A graphical systems model and tissue-specific functional gene sets to aid transcriptomic analysis of chemical impacts on the female teleost reproductive axis

Adverse Outcome Pathway Network-Based Assessment of the Interactive Effects of an Androgen Receptor Agonist and an Aromatase Inhibitor on Fish Endocrine Function

Predictive approaches to assessing the toxicity of contaminant mixtures have been largely limited to chemicals that exert effects through the same biological molecular initiating event. However, by understanding specific pathways through which chemicals exert effects, it may be possible to identify shared "downstream" nodes as the basis for forecasting interactive effects of chemicals with different molecular initiating events. Adverse outcome pathway (AOP) networks conceptually support this type of analysis. We assessed the utility of a simple AOP network for predicting the effects of mixtures of an aromatase inhibitor (fadrozole) and an androgen receptor agonist (17β-trenbolone) on aspects of reproductive endocrine function in female fathead minnows. The fish were exposed to multiple concentrations of fadrozole and 17β-trenbolone individually or in combination for 48 or 96 h. Effects on 2 shared nodes in the AOP network, plasma 17β-estradiol (E2) concentration and vitellogenin (VTG) production (measured as hepatic vtg transcripts) responded as anticipated to fadrozole alone but were minimally impacted by 17β-trenbolone alone. Overall, there were indications that 17β-trenbolone enhanced decreases in E2 and vtg in fadrozole-exposed fish, as anticipated, but the results often were not statistically significant. Failure to consistently observe hypothesized interactions between fadrozole and 17β-trenbolone could be due to several factors, including lack of impact of 17β-trenbolone, inherent biological variability in the endpoints assessed, and/or an incomplete understanding of interactions (including feedback) between different pathways within the hypothalamic-pituitary-gonadal axis. Environ Toxicol Chem 2020;39:913-922. © 2020 SETAC.

Evaluating Chemicals for Thyroid Disruption: Opportunities and Challenges with in Vitro Testing and Adverse Outcome Pathway Approaches

BACKGROUND

Extensive clinical and experimental research documents the potential for chemical disruption of thyroid hormone (TH) signaling through multiple molecular targets. Perturbation of TH signaling can lead to abnormal brain development, cognitive impairments, and other adverse outcomes in humans and wildlife. To increase chemical safety screening efficiency and reduce vertebrate animal testing, in vitro assays that identify chemical interactions with molecular targets of the thyroid system have been developed and implemented.

OBJECTIVES

We present an adverse outcome pathway (AOP) network to link data derived from in vitro assays that measure chemical interactions with thyroid molecular targets to downstream events and adverse outcomes traditionally derived from in vivo testing. We examine the role of new in vitro technologies, in the context of the AOP network, in facilitating consideration of several important regulatory and biological challenges in characterizing chemicals that exert effects through a thyroid mechanism.

DISCUSSION

There is a substantial body of knowledge describing chemical effects on molecular and physiological regulation of TH signaling and associated adverse outcomes. Until recently, few alternative nonanimal assays were available to interrogate chemical effects on TH signaling. With the development of these new tools, screening large libraries of chemicals for interactions with molecular targets of the thyroid is now possible. Measuring early chemical interactions with targets in the thyroid pathway provides a means of linking adverse outcomes, which may be influenced by many biological processes, to a thyroid mechanism. However, the use of in vitro assays beyond chemical screening is complicated by continuing limits in our knowledge of TH signaling in important life stages and tissues, such as during fetal brain development. Nonetheless, the thyroid AOP network provides an ideal tool for defining causal linkages of a chemical exerting thyroid-dependent effects and identifying research needs to quantify these effects in support of regulatory decision making. https://doi.org/10.1289/EHP5297.

Molecular signaling pathways elicited by 17α-ethinylestradiol in Japanese medaka male larvae undergoing gonadal differentiation

Estrogenic contaminants released into water bodies are potentially affecting the reproduction of aquatic organisms. Exposure to 17α-ethinylestradiol (EE2), a synthetic estrogen agonist commonly found in sewage effluents, has been shown to cause gonadal changes in male gonochoristic fish ranging from gonadal intersex to complete sex reversal. Although these gonadal changes have been well studied in Japanese medaka Oryzias latipes, the molecular mechanisms behind them are poorly understood. Our objective was to study the signaling pathways elicited by exposure to different concentrations of EE2 in this species. Embryos and larvae were sexed by the presence of leucophores and dmy expression (only in males). Male medaka were exposed to two EE2 concentrations (30 and 300 ng/L) during their gonadal differentiation period (7-22 dpf). The transcriptome of larvae was analyzed using RNA sequencing followed by pathway analysis. Genes involved in sex differentiation and gonadal development (e.g., cldn19, ctbp1, hsd17b4) showed a female-like expression pattern in EE2-exposed males with some genes changing in expression in an EE2 concentration-dependent manner. However, not all genes known to be involved in sex differentiation and gonadal development (e.g., wnt4b) were altered by EE2. Several of the prominently affected signaling pathways involved genes associated with steroidogenesis, steroid receptor signaling and steroid metabolism, such as cyp2b3, cyp3b40, cyp1a, hsd17b4. We also report on novel genes and pathways affected that might play a role in gonadal changes, including several genes associated with FXR/RXR and LXR/RXR activation networks. This study is the first to examine the transcriptomic changes in male fish resulting from exposure to EE2 during the gonadal differentiation period, providing new insights on the signaling pathways involved in the development of gonadal changes in gonochoristic fish.

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

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

Prioritization of Contaminants of Emerging Concern in Wastewater Treatment Plant Discharges Using Chemical:Gene Interactions in Caged Fish

We examined whether contaminants present in surface waters could be prioritized for further assessment by linking the presence of specific chemicals to gene expression changes in exposed fish. Fathead minnows were deployed in cages for 2, 4, or 8 days at three locations near two different wastewater treatment plant discharge sites in the Saint Louis Bay, Duluth, MN and one upstream reference site. The biological impact of 51 chemicals detected in the surface water of 133 targeted chemicals was determined using biochemical endpoints, exposure activity ratios for biological and estrogenic responses, known chemical:gene interactions from biological pathways and knowledge bases, and analysis of the covariance of ovary gene expression with surface water chemistry. Thirty-two chemicals were significantly linked by covariance with expressed genes. No estrogenic impact on biochemical endpoints was observed in male or female minnows. However, bisphenol A (BPA) was identified by chemical:gene covariation as the most impactful estrogenic chemical across all exposure sites. This was consistent with identification of estrogenic effects on gene expression, high BPA exposure activity ratios across all test sites, and historical analysis of the study area. Gene expression analysis also indicated the presence of nontargeted chemicals including chemotherapeutics consistent with a local hospital waste stream. Overall impacts on gene expression appeared to be related to changes in treatment plant function during rain events. This approach appears useful in examining the impacts of complex mixtures on fish and offers a potential route in linking chemical exposure to adverse outcomes that may reduce population sustainability.

Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology

A quantitative adverse outcome pathway (qAOP) consists of one or more biologically based, computational models describing key event relationships linking a molecular initiating event (MIE) to an adverse outcome. A qAOP provides quantitative, dose-response, and time-course predictions that can support regulatory decision-making. Herein we describe several facets of qAOPs, including (a) motivation for development, (b) technical considerations, (c) evaluation of confidence, and (d) potential applications. The qAOP used as an illustrative example for these points describes the linkage between inhibition of cytochrome P450 19A aromatase (the MIE) and population-level decreases in the fathead minnow (FHM; Pimephales promelas). The qAOP consists of three linked computational models for the following: (a) the hypothalamic-pitutitary-gonadal axis in female FHMs, where aromatase inhibition decreases the conversion of testosterone to 17β-estradiol (E2), thereby reducing E2-dependent vitellogenin (VTG; egg yolk protein precursor) synthesis, (b) VTG-dependent egg development and spawning (fecundity), and (c) fecundity-dependent population trajectory. While development of the example qAOP was based on experiments with FHMs exposed to the aromatase inhibitor fadrozole, we also show how a toxic equivalence (TEQ) calculation allows use of the qAOP to predict effects of another, untested aromatase inhibitor, iprodione. While qAOP development can be resource-intensive, the quantitative predictions obtained, and TEQ-based application to multiple chemicals, may be sufficient to justify the cost for some applications in regulatory decision-making.

Derivation and Evaluation of Putative Adverse Outcome Pathways for the Effects of Cyclooxygenase Inhibitors on Reproductive Processes in Female Fish

Cyclooxygenase (COX) inhibitors are ubiquitous in aquatic systems and have been detected in fish tissues. The exposure of fish to these pharmaceuticals is concerning because COX inhibitors disrupt the synthesis of prostaglandins (PGs), which modulate a variety of essential biological functions, including reproduction. In this study, we investigated the effects of well-characterized mammalian COX inhibitors on female fathead minnow reproductive health. Fish (n = 8) were exposed for 96 h to water containing indomethacin (IN; 100 µg/l), ibuprofen (IB; 200 µg/l) or celecoxib (CX; 20 µg/l), and evaluated for effects on liver metabolome and ovarian gene expression. Metabolomic profiles of IN, IB and CX were not significantly different from control or one another. Exposure to IB and CX resulted in differential expression of comparable numbers of genes (IB = 433, CX = 545). In contrast, 2558 genes were differentially expressed in IN-treated fish. Functional analyses (canonical pathway and gene set enrichment) indicated extensive effects of IN on PG synthesis pathway, oocyte meiosis, and several other processes consistent with physiological roles of PGs. Transcriptomic data were congruent with PG data; IN-reduced plasma PG F2α concentration, whereas IB and CX did not. Five putative AOPs were developed linking the assumed molecular initiating event of COX inhibition, with PG reduction and the adverse outcome of reproductive failure via reduction of: (1) ovulation, (2) reproductive behaviors mediated by exogenous or endogenous PGs, and (3) oocyte maturation in fish. These pathways were developed using, in part, empirical data from the present study and other publicly available data.

Editor's Highlight: Computational Modeling of Plasma Vitellogenin Alterations in Response to Aromatase Inhibition in Fathead Minnows

In vertebrates, conversion of testosterone into 17β-estradiol (E2) is catalyzed by cytochrome P450 (CYP) 19A aromatase. An important role of E2 in oviparous vertebrates such as fish is stimulation of hepatic synthesis of the glycolipoprotein vitellogenin (VTG), an egg yolk precursor essential to oocyte development and larval survival. In fathead minnows (FHMs) (Pimephales promelas) exposed to the aromatase inhibitor fadrozole, plasma VTG levels do not change in concert with plasma E2 levels. Specifically, while plasma VTG and E2 levels both drop quickly when aromatase is first inhibited, the recovery of plasma VTG upon cessation of aromatase inhibition is substantially delayed relative to the recovery of plasma E2. We modified an existing computational model of the FHM hypothalamic-pituitary-gonadal axis to evaluate alternative hypotheses that might explain this delay. In the first hypothesis, a feedback loop involving active transport of VTG from the blood into the ovary is used. The activity of the transporter is negatively regulated by ovarian VTG. In the second hypothesis, a type 1 coherent feed-forward loop is implemented in the liver. This loop has 2 arms, both requiring E2 activation. The first arm describes direct, canonical E2-driven transcriptional induction of VTG, and the second describes an E2-driven intermediate transcriptional regulator that is also required for VTG synthesis. Both hypotheses accurately described the observed VTG dynamics. This result could be used to guide design of laboratory experiments intended to determine if either of the motifs, or perhaps even both of them, actually do control VTG dynamics in FHMs exposed to aromatase inhibitors.

In Silico analysis of perturbed steroidogenesis and gonad growth in fathead minnows (P. promelas) exposed to 17α-ethynylestradiol

The multi-factorial nature of adverse reproductive effects mediated by endocrine disrupting compounds (or EDCs) makes understanding the mechanistic basis of reproductive dysfunction a highly pertinent area of research. As a consequence, a main motivator for continued research is to integrate 'multi-leveled' complexity (i.e., from genes to phenotype) using mathematical methods capable of encapsulating properties of physiological relevance. In this study, an in silico stoichiometric model of piscine steroidogenesis was augmented with a 'biomass' reaction associating the underlying stoichiometry of steroidogenesis with a reaction representative of gonad growth. The ability of the in silico model to predict perturbed steroidogenesis and subsequent effects on gonad growth was tested by exposing reproductively active male and female fathead minnows (Pimephales promelas) to 88 ng/L of the synthetic estrogen, 17α-ethynylestradiol (EE2). The in silico model was parameterized (or constrained) with experimentally quantified concentrations of selected steroid hormones (using mass spectrometry) and fold changes in gene expression (using RT-qPCR) for selected steroidogenic enzyme genes, in gonads of male and female fish. Once constrained, the optimization framework of flux balance analysis (FBA) was used to calculate an optimal flux through the biomass reaction (analogous to gonad growth) and associated steroidogenic flux distributions required to generate biomass. FBA successfully predicted effects of EE2 exposure on fathead minnow gonad growth (%gonadosomatic index or %GSI) and perturbed production of steroid hormones. Specifically, FBA accurately predicted no effects of exposure on male %GSI and a significant reduction for female %GSI. Furthermore, in silico simulations accurately identified disrupted reaction fluxes catalyzing productions of androgens (in male fish) and progestogens (in female fish), an observation which agreed with in vivo experimentation. The analyses presented is the first-ever to successfully associate underlying flux properties of the steroidogenic network with gonad growth in fish, an approach which can incorporate in silico predictions with toxicological risk assessments.

Transcriptional changes in African clawed frogs (Xenopus laevis) exposed to 17α-ethynylestradiol during early development

Although the past two decades have witnessed a significant increase in the number of studies investigating effects of estrogenic chemicals on amphibians, to date little is known about specific molecular interactions of estrogens with the hypothalamus-pituitary-gonadal-hepatic axis in developing amphibians. Here, tissue-specific functional sets of genes, derived previously from studies of fishes exposed to endocrine active chemicals, were evaluated in Xenopus laevis exposed to 17α-ethynylestradiol (EE2) throughout their early development. Specifically, transcriptional responses of X. laevis exposed to 0.09, 0.84, or 8.81 µg EE2/L were characterized during sexual differentiation [31 day post hatch (dph)] and after completion of metamorphosis during the juvenile stage (89 dph). While at 31 dph there were no consistent effects of EE2 on abundances of transcripts,at 89 dph X. laevis exhibited significant alterations in expression of genes involved in steroid signaling and metabolism, synthesis of cholesterol, and vitellogenesis. Specifically, expression of androgen receptor, farnesyl diphosphate synthase, estrogen receptor α, and vitellogenin A2 was significantly greater (>2-fold) than in controls while expression of farnesoid x-activated receptors α and β was significantly less (>2-fold reduction) than in controls. These results support the hypothesis that sets of genes derived from studies in teleost fish can be extrapolated for use in amphibians during the juvenile stage but not in sexually undifferentiated individuals. Furthermore, changes in abundances of transcripts of the here utilized sets of genes in animals sampled post sexual differentiation were in accordance with developmental effects and alterations of gonadal histology reported in a parallel study. This set of genes might be useful for predicting potential adverse outcomes at later life-stages.

Transcriptomic effects-based monitoring for endocrine active chemicals: assessing relative contribution of treated wastewater to downstream pollution

The present study investigated whether a combination of targeted analytical chemistry information with unsupervised, data-rich biological methodology (i.e., transcriptomics) could be utilized to evaluate relative contributions of wastewater treatment plant (WWTP) effluents to biological effects. The effects of WWTP effluents on fish exposed to ambient, receiving waters were studied at three locations with distinct WWTP and watershed characteristics. At each location, 4 d exposures of male fathead minnows to the WWTP effluent and upstream and downstream ambient waters were conducted. Transcriptomic analyses were performed on livers using 15,000 feature microarrays, followed by a canonical pathway and gene set enrichment analyses. Enrichment of gene sets indicative of teleost brain-pituitary-gonadal-hepatic (BPGH) axis function indicated that WWTPs serve as an important source of endocrine active chemicals (EACs) that affect the BPGH axis (e.g., cholesterol and steroid metabolism were altered). The results indicated that transcriptomics may even pinpoint pertinent adverse outcomes (i.e., liver vacuolization) and groups of chemicals that preselected chemical analytes may miss. Transcriptomic Effects-Based monitoring was capable of distinguishing sites, and it reflected chemical pollution gradients, thus holding promise for assessment of relative contributions of point sources to pollution and the efficacy of pollution remediation.

Using transcriptomic tools to evaluate biological effects across effluent gradients at a diverse set of study sites in Minnesota, USA

The aim of this study was to explore the utility of "omics" approaches in monitoring aquatic environments where complex, often unknown stressors make chemical-specific risk assessment untenable. We examined changes in the fathead minnow (Pimephales promelas) ovarian transcriptome following 4-day exposures conducted at three sites in Minnesota (MN, USA). Within each site, fish were exposed to water from three locations along a spatial gradient relative to a wastewater treatment plant (WWTP) discharge. After exposure, site-specific impacts on gene expression in ovaries were assessed. Using an intragradient point of comparison, biological responses specifically associated with the WWTP effluent were identified using functional enrichment analyses. Fish exposed to water from locations downstream of the effluent discharges exhibited many transcriptomic responses in common with those exposed to the effluent, indicating that effects of the discharge do not fully dissipate downstream. Functional analyses showed a range of biological pathways impacted through effluent exposure at all three sites. Several of those impacted pathways at each site could be linked to potential adverse reproductive outcomes associated with the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows, specifically signaling pathways associated with oocyte meiosis, TGF-beta signaling, gonadotropin-releasing hormone (GnRH) and epidermal growth factor receptor family (ErbB), and gene sets associated with cyclin B-1 and metalloproteinase. The utility of this approach comes from the ability to identify biological responses to pollutant exposure, particularly those that can be tied to adverse outcomes at the population level and those that identify molecular targets for future studies.

Metabolomics for in situ environmental monitoring of surface waters impacted by contaminants from both point and nonpoint sources

We investigated the efficacy of metabolomics for field-monitoring of fish exposed to wastewater treatment plant (WWTP) effluents and nonpoint sources of chemical contamination. Lab-reared male fathead minnows (Pimephales promelas, FHM) were held in mobile monitoring units and exposed on-location to surface waters upstream and downstream of the effluent point source, as well as to the actual effluent at three different WWTP sites in Minnesota. After four days of exposure, livers were collected, extracted, and analyzed by (1)H NMR spectroscopy and GC-MS to characterize responses of the hepatic metabolome. Multivariate statistical analysis revealed distinct metabolite profile changes in response to effluent exposure from each of the three WWTPs. Differences among locations (i.e., upstream, downstream, and effluent) within each of the three sites were also identified. These observed differences comport with land-use and WWTP characteristics at the study sites. For example, at one of the sites, the metabolomic analyses suggested a positive interactive response from exposure to WWTP effluent and nearby nonpoint (likely agricultural related) contamination. These findings demonstrate the utility of metabolomics as a field-based technique for monitoring the exposure of fish to impacted surface waters.

High-throughput sequencing and pathway analysis reveal alteration of the pituitary transcriptome by 17α-ethynylestradiol (EE2) in female coho salmon, Oncorhynchus kisutch

Considerable research has been done on the effects of endocrine disrupting chemicals (EDCs) on reproduction and gene expression in the brain, liver and gonads of teleost fish, but information on impacts to the pituitary gland are still limited despite its central role in regulating reproduction. The aim of this study was to further our understanding of the potential effects of natural and synthetic estrogens on the brain-pituitary-gonad axis in fish by determining the effects of 17α-ethynylestradiol (EE2) on the pituitary transcriptome. We exposed sub-adult coho salmon (Oncorhynchus kisutch) to 0 or 12 ng EE2/L for up to 6 weeks and effects on the pituitary transcriptome of females were assessed using high-throughput Illumina(®) sequencing, RNA-Seq and pathway analysis. After 1 or 6 weeks, 218 and 670 contiguous sequences (contigs) respectively, were differentially expressed in pituitaries of EE2-exposed fish relative to control. Two of the most highly up- and down-regulated contigs were luteinizing hormone β subunit (241-fold and 395-fold at 1 and 6 weeks, respectively) and follicle-stimulating hormone β subunit (-3.4-fold at 6 weeks). Additional contigs related to gonadotropin synthesis and release were differentially expressed in EE2-exposed fish relative to controls. These included contigs involved in gonadotropin releasing hormone (GNRH) and transforming growth factor-β signaling. There was an over-representation of significantly affected contigs in 33 and 18 canonical pathways at 1 and 6 weeks, respectively, including circadian rhythm signaling, calcium signaling, peroxisome proliferator-activated receptor (PPAR) signaling, PPARα/retinoid x receptor α activation, and netrin signaling. Network analysis identified potential interactions between genes involved in circadian rhythm and GNRH signaling, suggesting possible effects of EE2 on timing of reproductive events.

Effects of exposure to 17α-ethynylestradiol during larval development on growth, sexual differentiation, and abundances of transcripts in the liver of the wood frog (Lithobates sylvaticus)

Populations of amphibians are in decline in certain locations around the world, and the possible contribution of environmental contaminants, including estrogenic compounds, to these declines is of potential concern. In the current study, responses of the wood frog (Lithobates sylvaticus) to exposure to 17α-ethynylestradiol (EE2), the synthetic estrogen used in oral contraceptives, during the larval period were characterized. Exposure of L. sylvaticus to 1.08, 9.55, or 80.9 μg EE2/L had no effects on survival, growth, or metamorphic endpoints monitored in the current study. However, there were significant effects of exposure to EE2 on phenotypic sex ratios. In general, lesser proportions of L. sylvaticus developed as phenotypic males and greater proportions developed as phenotypic females or with mixed sex phenotypes at all concentrations of EE2 tested. Utilizing the data collected in the current study, the EC(50) for complete feminization of L. sylvaticus was determined to be 7.7 μg EE2/L, and the EC(50) for partial feminization was determined to be 2.3 μg EE2/L. In addition, after chronic exposure, abundances of transcripts of vitellogenin A2, high density lipoprotein binding protein, and 7-dehydrocholesterol reductase were 1.8-280-fold greater in livers from L. sylvaticus exposed to EE2 compared to controls. Overall, there were significant effects of exposure to all concentrations of EE2 tested, the least of which was within about 2-fold of estrogen equivalent concentrations previously measured in the environment.

A computational model to predict rat ovarian steroid secretion from in vitro experiments with endocrine disruptors

A finely tuned balance between estrogens and androgens controls reproductive functions, and the last step of steroidogenesis plays a key role in maintaining that balance. Environmental toxicants are a serious health concern, and numerous studies have been devoted to studying the effects of endocrine disrupting chemicals (EDCs). The effects of EDCs on steroidogenic enzymes may influence steroid secretion and thus lead to reproductive toxicity. To predict hormonal balance disruption on the basis of data on aromatase activity and mRNA level modulation obtained in vitro on granulosa cells, we developed a mathematical model for the last gonadal steps of the sex steroid synthesis pathway. The model can simulate the ovarian synthesis and secretion of estrone, estradiol, androstenedione, and testosterone, and their response to endocrine disruption. The model is able to predict ovarian sex steroid concentrations under normal estrous cycle in female rat, and ovarian estradiol concentrations in adult female rats exposed to atrazine, bisphenol A, metabolites of methoxychlor or vinclozolin, and letrozole.

Advancing the next generation of health risk assessment

BACKGROUND

Over the past 20 years, knowledge of the genome and its function has increased dramatically, but risk assessment methodologies using such knowledge have not advanced accordingly.

OBJECTIVE

This commentary describes a collaborative effort among several federal and state agencies to advance the next generation of risk assessment. The objective of the NexGen program is to begin to incorporate recent progress in molecular and systems biology into risk assessment practice. The ultimate success of this program will be based on the incorporation of new practices that facilitate faster, cheaper, and/or more accurate assessments of public health risks.

METHODS

We are developing prototype risk assessments that compare the results of traditional, data-rich risk assessments with insights gained from new types of molecular and systems biology data. In this manner, new approaches can be validated, traditional approaches improved, and the value of different types of new scientific information better understood.

DISCUSSION AND CONCLUSIONS

We anticipate that these new approaches will have a variety of applications, such as assessment of new and existing chemicals in commerce and the design of chemical products and processes that reduce or eliminate the use or generation of hazardous substances. Additionally, results of the effort are likely to spur further research and test methods development. Full implementation of new approaches is likely to take 10-20 years.

Discovery and validation of gene classifiers for endocrine-disrupting chemicals in zebrafish (danio rerio)

BACKGROUND

Development and application of transcriptomics-based gene classifiers for ecotoxicological applications lag far behind those of biomedical sciences. Many such classifiers discovered thus far lack vigorous statistical and experimental validations. A combination of genetic algorithm/support vector machines and genetic algorithm/K nearest neighbors was used in this study to search for classifiers of endocrine-disrupting chemicals (EDCs) in zebrafish. Searches were conducted on both tissue-specific and tissue-combined datasets, either across the entire transcriptome or within individual transcription factor (TF) networks previously linked to EDC effects. Candidate classifiers were evaluated by gene set enrichment analysis (GSEA) on both the original training data and a dedicated validation dataset.

RESULTS

Multi-tissue dataset yielded no classifiers. Among the 19 chemical-tissue conditions evaluated, the transcriptome-wide searches yielded classifiers for six of them, each having approximately 20 to 30 gene features unique to a condition. Searches within individual TF networks produced classifiers for 15 chemical-tissue conditions, each containing 100 or fewer top-ranked gene features pooled from those of multiple TF networks and also unique to each condition. For the training dataset, 10 out of 11 classifiers successfully identified the gene expression profiles (GEPs) of their targeted chemical-tissue conditions by GSEA. For the validation dataset, classifiers for prochloraz-ovary and flutamide-ovary also correctly identified the GEPs of corresponding conditions while no classifier could predict the GEP from prochloraz-brain.

CONCLUSIONS

The discrepancies in the performance of these classifiers were attributed in part to varying data complexity among the conditions, as measured to some degree by Fisher's discriminant ratio statistic. This variation in data complexity could likely be compensated by adjusting sample size for individual chemical-tissue conditions, thus suggesting a need for a preliminary survey of transcriptomic responses before launching a full scale classifier discovery effort. Classifier discovery based on individual TF networks could yield more mechanistically-oriented biomarkers. GSEA proved to be a flexible and effective tool for application of gene classifiers but a similar and more refined algorithm, connectivity mapping, should also be explored. The distribution characteristics of classifiers across tissues, chemicals, and TF networks suggested a differential biological impact among the EDCs on zebrafish transcriptome involving some basic cellular functions.