toxic effect of mono-(2-ethylhexyl) phthalate (MEHP) on mouse Sertoli cells. Cell apoptosis and proliferation assays were used to assess the effects of MEHP on the TM4 Sertoli cell line derived from mouse testes. TM4 cells were treated with two doses of MEHP or left untreated as a control group, followed by RNA extraction and analysis using high-throughput transcriptome sequencing technology. The gene expression profile obtained was then subjected to a bioinformatics analysis to explore the molecular mechanisms of reproductive toxicity. The results revealed that 528 and 269 genes were upregulated in the high- and low-dose MEHP groups of cells compared with the control group, while 148 and 173 genes were downregulated. Gene ontology (GO) analysis indicated that the differently expressed genes were associated with the GO term 'extracellular region' of the cellular component domain in the high and low MEHP groups. Compared with the control group, eight common pathway changes were identified in the high- and low-dose MEHP groups, including 'terpenoid backbone biosynthesis'. Reverse transcription-quantitative polymerase chain reaction analysis was used to validation, and hermetic effects were observed for certain genes. These results provide an important basis and experimental data for further research into the mechanisms of phthalate-induced toxicity.

A Qualitative Modeling Approach for Whole Genome Prediction Using High-Throughput Toxicogenomics Data and Pathway-Based Validation

Efficient high-throughput transcriptomics (HTT) tools promise inexpensive, rapid assessment of possible biological consequences of human and environmental exposures to tens of thousands of chemicals in commerce. HTT systems have used relatively small sets of gene expression measurements coupled with mathematical prediction methods to estimate genome-wide gene expression and are often trained and validated using pharmaceutical compounds. It is unclear whether these training sets are suitable for general toxicity testing applications and the more diverse chemical space represented by commercial chemicals and environmental contaminants. In this work, we built predictive computational models that inferred whole genome transcriptional profiles from a smaller sample of surrogate genes. The model was trained and validated using a large scale toxicogenomics database with gene expression data from exposure to heterogeneous chemicals from a wide range of classes (the Open TG-GATEs data base). The method of predictor selection was designed to allow high fidelity gene prediction from any pre-existing gene expression data set, regardless of animal species or data measurement platform. Predictive qualitative models were developed with this TG-GATES data that contained gene expression data of human primary hepatocytes with over 941 samples covering 158 compounds. A sequential forward search-based greedy algorithm, combining different fitting approaches and machine learning techniques, was used to find an optimal set of surrogate genes that predicted differential expression changes of the remaining genome. We then used pathway enrichment of up-regulated and down-regulated genes to assess the ability of a limited gene set to determine relevant patterns of tissue response. In addition, we compared prediction performance using the surrogate genes found from our greedy algorithm (referred to as the SV2000) with the landmark genes provided by existing technologies such as L1000 (Genometry) and S1500 (Tox21), finding better predictive performance for the SV2000. The ability of these predictive algorithms to predict pathway level responses is a positive step toward incorporating mode of action (MOA) analysis into the high throughput prioritization and testing of the large number of chemicals in need of safety evaluation.

Novel transcriptome assembly and comparative toxicity pathway analysis in mahi-mahi (Coryphaena hippurus) embryos and larvae exposed to Deepwater Horizon oil

The impacts of Deepwater Horizon (DWH) oil on morphology and function during embryonic development have been documented for a number of fish species, including the economically and ecologically important pelagic species, mahi-mahi (Coryphaena hippurus). However, further investigations on molecular events and pathways responsible for developmental toxicity have been largely restricted due to the limited molecular data available for this species. We sought to establish the de novo transcriptomic database from the embryos and larvae of mahi-mahi exposed to water accommodated fractions (HEWAFs) of two DWH oil types (weathered and source oil), in an effort to advance our understanding of the molecular aspects involved during specific toxicity responses. By high throughput sequencing (HTS), we obtained the first de novo transcriptome of mahi-mahi, with 60,842 assembled transcripts and 30,518 BLAST hits. Among them, 2,345 genes were significantly regulated in 96hpf larvae after exposure to weathered oil. With comparative analysis to a reference-transcriptome-guided approach on gene ontology and tox-pathways, we confirmed the novel approach effective for exploring tox-pathways in non-model species, and also identified a list of co-expressed genes as potential biomarkers which will provide information for the construction of an Adverse Outcome Pathway which could be useful in Ecological Risk Assessments.

Stem cell toxicology: a powerful tool to assess pollution effects on human health

Environmental pollution is a global problem; the lack of comprehensive toxicological assessments may lead to increased health risks. To fully understand the health effects of pollution, it is paramount to implement fast, efficient and specific toxicity screening that relies on human models rather than on time-consuming, expensive and often inaccurate tests involving live animals. Human stem cell toxicology represents a valid alternative to traditional toxicity assays because it takes advantage of the ability of stem cells to differentiate into multiple cell types and tissues of the human body. Thus, this branch of toxicology provides a possibility to assess cellular, embryonic, developmental, reproductive and functional toxicity in vitro within a single system highly relevant to human physiology. In this review, we describe the development, performance and future perspectives of stem cell toxicology, with an emphasis on how it can meet the increasing challenges posed by environmental pollution in the modern world.

Effects of long-term endocrine disrupting compound exposure on Macaca mulatta embryonic stem cells

Endocrine disrupting chemicals (EDCs) exert significant effects on health and physiology, many traceable to effects on stem cell programming underlying development. Understanding risk of low-level, chronic EDC exposure will be enhanced by knowledge of effects on stem cells. We exposed rhesus monkey embryonic stem cells to low levels of five EDCs [bisphenol A (BPA), atrazine (ATR), tributyltin (TBT), perfluorooctanoic acid (PFOA), and di-(2-ethylhexyl) phthalate (DEHP)] for 28days, and evaluated effects on gene expression by RNAseq transcriptome profiling. We observed little effect of BPA, and small numbers of affected genes (≤119) with other EDCs. There was substantial overlap in effects across two, three, or four treatments. Ingenuity Pathway analysis indicated suppression of cell survival genes and genes downstream of several stress response mediators, activation of cell death genes, and modulations in several genes regulating pluripotency, differentiation, and germ layer development. Potential adverse effects of these changes on development are discussed.

Using Transcriptomics to Evaluate Thresholds in Genotoxicity Dose–Response

Several genotoxic chemicals have been reported to produce threshold-shaped dose–response curves for mutation and genotoxicity assays, both in vivo and in vitro, challenging the current default practice for risk assessment of genotoxic chemicals, which assumes a linear dose–response below the lowest tested dose. Statistical methods cannot determine whether a biological threshold exists with sufficient confidence to overturn this assumption of linearity. Indeed, to truly define the shape of the dose–response curves, we must look to the underlying biology and develop targeted experiments to identify and measure the key processes governing the response of the cell to DNA damage. This chapter describes a series of studies aimed at defining the key transcriptional responses. Two approaches were taken to evaluate transcriptional responses preventing micronucleus induction: (1) comparison of gene signatures for several prototype compounds at a single chemical dose that led to a similar activation of the p53-DNA damage pathway (i.e. 1.5-fold increase in total p53); and (2) evaluation of a subset of chemicals with in-depth dose–response studies. The goal of these efforts was to determine the transcriptional pathways responsible for maintaining homeostasis at low levels of DNA damage, i.e., the biological underpinning of threshold-shaped dose–response curves for mutagenicity.

RNA transcripts for the quantification of differentiation allow marked improvements in the performance of embryonic stem cell test (EST)

Embryonic stem cell test (EST) is an in vitro validated assay for testing embryotoxicity. The EST needs improvements before being used for regulatory purposes, but also needs technical simplification for use in high throughput screenings. We propose the quantification in alterations of the differentiation of D3 monolayer cells cultures through the expression of biomarker genes in a shorter (5-day) and technically simpler (we use only monolayer cultures) test. We have defined a set of sixteen different genes biomarkers of ectoderm (Nrcam, Nes, Shh and Pnpla6), endoderm formation (Flk1 and Afp), mesoderm formation (Mesp1, Vegfa, Myo1e and Hdac7) and general cellular processes (Cdk1, Myc, Jun, Mixl, Cer and Wnt3). These, together with alterations in the viability of D3 and 3T3 cells and the prediction model of a classic EST, enhance the features of EST determinations to 100% concordance between in vivo-in vitro predictions with a set of seven different chemicals used in the validation of a classic EST. In conclusion, the proposed changes implemented in the classic EST confer it more reliability, speed and technical simplicity, which brings the EST closer to high throughput processes and regulatory purposes.

Grouping of histone deacetylase inhibitors and other toxicants disturbing neural crest migration by transcriptional profiling

Functional assays, such as the "migration inhibition of neural crest cells" (MINC) developmental toxicity test, can identify toxicants without requiring knowledge on their mode of action (MoA). Here, we were interested, whether (i) inhibition of migration by structurally diverse toxicants resulted in a unified signature of transcriptional changes; (ii) whether statistically-identified transcript patterns would inform on compound grouping even though individual genes were little regulated, and (iii) whether analysis of a small group of biologically-relevant transcripts would allow the grouping of compounds according to their MoA. We analyzed transcripts of 35 'migration genes' after treatment with 16 migration-inhibiting toxicants. Clustering, principal component analysis and correlation analyses of the data showed that mechanistically related compounds (e.g. histone deacetylase inhibitors (HDACi), PCBs) triggered similar transcriptional changes, but groups of structurally diverse toxicants largely differed in their transcriptional effects. Linear discriminant analysis (LDA) confirmed the specific clustering of HDACi across multiple separate experiments. Similarity of the signatures of the HDACi trichostatin A and suberoylanilide hydroxamic acid to the one of valproic acid (VPA), suggested that the latter compound acts as HDACi when impairing neural crest migration. In conclusion, the data suggest that (i) a given functional effect (e.g. inhibition of migration) can be associated with highly diverse signatures of transcript changes; (ii) statistically significant grouping of mechanistically-related compounds can be achieved on the basis of few genes with small regulations. Thus, incorporation of mechanistic markers in functional in vitro tests may support read-across procedures, also for structurally un-related compounds.

Distinct gene expression responses of two anticonvulsant drugs in a novel human embryonic stem cell based neural differentiation assay protocol

Hazard assessment of chemicals and pharmaceuticals is increasingly gaining from knowledge about molecular mechanisms of toxic action acquired in dedicated in vitro assays. We have developed an efficient human embryonic stem cell neural differentiation test (hESTn) that allows the study of the molecular interaction of compounds with the neural differentiation process. Within the 11-day differentiation protocol of the assay, embryonic stem cells lost their pluripotency, evidenced by the reduced expression of stem cell markers Pou5F1 and Nanog. Moreover, stem cells differentiated into neural cells, with morphologically visible neural structures together with increased expression of neural differentiation-related genes such as βIII-tubulin, Map2, Neurogin1, Mapt and Reelin. Valproic acid (VPA) and carbamazepine (CBZ) exposure during hESTn differentiation led to concentration-dependent reduced expression of βIII-tubulin, Neurogin1 and Reelin. In parallel VPA caused an increased gene expression of Map2 and Mapt which is possibly related to the neural protective effect of VPA. These findings illustrate the added value of gene expression analysis for detecting compound specific effects in hESTn. Our findings were in line with and could explain effects observed in animal studies. This study demonstrates the potential of this assay protocol for mechanistic analysis of specific compound-induced inhibition of human neural cell differentiation.

Predictive models and computational toxicology

Understanding the potential health risks posed by environmental chemicals is a significant challenge elevated by the large number of diverse chemicals with generally uncharacterized exposures, mechanisms, and toxicities. The ToxCast computational toxicology research program was launched by EPA in 2007 and is part of the federal Tox21 consortium to develop a cost-effective approach for efficiently prioritizing the toxicity testing of thousands of chemicals and the application of this information to assessing human toxicology. ToxCast addresses this problem through an integrated workflow using high-throughput screening (HTS) of chemical libraries across more than 650 in vitro assays including biochemical assays, human cells and cell lines, and alternative models such as mouse embryonic stem cells and zebrafish embryo development. The initial phase of ToxCast profiled a library of 309 environmental chemicals, mostly pesticidal actives having rich in vivo data from guideline studies that include chronic/cancer bioassays in mice and rats, multigenerational reproductive studies in rats, and prenatal developmental toxicity endpoints in rats and rabbits. The first phase of ToxCast was used to build models that aim to determine how well in vivo animal effects can be predicted solely from the in vitro data. Phase I is now complete and both the in vitro data (ToxCast) and anchoring in vivo database (ToxRefDB) have been made available to the public (http://actor.epa.gov/). As Phase II of ToxCast is now underway, the purpose of this chapter is to review progress to date with ToxCast predictive modeling, using specific examples on developmental and reproductive effects in rats and rabbits with lessons learned during Phase I.

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

Background

Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set analysis (GSA) methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles.

Methods

We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human) and 588 (mouse) gene sets from the Comparative Toxicogenomics Database (CTD). We tested for significant differential expression (SDE) (false discovery rate -corrected p-values < 0.05) of the next-gen TM-derived gene sets and the CTD-derived gene sets in gene expression (GE) data sets of five chemicals (from experimental models). We tested for SDE of gene sets for six fibrates in a peroxisome proliferator-activated receptor alpha (PPARA) knock-out GE dataset and compared to results from the Connectivity Map. We tested for SDE of 319 next-gen TM-derived gene sets for environmental toxicants in three GE data sets of triazoles, and tested for SDE of 442 gene sets associated with embryonic structures. We compared the gene sets to triazole effects seen in the Whole Embryo Culture (WEC), and used principal component analysis (PCA) to discriminate triazoles from other chemicals.

Results

Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants had a similar toxicity pattern as the triazoles. We confirmed embryotoxic effects, and discriminated triazoles from other chemicals.

Conclusions

Gene set analysis with next-gen TM-derived chemical response-specific gene sets is a scalable method for identifying similarities in gene responses to other chemicals, from which one may infer potential mode of action and/or toxic effect.

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.

The epigenetic lorax: gene-environment interactions in human health

Over the last decade, we have witnessed an explosion of information on genetic factors underlying common human diseases and disorders. This 'human genomics' information revolution has occurred as a backdrop to a rapid increase in the rates of many human disorders and diseases. For example, obesity, Type 2 diabetes, asthma, autism spectrum disorder and attention deficit hyperactivity disorder have increased at rates that cannot be due to changes in the genetic structure of the population, and are difficult to ascribe to changes in diagnostic criteria or ascertainment. A likely cause of the increased incidence of these disorders is increased exposure to environmental factors that modify gene function. Many environmental factors that have epidemiological association with common human disorders are likely to exert their effects through epigenetic alterations. This general mechanism of gene-environment interaction poses special challenges for individuals, educators, scientists and public policy makers in defining, monitoring and mitigating exposures.

Dose response analysis of monophthalates in the murine embryonic stem cell test assessed by cardiomyocyte differentiation and gene expression

The embryonic stem cell test (EST) is based on compound-induced inhibition of cardiomyocyte differentiation of pluripotent stem cells. We examined the use of transcriptomics to assess concentration-effect relationships and performed potency ranking within a chemical class. Three embryotoxic phthalate monoesters, monobutyl phthalate (MBuP), monobenzyl phthalate (MBzP) and mono-(2-ethylhexyl) phthalate (MEHP) and the non-embryotoxic monomethyl phthalate (MMP) were studied for their effects on gene expression. Effects on gene expression were observed at concentrations that did not inhibit cardiomyocyte differentiation or induce cytotoxicity. The embryotoxic phthalate monoesters altered the expression of 668 commonly expressed genes in a concentration-dependent fashion. The same potency ranking was observed for morphology and gene expression (MEHP>MBzP>MBuP>MMP). These results indicate that integrating transcriptomics provides a sensitive method to measure the dose-dependent effects of phthalate monoester exposure and enables potency ranking based on a common mode of action within a class of compounds. Transcriptomic approaches may improve the applicability of the EST, in terms of sensitivity and specificity.

An optimized gene set for transcriptomics based neurodevelopmental toxicity prediction in the neural embryonic stem cell test

The murine neural embryonic stem cell test (ESTn) is an in vitro model for neurodevelopmental toxicity testing. Recent studies have shown that application of transcriptomics analyses in the ESTn is useful for obtaining more accurate predictions as well as mechanistic insights. Gene expression responses due to stem cell neural differentiation versus toxicant exposure could be distinguished using the Principal Component Analysis based differentiation track algorithm. In this study, we performed a de novo analysis on combined raw data (10 compounds, 19 exposures) from three previous transcriptomics studies to identify an optimized gene set for neurodevelopmental toxicity prediction in the ESTn. By evaluating predictions of 200,000 randomly selected gene sets, we identified genes which significantly contributed to the prediction reliability. A set of 100 genes was obtained, predominantly involved in (neural) development. Further stringency restrictions resulted in a set of 29 genes that allowed for 84% prediction accuracy (area under the curve 94%). We anticipate these gene sets will contribute to further improve ESTn transcriptomics studies aimed at compound risk assessment.

Effect of chemical mutagens and carcinogens on gene expression profiles in human TK6 cells

Characterization of toxicogenomic signatures of carcinogen exposure holds significant promise for mechanistic and predictive toxicology. In vitro transcriptomic studies allow the comparison of the response to chemicals with diverse mode of actions under controlled experimental conditions. We conducted an in vitro study in TK6 cells to characterize gene expression signatures of exposure to 15 genotoxic carcinogens frequently used in European industries. We also examined the dose-responsive changes in gene expression, and perturbation of biochemical pathways in response to these carcinogens. TK6 cells were exposed at 3 dose levels for 24 h with and without S9 human metabolic mix. Since S9 had an impact on gene expression (885 genes), we analyzed the gene expression data from cells cultures incubated with S9 and without S9 independently. The ribosome pathway was affected by all chemical-dose combinations. However in general, no similar gene expression was observed among carcinogens. Further, pathways, i.e. cell cycle, DNA repair mechanisms, RNA degradation, that were common within sets of chemical-dose combination were suggested by clustergram. Linear trends in dose–response of gene expression were observed for Trichloroethylene, Benz[a]anthracene, Epichlorohydrin, Benzene, and Hydroquinone. The significantly altered genes were involved in the regulation of (anti-) apoptosis, maintenance of cell survival, tumor necrosis factor-related pathways and immune response, in agreement with several other studies. Similarly in S9+ cultures, Benz[a]pyrene, Styrene and Trichloroethylene each modified over 1000 genes at high concentrations. Our findings expand our understanding of the transcriptomic response to genotoxic carcinogens, revealing the alteration of diverse sets of genes and pathways involved in cellular homeostasis and cell cycle control.

Compound-specific effects of diverse neurodevelopmental toxicants on global gene expression in the neural embryonic stem cell test (ESTn)

Alternative assays for developmental toxicity testing are needed to reduce animal use in regulatory toxicology. The in vitro murine neural embryonic stem cell test (ESTn) was designed as an alternative for neurodevelopmental toxicity testing. The integration of toxicogenomic-based approaches may further increase predictivity as well as provide insight into underlying mechanisms of developmental toxicity. In the present study, we investigated concentration-dependent effects of six mechanistically diverse compounds, acetaldehyde (ACE), carbamazepine (CBZ), flusilazole (FLU), monoethylhexyl phthalate (MEHP), penicillin G (PENG) and phenytoin (PHE), on the transcriptome and neural differentiation in the ESTn. All compounds with the exception of PENG altered ESTn morphology (cytotoxicity and neural differentiation) in a concentration-dependent manner. Compound induced gene expression changes and corresponding enriched gene ontology biological processes (GO-BP) were identified after 24h exposure at equipotent differentiation-inhibiting concentrations of the compounds. Both compound-specific and common gene expression changes were observed between subsets of tested compounds, in terms of significance, magnitude of regulation and functionality. For example, ACE, CBZ and FLU induced robust changes in number of significantly altered genes (≥ 687 genes) as well as a variety of GO-BP, as compared to MEHP, PHE and PENG (≤ 55 genes with no significant changes in GO-BP observed). Genes associated with developmentally related processes (embryonic morphogenesis, neuron differentiation, and Wnt signaling) showed diverse regulation after exposure to ACE, CBZ and FLU. In addition, gene expression and GO-BP enrichment showed concentration dependence, allowing discrimination of non-toxic versus toxic concentrations on the basis of transcriptomics. This information may be used to define adaptive versus toxic responses at the transcriptome level.

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.

The embryonic stem cell test combined with toxicogenomics as an alternative testing model for the assessment of developmental toxicity

One of the most studied in vitro alternative testing methods for identification of developmental toxicity is the embryonic stem cell test (EST). Although the EST has been formally validated, the applicability domain as well as the predictability of the model needs further study to allow successful implementation of the EST as an alternative testing method in regulatory toxicity testing. Genomics technologies have already provided a proof of principle of their value in identification of toxicants such as carcinogenic compounds. Also within the EST, gene expression profiling has shown its value in the identification of developmental toxicity and in the evaluation of factors critical for risk assessment, such as dose and time responses. It is expected that the implementation of genomics into the EST will provide a more detailed end point evaluation as compared to the classical morphological scoring of differentiation cultures. Therefore, genomics may contribute to improvement of the EST, both in terms of definition of its applicability domain as well as its predictive capacity. In the present review, we present the progress that has been made with regard to the prediction of developmental toxicity using the EST combined with transcriptomics. Furthermore, we discuss the developments of additional aspects required for further optimization of the EST, including kinetics, the use of human embryonic stem cells (ESC) and computational toxicology. Finally, the current and future use of the EST model for prediction of developmental toxicity in testing strategies and in regulatory toxicity evaluations is discussed.