Modeling vitellogenesis in female fish exposed to environmental stressors: predicting the effects of endocrine disturbance due to exposure to a PCB mixture and cadmium

Effects of cadmium on the female reproductive axis of a Neotropical fish

Metals are one of the contaminants released from the increase of anthropic activities. They can be classified as endocrine disruptors once they can affect the reproductive parameters of different organisms. The aim of the study was to evaluate the potential effects of cadmium on regulatory reproduction axis (Hypothalamic-Pituitary-Gonadal-Liver, the HPGL axis) in females of Rhamdia quelen exposed to nominal concentrations of 0.1; 1; 10 and 100 μg.L^-1 of cadmium. After 15 days, tissues were collected for hormonal quantification, brain aromatase (cyp19a1b), hepatic vitellogenin (vtg) gene expression, and biomarkers analysis. Cadmium was quantified in water, gonad and liver samples. The plasma levels of estradiol, testosterone and gonad and hepatosomatic indexes did not changed after Cd exposure. The cyp19a1b was not different among the groups. Cadmium was detected at higher concentrations in the liver compared to the gonads. No genotoxicity was observed, only erythrocytes nuclear alterations. Metallothionein was reduced at 10 μg.L^-1 in the liver and 10 and 100 μg.L^-1 in the gonad. Hepatic superoxide dismutase activity increased and this can lead to a hydrogen peroxide increase, one of reactive oxygen species. This increase without a compensation of other enzymes of the antioxidant system can lead to lipoperoxidation, as occurred at 100 μg.L^-1. Hepatic vitellogenin gene expression increased as well as the injury index at 0,1 and 100 μg.L^-1. The tested cadmium concentrations have been found in the freshwater ecosystems and can affect the female reproductive regulation axis HPGL of the Neotropical species R. quelen.

Computational modelling of the Δ4 and Δ5 adrenal steroidogenic pathways provides insight into hypocortisolism

This study demonstrates the application of a mathematical steroidogenic model, constructed with individual in vitro enzyme characterisations, to simulate in vivo steroidogenesis in a diseased state. This modelling approach was applied to the South African Angora goat, that suffers from hypocortisolism caused by altered adrenal function. These animals are extremely vulnerable to cold stress, leading to substantial monetary loss in the mohair industry. The Angora goat has increased CYP17A1 17,20-lyase enzyme activity in comparison with hardy livestock species. Determining the effect of this altered adrenal function on adrenal steroidogenesis during a cold stress response is difficult. We developed a model describing adrenal steroidogenesis under control conditions, and under altered steroidogenic conditions where the animal suffers from hypocortisolism. The model is parameterised with experimental data from in vitro enzyme characterisations of a hardy control species. The increased 17,20-lyase activity of the Angora goat CYP17A1 enzyme was subsequently incorporated into the model and the response to physiological stress is simulated under both control and altered adrenal steroidogenic conditions.

Effects of cadmium exposure on sperm and larvae of the neotropical fish Prochilodus magdalenae

Cadmium (Cd) is a heavy metal with known deleterious effects on animal reproduction, decreasing the rate of fertilization of organisms such as fish. Prochilodus magdalenae is a very important fish species in Colombia, widely used by riparian communities from many rivers. Unfortunately, its population has been declining, whereas Cd seems to be more frequently detected in environmental matrices at Colombian ecosystems. The aim of this work was to determine the toxic effects of cadmium chloride on fertilization, sperm quality and mortality at 0, 1, 6 and 7 days post-hatching (dph) in this vulnerable species. The results indicated that Cd altered the fertilization and sperm quality by decreasing total motility and rapid and medium motilities of swimming spermatozoa. Results showed Cd produced 16.4 and 46.5% sperm motility inhibition, at 2.5 and 25 ppm, respectively. The heavy metal also impaired sperm curvilinear and straight-line velocities in a concentration-response dose. Cadmium-induced a dose-dependent effect on the mortality of the exposed larvae that depends on its development stage, with greater effects after 6 and 7 dph, observed at concentrations as low as 0.025 ppm. The results showed that the exposure to environmentally relevant Cd concentrations causes physiological changes in the initial stages of development of P. magdalenae, likely increasing the risk of reducing the fertility rate of this valuable fish species.

Heavy metals accumulation and endocrine disruption in Prochilodus argenteus from a polluted neotropical river

Heavy metals are considered major pollutants of aquatic environments due to the difficulty of metabolization and the bioaccumulative potential in tissues of aquatic organisms, especially fish muscle that is often used as food worldwide. In addition to causing cell damage, some metals such as aluminium (Al), cadmium (Cd), copper (Cu), and lead (Pb) can act as endocrine disrupting chemicals in fish. The Paraopeba and Abaete Rivers are important tributaries of the upper São Francisco River basin, but the Paraopeba River receives, along its course, the discharge of many types of effluents that affect fish species, including widely consumed species such as Prochilodus argenteus. This study evaluated histological and molecular changes caused by chronic exposure to heavy metals in P. argenteus from the Paraopeba River and compared this to fish from the non-impacted Abaete River. Sampled fish from both rivers were used in histological analyses and immunohistochemical assays. The results showed increased incidence of histopathologies and changes in number and morphology of germline cells in both sexes. In addition, up-regulated expression of oestrogens-induced proteins in the liver of males were detected in polluted environment. All the alterations were related to the concentration of metals in water and fish. The high concentration of various metals observed in water and fish from Paraopeba River serves as an alert to the environmental and public health regulatory authorities.

Joint effects of chronic exposure to environmentally relevant levels of nonylphenol and cadmium on the reproductive functions in male rockfish Sebastiscus marmoratus

Nonylphenol (NP) and Cadmium (Cd) are two common contaminants that can be detected in aquatic environments. Nevertheless, the combined toxicity of NP and Cd at environmentally relevant concentrations in aquatic organisms has not been thoroughly characterized to date. In the present study, the interactions between NP and Cd on male Sebastiscus marmoratus were studied. After 21 days of exposure, the brain aromatase activity was observed to be significantly induced by 100 ng/L NP and 40 μg/L Cd, whereas all of the concentrations of co-treatment resulted in an increase in brain aromatase activity. Additionally, NP could also reduce plasma testosterone concentration, while NP, Cd and their mixture could induce plasma 17β-estradiol (E2) concentration and VTG concentration. The interactions between NP and Cd on the reproductive physiology were antagonism. Our results also support the notion of using these indicators as biomarkers for exposure to EDCs and further extend the boundary of biomonitoring to environmental levels.

RNA-sequencing to assess the health of wild yellow perch (Perca flavescens) populations from the St. Lawrence River, Canada

This study aimed to better understand in situ cumulative effects of anthropogenic stressors on the health of St. Lawrence River (QC, Canada) yellow perch populations using high-throughput transcriptomics and a multi-biological level approach. Fish were collected in the upstream fluvial Lake Saint-François (LSF) with low degree of environmental perturbations; Lake Saint-Louis (LSL) considered having a moderate degree of anthropogenic stressors, and Lake Saint-Pierre (LSP) a sector where the perch population has been severely declining. Morphometric results indicated that fish from the downstream LSP showed lower body condition compared to LSF and LSL. Liver transcriptomic responses were assessed by RNA-sequencing. Two hundred and eighty genes were over-transcribed in LSP perch while 200 genes were under-transcribed compared to LSF and LSL. In LSP fish, genes transcripts related to reproduction, retinol, iron, thyroid hormones, oxidative stress, lipid metabolism and immune functions were among the most abundant suggesting that multiple metabolic and physiological pathways were impacted by environmental stressors at this site. Inhibition of liver superoxide dismutase, catalase and glutathione S-transferase activities were also observed at the cellular level. Overall, identified impacted biological pathways in perch from LSP may help understand the precarious state of this population and identify the factors inhibiting its recovery.

Female reproductive impacts of dietary methylmercury in yellow perch (Perca flavescens) and zebrafish (Danio rerio)

The purpose of this study was to evaluate the effects of environmentally relevant dietary MeHg exposures on adult female yellow perch (Perca flavescens) and female zebrafish (Danio rerio) ovarian development and reproduction. Yellow perch were used in the study for their socioeconomic and ecological importance within the Great Lakes basin, and the use of zebrafish allowed for a detailed analysis of the molecular effects of MeHg following a whole life-cycle exposure. Chronic whole life dietary exposure of F₁ zebrafish to MeHg mimics realistic wildlife exposure scenarios, and the twenty-week adult yellow perch exposure (where whole life-cycle exposures are difficult) captures early seasonal ovarian development. For both species, target dietary accumulation values were achieved prior to analyses. In zebrafish, several genes involved in reproductive processes were shown to be dysregulated by RNA-sequencing and quantitative real-time polymerase chain reaction (QPCR), but no significant phenotypic changes were observed regarding ovarian staging, fecundity, or embryo mortality. Yellow perch were exposed to dietary MeHg for 12, 16, or 20 weeks. In this species, a set of eight genes were assessed by QPCR in the pituitary, liver, and ovary, and no exposure-related changes were observed. The lack of genomic resources in yellow perch hinders the characterization of subtle molecular impacts. The ovarian somatic index, circulating estradiol and testosterone, and ovarian staging were not significantly altered by MeHg exposure in yellow perch. These results suggest that environmentally relevant MeHg exposures do not drastically reduce the reproductively important endpoints in these fish, but to capture realistic exposure scenarios, whole life-cycle yellow perch exposures are needed.

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.

Next-generation ecological risk assessment: Predicting risk from molecular initiation to ecosystem service delivery

Ecological risk assessment is the process of evaluating how likely it is that the environment may be impacted as the result of exposure to one or more chemicals and/or other stressors. It is not playing as large a role in environmental management decisions as it should be. A core challenge is that risk assessments often do not relate directly or transparently to protection goals. There have been exciting developments in in vitro testing and high-throughput systems that measure responses to chemicals at molecular and biochemical levels of organization, but the linkage between such responses and impacts of regulatory significance - whole organisms, populations, communities, and ecosystems - are not easily predictable. This article describes some recent developments that are directed at bridging this gap and providing more predictive models that can make robust links between what we typically measure in risk assessments and what we aim to protect.

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.

Ecotoxicological assessment of solar cell leachates: Copper indium gallium selenide (CIGS) cells show higher activity than organic photovoltaic (OPV) cells

Despite the increasing use of photovoltaics their potential environmental risks are poorly understood. Here, we compared ecotoxicological effects of two thin-film photovoltaics: established copper indium gallium selenide (CIGS) and organic photovoltaic (OPV) cells. Leachates were produced by exposing photovoltaics to UV light, physical damage, and exposure to environmentally relevant model waters, representing mesotrophic lake water, acidic rain, and seawater. CIGS cell leachates contained 583 μg L(-1) molybdenum at lake water, whereas at acidic rain and seawater conditions, iron, copper, zinc, molybdenum, cadmium, silver, and tin were present up to 7219 μg L(-1). From OPV, copper (14 μg L(-1)), zinc (87 μg L(-1)) and silver (78 μg L(-1)) leached. Zebrafish embryos were exposed until 120 h post-fertilization to these extracts. CIGS leachates produced under acidic rain, as well as CIGS and OPV leachates produced under seawater conditions resulted in a marked hatching delay and increase in heart edema. Depending on model water and solar cell, transcriptional alterations occurred in genes involved in oxidative stress (cat), hormonal activity (vtg1, ar), metallothionein (mt2), ER stress (bip, chop), and apoptosis (casp9). The effects were dependent on the concentrations of cationic metals in leachates. Addition of ethylenediaminetetraacetic acid protected zebrafish embryos from morphological and molecular effects. Our study suggests that metals leaching from damaged CIGS cells, may pose a potential environmental risk.

Predicting Fecundity of Fathead Minnows (Pimephales promelas) Exposed to Endocrine-Disrupting Chemicals Using a MATLAB®-Based Model of Oocyte Growth Dynamics

Fish spawning is often used as an integrated measure of reproductive toxicity, and an indicator of aquatic ecosystem health in the context of forecasting potential population-level effects considered important for ecological risk assessment. Consequently, there is a need for flexible, widely-applicable, biologically-based models that can predict changes in fecundity in response to chemical exposures, based on readily measured biochemical endpoints, such as plasma vitellogenin (VTG) concentrations, as input parameters. Herein we describe a MATLAB® version of an oocyte growth dynamics model for fathead minnows (Pimephales promelas) with a graphical user interface based upon a previously published model developed with MCSim software and evaluated with data from fathead minnows exposed to an androgenic chemical, 17β-trenbolone. We extended the evaluation of our new model to include six chemicals that inhibit enzymes involved in steroid biosynthesis: fadrozole, ketoconazole, propiconazole, prochloraz, fenarimol, and trilostane. In addition, for unexposed fathead minnows from group spawning design studies, and those exposed to the six chemicals, we evaluated whether the model is capable of predicting the average number of eggs per spawn and the average number of spawns per female, which was not evaluated previously. The new model is significantly improved in terms of ease of use, platform independence, and utility for providing output in a format that can be used as input into a population dynamics model. Model-predicted minimum and maximum cumulative fecundity over time encompassed the observed data for fadrozole and most propiconazole, prochloraz, fenarimol and trilostane treatments, but did not consistently replicate results from ketoconazole treatments. For average fecundity (eggs•female(-1)•day(-1)), eggs per spawn, and the number of spawns per female, the range of model-predicted values generally encompassed the experimentally observed values. Overall, we found that the model predicts reproduction metrics robustly and its predictions capture the variability in the experimentally observed data.

Relating suborganismal processes to ecotoxicological and population level endpoints using a bioenergetic model

Ecological effects of environmental stressors are commonly evaluated using organismal or suborganismal data, such as standardized toxicity tests that characterize responses of individuals (e.g., mortality and reproduction) and a rapidly growing body of "omics" data. A key challenge for environmental risk assessment is relating such information to population dynamics. One approach uses dynamic energy budget (DEB) models that relate growth and reproduction of individuals to underlying flows of energy and elemental matter. We hypothesize that suborganismal information identifies DEB parameters that are most likely impacted by a particular stressor and that the DEB model can then project suborganismal effects on life history and population endpoints. We formulate and parameterize a model of growth and reproduction for the water flea Daphnia magna. Our model resembles previous generic bioenergetic models, but has explicit representation of discrete molts, an important feature of Daphnia life history. We test its ability to predict six endpoints commonly used in chronic toxicity studies in specified food environments. With just one adjustable parameter, the model successfully predicts growth and reproduction of individuals from a wide array of experiments performed in multiple laboratories using different clones of D. magna raised on different food sources. Fecundity is the most sensitive endpoint, and there is broad correlation between the sensitivities of fecundity and long-run growth rate, as is desirable for the default metric used in chronic toxicity tests. Under some assumptions, we can combine our DEB model with the Euler-Lotka equation to estimate longrun population growth rates at different food levels. A review of Daphnia gene-expression experiments on the effects of contaminant exposure reveals several connections to model parameters, in particular a general trend of increased transcript expression of genes involved in energy assimilation and utilization at concentrations affecting growth and reproduction. The sensitivity of fecundity to many model parameters was consistent with frequent generalized observations of decreased expression of genes involved in reproductive physiology, but interpretation of these observations requires further mechanistic modeling. We thus propose an approach based on generic DEB models incorporating few essential species-specific features for rapid extrapolation of ecotoxicogenomic assays for Daphnia-based population risk assessment.

Linking mechanistic toxicology to population models in forecasting recovery from chemical stress: A case study from Jackfish Bay, Ontario, Canada

Recovery of fish and wildlife populations after stressor mitigation serves as a basis for evaluating remediation success. Unfortunately, effectively monitoring population status on a routine basis can be difficult and costly. In the present study, the authors describe a framework that can be applied in conjunction with field monitoring efforts (e.g., through effects-based monitoring programs) to link chemically induced alterations in molecular and biochemical endpoints to adverse outcomes in whole organisms and populations. The approach employs a simple density-dependent logistic matrix model linked to adverse outcome pathways (AOPs) for reproductive effects in fish. Application of this framework requires a life table for the organism of interest, a measure of carrying capacity for the population of interest, and estimation of the effect of stressors on vital rates of organisms within the study population. The authors demonstrate the framework using linked AOPs and population models parameterized with long-term monitoring data for white sucker (Catostomus commersoni) collected from a study site at Jackfish Bay, Lake Superior, Canada. Individual responses of fish exposed to pulp mill effluent were used to demonstrate the framework's capability to project alterations in population status, both in terms of ongoing impact and subsequent recovery after stressor mitigation associated with process changes at the mill. The general approach demonstrated at the Jackfish Bay site can be applied to characterize population statuses of other species at a variety of impacted sites and can account for effects of multiple stressors (both chemical and nonchemical) and dynamics within complex landscapes (i.e., meta-populations including emigration and immigration processes).

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.

Determining the effects of a mixture of an endocrine disrupting compound, 17α-ethinylestradiol, and ammonia on fathead minnow (Pimephales promelas) reproduction

Aquatic organisms are exposed to a multitude of contaminants and to fully understand the impact of multiple stressors on fish populations, we must first understand the mechanism of action for each toxicant and how the combined effects manifest at the level of the individual. 17α-ethinylestradiol (EE2) has been known to cause adverse reproductive effects including reduced fecundity and fertility, intersex and skewed sex ratios in fish by mimicking naturally produced estrogen at low concentrations. Ammonia can cause adverse reproductive and mortality effects in individual fish through effects or damage to the central nervous system. Both EE2 and ammonia are found in most municipal effluents in various concentrations. A flow-through diluter system was used to test the individual effects of these two contaminants at their respective no observable adverse effect concentration (NOAEC) as well as their combined effects on fathead minnow, (Pimephales promelas) reproduction in a mixture exposure. While neither contaminant nor their mixture altered reproduction in terms of fecundity, their mixture resulted in significant fathead minnow mortality during a 21 d exposure. This study demonstrated the need to consider mixture effects when assessing risk for toxicity testing with multiple stressors.

Vitellogenin-like proteins in the freshwater amphipod Gammarus fossarum (Koch, 1835): functional characterization throughout reproductive process, potential for use as an indicator of oocyte quality and endocrine disruption biomarker in males

This work focused on the validation of biological specificity of the quantitative LC-MS/MS assay by checking the natural variability of Vg levels during the reproductive cycle in Gammarus fossarum (i.e., including oogenesis and embryogenesis). Laboratory tests were performed for 21 days under controlled conditions to assess Vg changes in male and female gammarids after exposure to chemical stress. Females were exposed to two crustacean hormones, 20-hydroxyecdysone (0.01, 1 and 100 μg L⁻¹) and methyl-farnesoate (0.01, 1 and 100 μg L⁻¹). No effect was recorded for 20-hydroxyecdysone, whereas in females exposed to methyl-farnesoate a deleterious impact on Vg production was observed. Males were exposed to crustacean hormones 20-hydroxyecdysone (0.01, 1 and 100 μg L⁻¹) and methyl-farnesoate (0.01, 1 and 100 μg L⁻¹), the insecticide methoxyfenozide (0.001, 0.1 and 10 μg L⁻¹), the fungicide propiconazole (0.001, 0.1, 10 and 1000 μg L⁻¹), and the pharmaceutical products benzophenone, carbamazepine, cyproterone, and R-propranolol (0.001, 0.1, 10 and 1000 μg L⁻¹). Induction of Vg synthesis was recorded in males exposed to cyproterone, methoxyfenozide, methyl-farnesoate, and propiconazole. Finally, we validated the function of the ILIPGVGK peptide used to track vitellogenin in G. fossarum across reproductive processes (vitellogenesis and embryogenesis), and results confirmed the energy reserve role of Vg during embryo development. We show that oocyte surface measurement is directly related to Vg levels in the oocyte, constituting a reliable indicator of egg quality in G. fossarum. Consequently, it could be used as a reliable tool for biomonitoring programs. We recorded induction of Vg in male G. fossarum; however, the possible use of this tool as a specific biomarker of exposure to endocrine disruption should be confirmed in further studies.

Constraints-based stoichiometric analysis of hypoxic stress on steroidogenesis in fathead minnows, Pimephales promelas

In this study, an in silico genome-scale metabolic model of steroidogenesis was used to investigate the effects of hypoxic stress on steroid hormone productions in fish. Adult female fathead minnows (Pimephales promelas) were exposed to hypoxia for 7 days with fish sub-sampled on days 1, 3 and 7 of exposure. At each time point, selected steroid enzyme gene expressions and steroid hormone productions were quantified in ovaries. Fold changes in steroid enzyme gene expressions were used to qualitatively scale transcript enzyme reaction constraints (akin to the range of an enzyme’s catalytic activity) in the in silico model. Subsequently, in silico predicted steroid hormone productions were qualitatively compared with experimental results. Key findings were as follows. (1) In silico gene deletion analysis identified highly conserved ‘essential’ genes required for steroid hormone productions. These agreed well (75%) with literature-published genes downregulated in vertebrates (fish and mammal) exposed to hypoxia. (2) Quantification of steroid hormones produced ex vivo from ovaries showed a significant reduction for 17β-estradiol and 17α,20β-dihydroxypregnenone production after 24 h (day 1) of exposure. This lowered 17β-estradiol production was concomitant with downregulation of cyp19a1a gene expression in ovaries. In silico predictions showed agreement with experimentation by predicting effects on estrogen (17β-estradiol and estrone) production. (3) Stochastic sampling of in silico reactions indicated that cholesterol uptake and catalysis to pregnenolone along with estrogen methyltransferase and glucuronidation reactions were also impacted by hypoxia. Taken together, this in silico analysis introduces a powerful model for pathway analysis that can lend insights on the effects of various stressor scenarios on metabolic functions.

Determining the effects of ammonia on fathead minnow (Pimephales promelas) reproduction

Ammonia can cause adverse reproductive and mortality effects in individual fish by interacting with the central nervous system. The last published study that assessed the effects of ammonia on fathead minnow reproduction was a lifecycle study conducted in 1986. Our study's main goal was to re-evaluate ammonia toxicity on fathead minnow Pimephales promelas reproduction using a 20-day fecundity flow-through diluter method. Flow-through diluter systems have been used by regulatory agencies, such as the U.S. Environmental Protection Agency, in the past as an effective way to estimate acceptable levels of contaminants. There was a significant difference in cumulative egg production among treatments (ANOVA; F=10.167, p≤0.01, df=3). All three concentrations of ammonia tested in this study significantly reduced fecundity after 20days of exposure (Dunnett's, p≤0.05 for each treatment). The lowest un-ionized ammonia concentration (0.06mg/L at a pH of 7.3 and temperature of 25.1°C) tested during this study resulted in a 29% decrease in cumulative fecundity. Because all tested ammonia concentrations caused an effect on P. promelas reproduction, the no effect concentration was estimated to be 0.025mg/L un-ionized ammonia (2.19mg/L total ammonia-nitrogen). This estimate was determined using the U.S. EPA Toxicity Relationship Analysis Program to calculate the 10% effect concentration of ammonia on P. promelas reproduction. This value is much lower than the previous reported no effect concentration on P. promelas reproduction (0.37mg/L un-ionized ammonia or 6.43mg/L total ammonia-nitrogen) as determined from the 1986 study, which was used to determine the ammonia water quality criteria by the U.S. Environmental Protection Agency. Our results should be considered in the next revision of water quality criteria.

A CONSTRAINT-BASED STOICHIOMETRIC MODEL OF THE STEROIDOGENIC NETWORK OF ZEBRAFISH (DANIO RERIO)

The metabolic process of steroidogenesis exhibits a complex biochemical network topology as the activity of various steroidogenic enzymes control cholesterol metabolism to steroid hormone derivatives. In this paper, a stoichiometric reconstruction of a sub-set of 65 reactions from the zebrafish (Danio rerio) steroidogenic network is presented and simulated using uniform reaction constraints. The reconstruction defined a set of 65 enzyme catalyzed reactions and 37 exchange or transport reactions for steroid metabolites. The reconstructed reactions were inclusive of cholesterol and androgen/estrogen metabolism. Biased (statement of network objective function) and un-biased (no statement of objective function) analyses were applied to identify network properties dependent on reaction stoichiometry. Random sampling of flux distributions through the network identified highly-correlated reaction sets that corresponded to the catalysis of steroid metabolites of physiological relevance. Subsequently, optimal flux distributions through network pathways were determined for the production of the three steroidogenic metabolites of: 11-deoxycorticosterone, testosterone and 17β-estradiol. Furthermore, flux variability analyses revealed and confirmed optimal network fluxes through physiologically feasible pathways. The stoichiometric dependence of reactions was also confirmed by conducting deletions of reactions utilized for the optimal production of 17β-estradiol. This paper demonstrates the potential application of constraint-based reconstruction and simulation techniques in enabling the construction of deterministic and predictive physiological models. This acknowledgement is poignant considering the susceptibility of the steroidogenic network to environmental and anthropogenic stressors.

Accumulation of heavy metals to assess the health status of swordfish in a comparative analysis of Mediterranean and Atlantic areas

During the last few decades, the combined effects of natural and human activities acting on the Mediterranean Sea basin have caused a reduction in the swordfish (Xiphias gladius, L. 1758) population. In this project, we investigated the accumulation of lead (Pb), cadmium (Cd) and mercury (Hg) levels in the Atlantic and Mediterranean populations of swordfish during a five-year survey. In the marine environment, top predators such as swordfish accumulate high concentrations of toxic metals, and thus, potentially incur a high toxicological risk. Furthermore, heavy metals, such as chemical pollutants, have strong long-term effects on fish, and thus, constitute a high risk for the resource and humans that consume it. The aim of this work is to contribute to the assessment of the state of European swordfish population health. We analyzed muscle tissue from 56 specimens captured in Mediterranean and Atlantic areas for trace elements. Mean concentrations of Hg, Cd, and Pb were in the following ranges: 0.66-2.41, 0.04-0.16, and 0.97-1.36 mg/kg ww, respectively. These data suggest a need for continuous monitoring to avoid reductions in the population of this fish species of high commercial and ecological interest.

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.

Molecular characterization of estrogen receptor genes in Gobiocypris rarus and their expression upon endocrine disrupting chemicals exposure in juveniles

Estrogens play an important role in many physiological processes of vertebrates, mediated by estrogen receptors (ERs). The full length of the cDNAs for ERα, ERβ1, and ERβ2 were isolated and characterized from Gobiocypris rarus. G. rarus ERs shared the highest amino acid identities with counterparts of three cyprinidae species (Pimephales promelas ERα: 91.1%, Rutilus rutilus ERβ1: 92.9%, Tanichthy albonubes ERβ2: 93.5%). The phylogenic tree of vertebrate ERs indicates G. rarus ER isoforms are more related to counterparts of cyprinidae species. The expression of ERα mRNA was high in gonad and liver. The ERβ1 transcript was the highest in the liver of female fish and was evenly high in the liver, testis and intestine in male. The ERβ2 transcript was high in liver, gonad, and intestine. G. rarus juvenile at 34 days post fertilization were exposed for 3 days to endocrine disrupting chemicals including 17α-ethynylestradiol (EE2), 4-nonylphenol (NP) and bisphenol A (BPA). ER mRNA expression following the xenoestrogens' exposure was analyzed by quantitative real-time PCR. EE2 exposure at 0.01, 0.1 and 1 nM significantly up-regulated ERα transcript. ERβ1 mRNA expression was suppressed by EE2 at all concentrations. However ERβ2 transcript had opposite response to EE2 at low and high concentrations (up-regulation at 0.1 nM, down-regulation at 1 nM). Except a weak increase of ERα at 10 nM EE2, varying decrease of three ER transcripts was resulted in by NP at 10, 100 and 1000 nM. ERα transcript was significantly up-regulated by BPA at 10 nM. A non-significant weak increase in ERβ1 mRNA expression was caused by 1 nM BPA. However 1 nM and 10 nM BPA exposures resulted in significant and non-significant decrease of ERβ2 transcript, respectively. The BPA exposures at other concentrations almost had no effect on the ER transcripts. Vitellogenin (Vtg) mRNA expression profiling following exposure to three xenoestrogens indicated that Vtg transcript is a sensitive biomarker of the juvenile G. rarus at 34 dpf to the EDCs, especially to EE2. These results combined suggest that the ER genes are not modulated in the same manner by EE2, NP, and BPA and that ERs may not contribute equally to the transcriptional regulation of genes involved in fish development and reproduction.

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.

Adverse outcome pathways and ecological risk assessment: bridging to population-level effects

Maintaining the viability of populations of plants and animals is a key focus for environmental regulation. Population-level responses integrate the cumulative effects of chemical stressors on individuals as those individuals interact with and are affected by their conspecifics, competitors, predators, prey, habitat, and other biotic and abiotic factors. Models of population-level effects of contaminants can integrate information from lower levels of biological organization and feed that information into higher-level community and ecosystem models. As individual-level endpoints are used to predict population responses, this requires that biological responses at lower levels of organization be translated into a form that is usable by the population modeler. In the current study, we describe how mechanistic data, as captured in adverse outcome pathways (AOPs), can be translated into modeling focused on population-level risk assessments. First, we describe the regulatory context surrounding population modeling, risk assessment and the emerging role of AOPs. Then we present a succinct overview of different approaches to population modeling and discuss the types of data needed for these models. We describe how different key biological processes measured at the level of the individual serve as the linkage, or bridge, between AOPs and predictions of population status, including consideration of community-level interactions and genetic adaptation. Several case examples illustrate the potential for use of AOPs in population modeling and predictive ecotoxicology. Finally, we make recommendations for focusing toxicity studies to produce the quantitative data needed to define AOPs and to facilitate their incorporation into population modeling.

Dual effects of daidzein on chicken hepatic vitellogenin II expression and estrogen receptor-mediated transactivation in vitro

Two in vitro systems were employed to delineate the estrogenic activity of daidzein (Da), alone or in combination with high or low concentrations of estrogen in two cell types possessing different estrogen-receptor (ER) isoforms, ERalpha and/or ERbeta: (1) vitellogenin II (VTG), the egg yolk precursor protein and the endpoint biomarker for estrogenicity, in chicken primary hepatocytes, and (2) CHO-K1 cells transiently co-transfected with ERalpha or ERbeta and estrogen-response elements (ERE) linked to a luciferase reporter gene. Da (100 microM) alone induced VTG mRNA expression in chicken hepatocytes, albeit with much less potency compared to estradiol (E(2)). Da exhibited different effects in the presence of 1 microM and 10 microM E(2). At a concentration of 100 microM, Da enhanced 1 microM E(2)-induced VTG transcription by 2.4-fold, but significantly inhibited 10 microM E(2)-induced VTG mRNA expression in a dose-dependent fashion from 1 to 100 microM. Tamoxifen completely blocked the estrogenic effect of daidzein, alone or in combination with 1 microM of E(2), but did not influence its anti-estrogenic effect on 10 microM E(2)-induced VTG mRNA expression. Furthermore, neither E(2) nor daidzein, alone or in combination, affected ERalpha mRNA expression, yet all the treatments significantly up-regulated ERbeta mRNA expression in chicken hepatocytes. E(2) effectively triggered estrogen-response elements (ERE)-driven reporter gene transactivation in CHO-K1 cells expressing ERalpha or ERbeta and showed much greater potency with ERalpha than with ERbeta. In contrast, daidzein was 1000 times more powerful in stimulating ERbeta- over ERalpha-mediated transactivation. Daidzein, in concentrations ranging from 5 nM to 50 microM, did not affect ERbeta-mediated transactivation induced by 1 nM E(2), but it significantly inhibited ERbeta-mediated transactivation induced by 10 nM E(2) at 500 nM. Despite the tremendous difference in sensitivity between the two in vitro systems, daidzein exhibited greater potency as an estrogen-antagonist for ERbeta-mediated activity.

Computational model of steroidogenesis in human H295R cells to predict biochemical response to endocrine-active chemicals: model development for metyrapone

BACKGROUND

An in vitro steroidogenesis assay using the human adrenocortical carcinoma cell line H295R is being evaluated as a possible screening assay to detect and assess the impact of endocrine-active chemicals (EACs) capable of altering steroid biosynthesis. Data interpretation and their quantitative use in human and ecological risk assessments can be enhanced with mechanistic computational models to help define mechanisms of action and improve understanding of intracellular concentration-response behavior.

OBJECTIVES

The goal of this study was to develop a mechanistic computational model of the metabolic network of adrenal steroidogenesis to estimate the synthesis and secretion of adrenal steroids in human H295R cells and their biochemical response to steroidogenesis-disrupting EAC.

METHODS

We developed a deterministic model that describes the biosynthetic pathways for the conversion of cholesterol to adrenal steroids and the kinetics for enzyme inhibition by metryrapone (MET), a model EAC. Using a nonlinear parameter estimation method, the model was fitted to the measurements from an in vitro steroidogenesis assay using H295R cells.

RESULTS

Model-predicted steroid concentrations in cells and culture medium corresponded well to the time-course measurements from control and MET-exposed cells. A sensitivity analysis indicated the parameter uncertainties and identified transport and metabolic processes that most influenced the concentrations of primary adrenal steroids, aldosterone and cortisol.

CONCLUSIONS

Our study demonstrates the feasibility of using a computational model of steroidogenesis to estimate steroid concentrations in vitro. This capability could be useful to help define mechanisms of action for poorly characterized chemicals and mixtures in support of predictive hazard and risk assessments with EACs.

Mechanistic Computational Model of Ovarian Steroidogenesis to Predict Biochemical Responses to Endocrine Active Compounds

Sex steroids, which have an important role in a wide range of physiological and pathological processes, are synthesized primarily in the gonads and adrenal glands through a series of enzyme-mediated reactions. The activity of steroidogenic enzymes can be altered by a variety of endocrine active compounds (EAC), some of which are therapeutics and others that are environmental contaminants. A steady-state computational model of the intraovarian metabolic network was developed to predict the synthesis and secretion of testosterone (T) and estradiol (E2), and their responses to EAC. Model predictions were compared to data from an in vitro steroidogenesis assay with ovary explants from a small fish model, the fathead minnow. Model parameters were estimated using an iterative optimization algorithm. Model-predicted concentrations of T and E2 closely correspond to the time-course data from baseline (control) experiments, and dose-response data from experiments with the EAC, fadrozole (FAD). A sensitivity analysis of the model parameters identified specific transport and metabolic processes that most influence the concentrations of T and E2, which included uptake of cholesterol into the ovary, secretion of androstenedione (AD) from the ovary, and conversions of AD to T, and AD to estrone (E1). The sensitivity analysis also indicated the E1 pathway as the preferred pathway for E2 synthesis, as compared to the T pathway. Our study demonstrates the feasibility of using the steroidogenesis model to predict T and E2 concentrations, in vitro, while reducing model complexity with a steady-state assumption. This capability could be useful for pharmaceutical development and environmental health assessments with EAC.

Vitellogenin gene expression in males of the Antarctic fish Trematomus bernacchii from Terra Nova Bay (Ross Sea): a role for environmental cadmium?

Synthesis of vitellogenin (VTG) in male fish is a widely recognized effect for estrogenic pollutants in temperate environments, while similar investigations are still lacking for Antarctic organisms. In this study, a preliminary characterization of vitellogenin gene expression was performed by RT-PCR in the key species Trematomus bernacchii sampled in different phases of reproductive cycle and food availability. Females exhibited the highest gene expression during the spawning period, but VTG mRNA was always detected also in males; a significant increase of gene expression was observed both in males and females at the end of the feeding season. These results were not fully supported by a differential exposure to phyto- or anthropogenic estrogens during the planctonic cycle; on the other side, the endocrine properties of cadmium, naturally elevated in Terra Nova Bay and increasing during algal bloom, would explain both the presence of VTG mRNA in males and the seasonal changes of gene induction. Laboratory exposures did not reveal short-term estrogenic effects of cadmium while an elevated responsiveness of T. bernacchii was observed toward a classical estrogenic receptor agonist (17beta-estradiol). Different hypotheses were considered to suggest delayed endocrine effects of cadmium, including the early interaction with other cellular detoxification systems or alterations at multiple levels of the hypothalamus-pituitary-gonad-liver axis. Although molecular mechanisms of VTG gene expression in males of T. bernacchii remain unclear, obtained results provide interesting insights on this species which should stimulate future research activities.

Vitellogenin detection in Caiman latirostris (Crocodylia: Alligatoridae): a tool to assess environmental estrogen exposure in wildlife

Environmental pollution with endocrine disrupting compounds (EDCs) has adverse effects on the ecosystem's health. Caiman latirostris are widely distributed in South American aquatic ecosystems. Caimans have physiological and ecological characteristics that make them particularly vulnerable to EDCs exposure and suitable candidate as a sentinel species. Vitellogenin (Vtg) is a yolk pre-cursor protein synthesized by the liver of non-mammalian vertebrates and induced in response to estrogen. Purified plasma Vtg from caimans injected with estradiol-17beta (E2) was used to generate a polyclonal anti-body. Anti-body specificity was assessed using Western blot. The antiserum was also effective in detecting turtle Vtg, exhibiting high cross-reactivity with Vtg from Phrynops hilarii and Trachemys scripta dorbigni. We developed a specific and highly sensitive ELISA for caiman Vtg. This method has a detection limit of 0.1 ng/ml of plasma. The ELISA did not detect Vtg in plasma of non-induced male caimans. Induction of Vtg in male caimans was evaluated in response to one or two (7 days apart) doses of E2. Due to its high sensitivity, ELISA allows to measure the small increases in plasma Vtg after exposure to exogenous estrogen. A priming effect was observed following the second E2 dose, with a tenfold increase in circulating Vtg. Hepatic synthesis was confirmed by immunohistochemistry. The results presented herein suggest that detection of plasma Vtg in male caimans might become a valuable tool in biomonitoring xenoestrogen exposure in a polluted environment.