Putative adverse outcome pathway development based on physiological responses of female fathead minnows to model estrogen versus androgen receptor agonists

Several adverse outcome pathways (AOPs) have linked molecular initiating events like aromatase inhibition, androgen receptor (AR) agonism, and estrogen receptor (ER) antagonism to reproductive impairment in adult fish. Estrogen receptor agonists can also cause adverse reproductive effects, however, the early key events (KEs) in an AOP leading to this are mostly unknown. The primary aim of this study was to develop hypotheses regarding the potential mechanisms through which exposure to ER agonists might lead to reproductive impairment in female fish. Mature fathead minnows were exposed to 1 or 10 ng 17α-ethynylestradiol (EE2)/L or 10 or 100 µg bisphenol A (BPA)/L for 14 d. The response to EE2 and BPA was contrasted with the effects of 500 ng/L of 17β-trenbolone (TRB), an AR agonist, as well as TRB combined with the low and high concentrations of EE2 or BPA tested individually. Exposure to 10 ng EE2/L, 100 µg BPA/L, TRB, or the various mixtures with TRB caused significant decreases in plasma concentrations of 17β-estradiol. Exposure to TRB alone caused a significant reduction in plasma vitellogenin (VTG), but VTG was unaffected or even increased in females exposed to EE2 or BPA alone or, in most cases, in mixtures with TRB. Over the course of the 14-d exposure, the only treatments that clearly did not affect egg production were 1 ng EE2/L and 10 µg BPA/L. Based on these results and knowledge of hypothalamic-pituitary-gonadal axis function, we hypothesize an AOP whereby decreased production of maturation-inducing steroid leading to impaired oocyte maturation and ovulation, possibly due to negative feedback or direct inhibitory effects of membrane ER activation, could be responsible for causing adverse reproductive impacts in female fish exposed to ER agonists.

Inhibitory effects of estrogenic endocrine disrupting chemicals on fin regeneration in zebrafish are dependent on estrogen receptors

For fish and other aquatic organisms, disrupting their capacity for repair and regeneration will reduce their quality of life and survivorship in the wild. Studies have shown that 17α-ethinylestradiol (EE2), a synthetic estrogenic endocrine disrupting chemical (EEDC), can inhibit caudal fin regeneration in larval zebrafish following fin amputation. However, whether the inhibitory effects of EE2 are dependent on estrogen receptor (ER) remains unknown. Therefore, in this study, amputated zebrafish larvae were exposed to the ER agonist EE2 alone and in combination with the ER antagonist ICI 182,780 (ICI), and the change in regenerative capacity was determined. The inhibition of fin regeneration caused by EE2 alone (100 ng/L) was ameliorated after combination with ICI (30-300 μg/L), and these changes in regeneration-related signaling and the immune system corresponded with morphological observations, implying that the effects of EE2 on regeneration were possibly initiated by the activation of ER. Furthermore, the role of ER was confirmed with a natural ligand of ER, namely, 17β-estradiol (E2), and as expected, the effects of E2 (10, 100 and 1000 ng/L) paralleled those of EE2. In conclusion, EEDCs can disrupt the regenerative capacity in zebrafish, possibly due to the binding and activation of ERs and the consequent alteration of signaling pathways that regulate fin regeneration and immune competence. Given that EEDCs appear to be ubiquitous in the aquatic environment, the risk of these chemicals might be readdressed regarding their potential effects on tissue repair and regeneration.

Characterization of vitellogenin concentration in male fathead minnow mucus compared to plasma, and liver mRNA

The objective of this study was to characterize vitellogenin (VTG) protein in male fathead minnow (Pimephales promelas) mucus compared with more conventional measures in plasma and mRNA isolated from liver. To assess the intensity and duration of changes in mucus VTG concentrations, male fathead minnows were exposed to 17α-ethinylestradiol (EE2) for 7 days with a subsequent depuration period of 14 days. The experiment was conducted in a flow-through system to maintain a consistent concentration of EE2 at a nominal EC₅₀ concentration of 2.5 ng/L and high concentration of 10 ng/L as a positive control. Mucus, plasma and liver were sampled at regular intervals throughout the study. Relative abundance of vtg mRNA increased after 2 days of exposure and returned to control levels after 4 days of depuration. VTG protein concentration displayed similar induction kinetics in both mucus and plasma, however, it was found to be significantly increased after 2 days of exposure using the mucus-based assays and 7 days with the plasma-based assay. Significantly elevated levels of VTG were detected by both assays throughout the 14-day depuration period. The elimination of the laborious plasma collection step in the mucus-based workflow allowed sampling of smaller organisms where blood volume is limiting. It also resulted in significant gains in workflow efficiency, decreasing sampling time without loss of performance.

Chronic exposure to environmental concentrations of phenanthrene impairs zebrafish reproduction

Phenanthrene (PHE) is a tricyclic polycyclic aromatic hydrocarbon which distributed extensively in the aquatic environment. However, the knowledge about its impact on fish reproduction is still limited, particularly under a chronic exposure regime. In this study, we exposed zebrafish (Danio rerio) embryos to environmentally relevant concentrations (0.2, 1.0, and 5.0 μg/L) of PHE for 4 months and assessed the impact on reproduction. The results demonstrated that egg production was decreased in fish exposed to PHE, with a significant reduction at 5.0 μg/L. The exposure significantly decreased the circulating concentrations of estradiol (E2) and testosterone (T) in female fish or E2 in male fish. In addition, plasma vitellogenin levels were significantly inhibited after PHE exposure in female fish. The transcription of hypothalamic-pituitary-gonadal (HPG) axis related genes (GnRH2, FSHβ, LHβ, 17β-HSD, CYP11A1, and CYP19a) were significantly altered in a sex-specific manner. In addition, embryos derived from exposed parents exhibited increased malformation and decreased hatching success in the F1 generation. Taken together, these results demonstrate that chronic exposure to environmentally relevant concentration of PHE could cause adverse effects on reproduction and impair the development of offspring, ultimately leading to fish population decline in aquatic environment.

Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment

A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide "bottom-up" mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a "top-down" approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments. Integr Environ Assess Manag 2018;14:615-624. © 2018 SETAC.

Physiological modes of action across species and toxicants: the key to predictive ecotoxicology

As ecotoxicologists we strive for a better understanding of how chemicals affect our environment. Humanity needs tools to identify those combinations of man-made chemicals and organisms most likely to cause problems. In other words: which of the millions of species are at risk from pollution? And which of the tens of thousands of chemicals contribute most to the risk? We identified our poor knowledge on physiological modes of action (how a chemical affects the energy allocation in an organism), and how they vary across species and toxicants, as a major knowledge gap. We also find that the key to predictive ecotoxicology is the systematic, rigorous characterization of physiological modes of action because that will enable more powerful in vitro to in vivo toxicity extrapolation and in silico ecotoxicology. In the near future, we expect a step change in our ability to study physiological modes of action by improved, and partially automated, experimental methods. Once we have populated the matrix of species and toxicants with sufficient physiological mode of action data we can look for patterns, and from those patterns infer general rules, theory and models.

Evaluating parameter availability for physiologically based pharmacokinetic (PBPK) modeling of perfluorooctanoic acid (PFOA) in zebrafish

Physiologically based pharmacokinetic (PBPK) models are considered useful tools to describe the absorption, distribution, metabolism and excretion of xenobiotics. For accurate predictions, PBPK models require species-specific and compound-specific parameters. Zebrafish are considered an appropriate vertebrate model for investigating the toxicity of a wide variety of compounds. However, no specific mechanistic model exists for the pharmacokinetics of perfluoroalkyl acids (PFAAs) in zebrafish, despite growing concern about this class of ubiquitous environmental contaminants. The purpose of this study was to evaluate the current state of knowledge for the parameters that would be needed to construct such a model for zebrafish. We chose perfluorooctanoic acid (PFOA) as a model PFAA with greater data availability. We have updated a previous PBPK model for rainbow trout to simulate PFOA fate in zebrafish following waterborne exposure. For the first time, the model considers hepatobiliary circulation. In order to evaluate the availability of parameters to implement this model, we performed an extensive literature review to find zebrafish-specific parameters. As in previous approaches, we broadened our search to include mammalian and other fish studies when zebrafish-specific data were lacking. Based on the method used to measure or estimate parameters, or based on their species-specific origin, we scored and ranked the quality of available parameters. These scores were then used in Monte Carlo and partial rank correlation analyses to identify the most critical data gaps. The liver, where fatty acid binding proteins (FABPs) and plasma proteins are considered, represented the best model-data agreement. Lack of agreement in other tissues suggest better parameters are needed. The results of our study highlight the lack of zebrafish-specific parameters. Based on sensitivity and uncertainty analysis, parameters associated with PFAA-protein interactions and passive diffusion need further refinement to enable development of predictive models for these emerging chemicals in zebrafish.

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.

Blockage of androgen and administration of estrogen induce transdifferentiation of testis into ovary

Induction of sex reversal of XY fish has been restricted to the sex undifferentiated period. In the present study, differentiated XY tilapia were treated with trilostane (TR), metopirone (MN) and glycyrrhetinic acid (GA) (inhibitor of 3β-HSD, Cyp11b2 and 11β-HSD, respectively) alone or in combination with 17β-estradiol (E2) from 30 to 90 dah (days after hatching). At 180 dah, E2 alone resulted in 8.3%, and TR, MN and GA alone resulted in no secondary sex reversal (SSR), whereas TR + E2, MN + E2 and GA + E2 resulted in 88.3, 60.0 and 46.7% of SSR, respectively. This sex reversal could be rescued by simultaneous administration of 11-ketotestosterone (11-KT). Compared with the control XY fish, decreased serum 11-KT and increased E2 level were detected in SSR fish. Immunohistochemistry analyses revealed that Cyp19a1a, Cyp11b2 and Dmrt1 were expressed in the gonads of GA + E2, MN + E2 and TR + E2 SSR XY fish at 90 dah, but only Cyp19a1a was expressed at 180 dah. When the treatment was applied from 60 to 120 dah, TR + E2 resulted in 3.3% of SSR, MN + E2 and GA + E2 resulted in no SSR. These results demonstrated that once 11-KT was synthesized, it could antagonize E2-induced male-to-female SSR, which could be abolished by simultaneous treatment with the inhibitor of steroidogenic enzymes. The upper the enzyme was located in the steroidogenic pathway, the higher SSR rate was achieved when it was inhibited as some of the precursors, such as androstenedione, testosterone and 5α-dihydrotestosterone, could act as androgens. These results highlight the key role of androgen in male sex maintenance.

Perspectives for integrating human and environmental exposure assessments

Integrated Risk Assessment (IRA) has been defined by the EU FP7 HEROIC Coordination action as "the mutual exploitation of Environmental Risk Assessment for Human Health Risk Assessment and vice versa in order to coherently and more efficiently characterize an overall risk to humans and the environment for better informing the risk analysis process" (Wilks et al., 2015). Since exposure assessment and hazard characterization are the pillars of risk assessment, integrating Environmental Exposure assessment (EEA) and Human Exposure assessment (HEA) is a major component of an IRA framework. EEA and HEA typically pursue different targets, protection goals and timeframe. However, human and wildlife species also share the same environment and they similarly inhale air and ingest water and food through often similar overlapping pathways of exposure. Fate models used in EEA and HEA to predict the chemicals distribution among physical and biological media are essentially based on common properties of chemicals, and internal concentration estimations are largely based on inter-species (i.e. biota-to-human) extrapolations. Also, both EEA and HEA are challenged by increasing scientific complexity and resources constraints. Altogether, these points create the need for a better exploitation of all currently existing data, experimental approaches and modeling tools and it is assumed that a more integrated approach of both EEA and HEA may be part of the solution. Based on the outcome of an Expert Workshop on Extrapolations in Integrated Exposure Assessment organized by the HEROIC project in January 2014, this paper identifies perspectives and recommendations to better harmonize and extrapolate exposure assessment data, models and methods between Human Health and Environmental Risk Assessments to support the further development and promotion of the concept of IRA. Ultimately, these recommendations may feed into guidance showing when and how to apply IRA in the regulatory decision-making process for chemicals.

The pros and cons of ecological risk assessment based on data from different levels of biological organization

Ecological risk assessment (ERA) is the process used to evaluate the safety of manufactured chemicals to the environment. Here we review the pros and cons of ERA across levels of biological organization, including suborganismal (e.g., biomarkers), individual, population, community, ecosystem and landscapes levels. Our review revealed that level of biological organization is often related negatively with ease at assessing cause-effect relationships, ease of high-throughput screening of large numbers of chemicals (it is especially easier for suborganismal endpoints), and uncertainty of the ERA because low levels of biological organization tend to have a large distance between their measurement (what is quantified) and assessment endpoints (what is to be protected). In contrast, level of biological organization is often related positively with sensitivity to important negative and positive feedbacks and context dependencies within biological systems, and ease at capturing recovery from adverse contaminant effects. Some endpoints did not show obvious trends across levels of biological organization, such as the use of vertebrate animals in chemical testing and ease at screening large numbers of species, and other factors lacked sufficient data across levels of biological organization, such as repeatability, variability, cost per study and cost per species of effects assessment, the latter of which might be a more defensible way to compare costs of ERAs than cost per study. To compensate for weaknesses of ERA at any particular level of biological organization, we also review mathematical modeling approaches commonly used to extrapolate effects across levels of organization. Finally, we provide recommendations for next generation ERA, submitting that if there is an ideal level of biological organization to conduct ERA, it will only emerge if ERA is approached simultaneously from the bottom of biological organization up as well as from the top down, all while employing mathematical modeling approaches where possible to enhance ERA. Because top-down ERA is unconventional, we also offer some suggestions for how it might be implemented efficaciously. We hope this review helps researchers in the field of ERA fill key information gaps and helps risk assessors identify the best levels of biological organization to conduct ERAs with differing goals.

A Computational Model of the Rainbow Trout Hypothalamus-Pituitary-Ovary-Liver Axis

Reproduction in fishes and other vertebrates represents the timely coordination of many endocrine factors that culminate in the production of mature, viable gametes. In recent years there has been rapid growth in understanding fish reproductive biology, which has been motivated in part by recognition of the potential effects that climate change, habitat destruction and contaminant exposure can have on natural and cultured fish populations. New approaches to understanding the impacts of these stressors are being developed that require a systems biology approach with more biologically accurate and detailed mathematical models. We have developed a multi-scale mathematical model of the female rainbow trout hypothalamus-pituitary-ovary-liver axis to use as a tool to help understand the functioning of the system and for extrapolation of laboratory findings of stressor impacts on specific components of the axis. The model describes the essential endocrine components of the female rainbow trout reproductive axis. The model also describes the stage specific growth of maturing oocytes within the ovary and permits the presence of sub-populations of oocytes at different stages of development. Model formulation and parametrization was largely based on previously published in vivo and in vitro data in rainbow trout and new data on the synthesis of gonadotropins in the pituitary. Model predictions were validated against several previously published data sets for annual changes in gonadotropins and estradiol in rainbow trout. Estimates of select model parameters can be obtained from in vitro assays using either quantitative (direct estimation of rate constants) or qualitative (relative change from control values) approaches. This is an important aspect of mathematical models as in vitro, cell-based assays are expected to provide the bulk of experimental data for future risk assessments and will require quantitative physiological models to extrapolate across biological scales.

Reproduction in fishes and other vertebrates represents the timely coordination of many endocrine factors that culminate in the production of mature, viable gametes. Improving the ability to estimate reproductive performance in fish is important, due to the growth of the aquaculture industry and the need to maintain adequate broodstock and concerns over the effects of anthropogenic stressors on feral fish populations. We present here a quantitative, mathematical model of the female rainbow trout reproductive cycle. We show how the model is able to accurately describe experimentally measured data associated with pituitary, ovarian and liver reproductive performance. We also use the model to describe similar data sets collected in rainbow trout by other researchers. An important value of quantitative biological models is the ability to simulate various physiological conditions, real or hypothetical. We demonstrate this by predicting the effects of exposure to an endocrine disruptor on oocyte growth. The need to limit cost and animal usage will encourage future experimental studies to use in vitro methods. The model presented here can assist with the extrapolation of in vitro effects to the whole fish.

Integrated analysis of toxicity data of two pharmaceutical immunosuppressants and two environmental pollutants with immunomodulating properties to improve the understanding of side effects-A toxicopathologist׳s view

Data in a toxicity test are evaluated generally per parameter. Information on the response per animal in addition to per parameter can improve the evaluation of the results. The results from the six studies in rats, described in the paper by Kemmerling, J., Fehlert, E., Rühl-Fehlert, C., Kuper, C.F., Stropp, G., Vogels, J., Krul, C., Vohr, H.-W., 2015. The transferability from rat subacute 4-week oral toxicity study to translational research exemplified by two pharmaceutical immunosuppressants and two environmental pollutants with immunomodulating properties (In this issue), have been subjected to principal component analysis (PCA) and principal component discriminant analysis (PC-DA). The two pharmaceuticals azathioprine (AZA) and cyclosporine A (CSA) and the two environmental pollutants hexachlorobenzene (HCB) and benzo(a)pyrene (BaP) all modulate the immune system, albeit that their mode of immunomodulation is quite diverse. PCA illustrated the similarities between the two independent studies with AZA (AZA1 and AZA2) and CSA (CSA1 and CSA2). The PC-DA on data of the AZA2 study did not increase substantially the information on dose levels. In general, the no-effect levels were lower upon single parameter analysis than indicated by the distances between the dose groups in the PCA. This was mostly due to the expert judgment in the single parameter evaluation, which took into account outstanding pathology in only one or two animals. The PCA plots did not reveal sex-related differences in sensitivity, but the key pathology for males and females differed. The observed variability in some of the control groups was largely a peripheral blood effect. Most importantly, PCA analysis identified several animals outside the 95% confidence limit indicating high-responders; also low-to-non-responders were identified. The key pathology enhanced the understanding of the response of the animals to the four model compounds.

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.

Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: I. Challenges and research needs in ecotoxicology

To elucidate the effects of chemicals on populations of different species in the environment, efficient testing and modeling approaches are needed that consider multiple stressors and allow reliable extrapolation of responses across species. An adverse outcome pathway (AOP) is a concept that provides a framework for organizing knowledge about the progression of toxicity events across scales of biological organization that lead to adverse outcomes relevant for risk assessment. In this paper, we focus on exploring how the AOP concept can be used to guide research aimed at improving both our understanding of chronic toxicity, including delayed toxicity as well as epigenetic and transgenerational effects of chemicals, and our ability to predict adverse outcomes. A better understanding of the influence of subtle toxicity on individual and population fitness would support a broader integration of sublethal endpoints into risk assessment frameworks. Detailed mechanistic knowledge would facilitate the development of alternative testing methods as well as help prioritize higher tier toxicity testing. We argue that targeted development of AOPs supports both of these aspects by promoting the elucidation of molecular mechanisms and their contribution to relevant toxicity outcomes across biological scales. We further discuss information requirements and challenges in application of AOPs for chemical- and site-specific risk assessment and for extrapolation across species. We provide recommendations for potential extension of the AOP framework to incorporate information on exposure, toxicokinetics and situation-specific ecological contexts, and discuss common interfaces that can be employed to couple AOPs with computational modeling approaches and with evolutionary life history theory. The extended AOP framework can serve as a venue for integration of knowledge derived from various sources, including empirical data as well as molecular, quantitative and evolutionary-based models describing species responses to toxicants. This will allow a more efficient application of AOP knowledge for quantitative chemical- and site-specific risk assessment as well as for extrapolation across species in the future.

Effects of trilostane and fipronil on the reproductive axis in an early life stage of the Japanese medaka (Oryzias latipes)

Given the critical role of the hypothalamic-pituitary-gonadal (HPG) axis, it is conceivable that perturbations at any point along this axis can potentially affect reproduction in fish and other vertebrates. We investigated the effects of a 3β-hydroxysteroid dehydrogenase (3β-HSD) inhibitor, trilostane (TRI), and a gamma-aminobutyric acid (GABA)-receptor antagonist, fipronil (FIP), on the HPG axis using an early life stage of the Japanese medaka. The newly hatched larvae were exposed to TRI (100, 300 and 1000 μg/L) and FIP (3, 10 and 30 μg/L), respectively, until 28 days post-hatching. Exposure to TRI decreased the body length in males, whereas FIP inhibited growth in both sexes. The induction of steroidogenesis-regulating genes (including 3β-hsd) in males exposed to TRI, accompanied by increased vtg and er transcription, indicating a compensatory response to the presumed 3β-HSD inhibition. These compensatory responses were not observed in TRI-treated females. Regarding FIP exposure, the GABA blocker resulted in the down-regulation of fshr and lhr. A compensatory up-regulation of steroidogenesis-regulating genes partially explained the elevated transcripts of vtg genes in both males and females after FIP exposure. These results suggest that both the inhibition of 3β-HSD and the antagonism of GABA receptors are relevant modes of endocrine disruption that could impact the normal regulation of the HPG axis.

Endocrinology: advances through omics and related technologies

The rapid development of new omics technologies to measure changes at genetic, transcriptomic, proteomic, and metabolomics levels together with the evolution of methods to analyze and integrate the data at a systems level are revolutionizing the study of biological processes. Here we discuss how new approaches using omics technologies have expanded our knowledge especially in nontraditional models. Our increasing knowledge of these interactions and evolutionary pathway conservation facilitates the use of nontraditional species, both invertebrate and vertebrate, as new model species for biological and endocrinology research. The increasing availability of technology to create organisms overexpressing key genes in endocrine function allows manipulation of complex regulatory networks such as growth hormone (GH) in transgenic fish where disregulation of GH production to produce larger fish has also permitted exploration of the role that GH plays in testis development, suggesting that it does so through interactions with insulin-like growth factors. The availability of omics tools to monitor changes at nearly any level in any organism, manipulate gene expression and behavior, and integrate data across biological levels, provides novel opportunities to explore endocrine function across many species and understand the complex roles that key genes play in different aspects of the endocrine function.

A physiologically based toxicokinetic model for the zebrafish Danio rerio

Zebrafish (Danio rerio) is a widely used model for toxicological studies, in particular those related to investigations on endocrine disruption. The development and regulatory use of in vivo and in vitro tests based on this species can be enhanced by toxicokinetic modeling. For this reason, we propose a physiologically based toxicokinetic (PBTK) model for zebrafish describing the uptake and disposition of organic chemicals. The model is based on literature data on zebrafish, other cyprinidae and other fish families, new experimental physiological information (volumes, lipids and water contents) obtained from zebrafish, and chemical-specific parameters predicted by generic models. The relevance of available models predicting the latter parameters was evaluated with respect to gill uptake and partition coefficients in zebrafish. This evaluation benefited from the fact that the influence of confounding factors such as body weight and temperature on ventilation rate was included in our model. The predictions for six chemicals (65 data points) yielded by our PBTK model were compared to available toxicokinetics data for zebrafish and 88% of them were within a factor of 5 of the corresponding experimental values. Sensitivity analysis highlighted that the 1-octanol/water partition coefficient, the metabolism rate, and all the parameters that enable the prediction of assimilation efficiency and partitioning of chemicals need to be precisely determined in order to allow an effective toxicokinetic modeling.

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.

Endocrine disruption by di-(2-ethylhexyl)-phthalate in Chinese rare minnow (Gobiocypris rarus)

Great concern has been raised over the potential impact of environmental contaminants on fish populations that inhabit the Three Gorge Reservoir. The present study investigated the endocrine-disrupting effects of di-(2-ethylhexyl)-phthalate (DEHP) on the Chinese rare minnow (Gobiocypris rarus), an endemic fish distributed in upstream waters in the Yangtze River. Adult rare minnow were exposed to environmentally relevant concentrations of DEHP (0 µg/L, 3.6 µg/L, 12.8 µg/L, 39.4 µg/L, and 117.6 µg/L) for a 21-d period. Then, concentrations of sex hormones in the plasma and relative transcription of various associated genes were measured in the hypothalamic-pituitary-gonadal (HPG) axis and liver of the fish. Exposure to DEHP resulted in greater circulating concentrations of testosterone (T) and lower concentrations of estradiol (E2), which were accompanied by upregulation of Cyp17 mRNA and downregulation of Cyp19a mRNA in the gonads of females. In males, increases of T and E2 levels were consistent with upregulation of Cyp17 and Cyp19a in the gonads. Furthermore, the T/E2 ratio was increased in females but reduced in males. A significant increase in the levels of hepatic vitellogenin (VTG) gene transcription was observed in both females and males. The present study showed that waterborne exposure to DEHP altered plasma sex hormone levels and modulated gene transcription profiles of associated genes in the HPG axis and liver, occurring mostly at higher concentrations (>39.4 µg/L), which suggests that environmental concentration of DEHP (5.4 µg/L) alone might not disturb the endocrine system of the rare minnow in the TGR.

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.

Toxicokinetic-toxicodynamic modeling of quantal and graded sublethal endpoints: a brief discussion of concepts

We report on the advantages and problems of using toxicokinetic-toxicodynamic (TKTD) models for the analysis, understanding, and simulation of sublethal effects. Only a few toxicodynamic approaches for sublethal effects are available. These differ in their effect mechanism and emphasis on linkages between endpoints. We discuss how the distinction between quantal and graded endpoints and the type of linkage between endpoints can guide model design and selection. Strengths and limitations of two main approaches and possible ways forward are outlined.

A computational model of the hypothalamic: pituitary: gonadal axis in female fathead minnows (Pimephales promelas) exposed to 17α-ethynylestradiol and 17β-trenbolone

Background

Endocrine disrupting chemicals (e.g., estrogens, androgens and their mimics) are known to affect reproduction in fish. 17α-ethynylestradiol is a synthetic estrogen used in birth control pills. 17β-trenbolone is a relatively stable metabolite of trenbolone acetate, a synthetic androgen used as a growth promoter in livestock. Both 17α-ethynylestradiol and 17β-trenbolone have been found in the aquatic environment and affect fish reproduction. In this study, we developed a physiologically-based computational model for female fathead minnows (FHM, Pimephales promelas), a small fish species used in ecotoxicology, to simulate how estrogens (i.e., 17α-ethynylestradiol) or androgens (i.e., 17β-trenbolone) affect reproductive endpoints such as plasma concentrations of steroid hormones (e.g., 17β-estradiol and testosterone) and vitellogenin (a precursor to egg yolk proteins).

Results

Using Markov Chain Monte Carlo simulations, the model was calibrated with data from unexposed, 17α-ethynylestradiol-exposed, and 17β-trenbolone-exposed FHMs. Four Markov chains were simulated, and the chains for each calibrated model parameter (26 in total) converged within 20,000 iterations. With the converged parameter values, we evaluated the model's predictive ability by simulating a variety of independent experimental data. The model predictions agreed with the experimental data well.

Conclusions

The physiologically-based computational model represents the hypothalamic-pituitary-gonadal axis in adult female FHM robustly. The model is useful to estimate how estrogens (e.g., 17α-ethynylestradiol) or androgens (e.g., 17β-trenbolone) affect plasma concentrations of 17β-estradiol, testosterone and vitellogenin, which are important determinants of fecundity in fish.

Systems biology: leading the revolution in ecotoxicology

The rapid development of new technologies such as transcriptomics, proteomics, and metabolomics (Omics) are changing the way ecotoxicology is practiced. The data deluge has begun with genomes of over 65 different aquatic species that are currently being sequenced, and many times that number with at least some level of transcriptome sequencing. Integrating these top-down methodologies is an essential task in the field of systems biology. Systems biology is a biology-based interdisciplinary field that focuses on complex interactions in biological systems, with the intent to model and discover emergent properties of the system. Recent studies demonstrate that Omics technologies provide valuable insight into ecotoxicity, both in laboratory exposures with model organisms and with animals exposed in the field. However, these approaches require a context of the whole animal and population to be relevant. Powerful approaches using reverse engineering to determine interacting networks of genes, proteins, or biochemical reactions are uncovering unique responses to toxicants. Modeling efforts in aquatic animals are evolving to interrelate the interacting networks of a system and the flow of information linking these elements. Just as is happening in medicine, systems biology approaches that allow the integration of many different scales of interaction and information are already driving a revolution in understanding the impacts of pollutants on aquatic systems.

Defining and modeling known adverse outcome pathways: Domoic acid and neuronal signaling as a case study

An adverse outcome pathway (AOP) is a sequence of key events from a molecular-level initiating event and an ensuing cascade of steps to an adverse outcome with population-level significance. To implement a predictive strategy for ecotoxicology, the multiscale nature of an AOP requires computational models to link salient processes (e.g., in chemical uptake, toxicokinetics, toxicodynamics, and population dynamics). A case study with domoic acid was used to demonstrate strategies and enable generic recommendations for developing computational models in an effort to move toward a toxicity testing paradigm focused on toxicity pathway perturbations applicable to ecological risk assessment. Domoic acid, an algal toxin with adverse effects on both wildlife and humans, is a potent agonist for kainate receptors (ionotropic glutamate receptors whose activation leads to the influx of Na(+) and Ca²(+)). Increased Ca²(+) concentrations result in neuronal excitotoxicity and cell death, primarily in the hippocampus, which produces seizures, impairs learning and memory, and alters behavior in some species. Altered neuronal Ca²(+) is a key process in domoic acid toxicity, which can be evaluated in vitro. Furthermore, results of these assays would be amenable to mechanistic modeling for identifying domoic acid concentrations and Ca²(+) perturbations that are normal, adaptive, or clearly toxic. In vitro assays with outputs amenable to measurement in exposed populations can link in vitro to in vivo conditions, and toxicokinetic information will aid in linking in vitro results to the individual organism. Development of an AOP required an iterative process with three important outcomes: a critically reviewed, stressor-specific AOP; identification of key processes suitable for evaluation with in vitro assays; and strategies for model development.

Predicting chemical impacts on vertebrate endocrine systems

Animals have evolved diverse protective mechanisms for responding to toxic chemicals of both natural and anthropogenic origin. From a governmental regulatory perspective, these protective responses complicate efforts to establish acceptable levels of chemical exposure. To explore this issue, we considered vertebrate endocrine systems as potential targets for environmental contaminants. Using the hypothalamic-pituitary-thyroid (HPT), hypothalamic-pituitary-gonad (HPG), and hypothalamic-pituitary-adrenal (HPA) axes as case examples, we identified features of these systems that allow them to accommodate and recover from chemical insults. In doing so, a distinction was made between effects on adults and those on developing organisms. This distinction was required because endocrine system disruption in early life stages may alter development of organs and organ systems, resulting in permanent changes in phenotypic expression later in life. Risk assessments of chemicals that impact highly regulated systems must consider the dynamics of these systems in relation to complex environmental exposures. A largely unanswered question is whether successful accommodation to a toxic insult exerts a fitness cost on individual animals, resulting in adverse consequences for populations. Mechanistically based mathematical models of endocrine systems provide a means for better understanding accommodation and recovery. In the short term, these models can be used to design experiments and interpret study findings. Over the long term, a set of validated models could be used to extrapolate limited in vitro and in vivo testing data to a broader range of untested chemicals, species, and exposure scenarios. With appropriate modification, Tier 2 assays developed in support of the U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program could be used to assess the potential for accommodation and recovery and inform the development of mechanistically based models.

Fathead minnow steroidogenesis: in silico analyses reveals tradeoffs between nominal target efficacy and robustness to cross-talk

Background

Interpreting proteomic and genomic data is a major challenge in predictive ecotoxicology that can be addressed by a systems biology approach. Mathematical modeling provides an organizational platform to consolidate protein dynamics with possible genomic regulation. Here, a model of ovarian steroidogenesis in the fathead minnow, Pimephales promelas, (FHM) is developed to evaluate possible transcriptional regulation of steroid production observed in microarray studies.

Results

The model was developed from literature sources, integrating key signaling components (G-protein and PKA activation) with their ensuing effect on steroid production. The model properly predicted trajectory behavior of estradiol and testosterone when fish were exposed to fadrozole, a specific aromatase inhibitor, but failed to predict the steroid hormone behavior occurring one week post-exposure as well as the increase in steroid levels when the stressor was removed. In vivo microarray data implicated three modes of regulation which may account for over-production of steroids during a depuration phase (when the stressor is removed): P450 enzyme up-regulation, inhibin down-regulation, and luteinizing hormone receptor up-regulation. Simulation studies and sensitivity analysis were used to evaluate each case as possible source of compensation to endocrine stress.

Conclusions

Simulation studies of the testosterone and estradiol response to regulation observed in microarray data supported the hypothesis that the FHM steroidogenesis network compensated for endocrine stress by modulating the sensitivity of the ovarian network to global cues coming from the hypothalamus and pituitary. Model predictions of luteinizing hormone receptor regulation were consistent with depuration and in vitro data. These results challenge the traditional approach to network elucidation in systems biology. Generally, the most sensitive interactions in a network are targeted for further elucidation but microarray evidence shows that homeostatic regulation of the steroidogenic network is likely maintained by a mildly sensitive interaction. We hypothesize that effective network elucidation must consider both the sensitivity of the target as well as the target's robustness to biological noise (in this case, to cross-talk) when identifying possible points of regulation.