A predictive data-driven framework for endocrine prioritization: a triazole fungicide case study

Evaluating scientific confidence in the concordance of in vitro and in vivo protective points of departure

To fulfil the promise of reducing reliance on mammalian in vivo laboratory animal studies, new approach methods (NAMs) need to provide a confident basis for regulatory decision-making. However, previous attempts to develop in vitro NAMs-based points of departure (PODs) have yielded mixed results, with PODs from U.S. EPA's ToxCast, for instance, appearing more conservative (protective) but poorly correlated with traditional in vivo studies. Here, we aimed to address this discordance by reducing the heterogeneity of in vivo PODs, accounting for species differences, and enhancing the biological relevance of in vitro PODs. However, we only found improved in vitro-to-in vivo concordance when combining the use of Bayesian model averaging-based benchmark dose modeling for in vivo PODs, allometric scaling for interspecies adjustments, and human-relevant in vitro assays with multiple induced pluripotent stem cell-derived models. Moreover, the available sample size was only 15 chemicals, and the resulting level of concordance was only fair, with correlation coefficients <0.5 and prediction intervals spanning several orders of magnitude. Overall, while this study suggests several ways to enhance concordance and thereby increase scientific confidence in vitro NAMs-based PODs, it also highlights challenges in their predictive accuracy and precision for use in regulatory decision making.

Assessing utility of thyroid in vitro screening assays through comparisons to observed impacts in vivo

To better understand endocrine disruption, the U.S. Environmental Protection Agency's (USEPA) Endocrine Disruptor Screening Program (EDSP) utilizes a two-tiered approach to investigate the potential of a chemical to interact with the estrogen, androgen, or thyroid systems. As in vivo testing lacks the throughput to address data gaps on endocrine bioactivity for thousands of chemicals, in vitro high-throughput screening (HTS) methods are being developed to screen larger chemical libraries. The primary objective of this work was to investigate for how many of the 52 chemicals with weight-of-evidence (WoE) determinations from EDSP Tier 1 screening there are available in vitro HTS data supporting a thyroid impact. HTS data from the USEPA ToxCast program and the EDSP WoE were collected for this analysis. Considering the complexity of endocrine disruption and interpreting HTS data, concordance between in vitro activity and in vivo effects ranges from 58 to 78%. Based on this evaluation, we conclude that the current suite of HTS assays is beneficial for prioritizing chemicals for further inquiry; however, without a more detailed analysis, one cannot conclude whether HTS results are the primary mode-of-action. Furthermore, development of in vitro assays for additional thyroid-relevant molecular initiating events is required to effectively predict in vivo thyroid impacts.

Hazards of current concentration-setting practices in environmental toxicology studies

The setting of concentrations for testing substances in ecotoxicological studies is often based on fractions of the concentrations that cause 50% mortality (LC50 or LD50) rather than environmentally relevant levels. This practice can result in exposures to animals at test concentrations that are magnitudes of order greater than those experienced in the environment. Often, such unrealistically high concentrations may cause non-specific biochemical or morphologic changes that primarily reflect the near-lethal health condition of the animal subjects, as opposed to effects characteristic of the particular test compound. Meanwhile, it is recognized that for many chemicals, the toxicologic mode of action (MOA) responsible for lethality may differ entirely from the MOAs that cause various sublethal effects. One argument for employing excessively high exposure concentrations in sublethal studies is to ensure the generation of positive toxicological effects, which can then be used to establish safety thresholds; however, it is possible that the pressure to produce exposure-related effects may also contribute to false positive outcomes. The purpose of this paper is to explore issues involving some current usages of acute LC50 data in ecotoxicology testing, and to propose an alternative strategy for performing this type of research moving forward. Toward those ends, a brief literature survey was conducted to gain an appreciation of methods that are currently being used to set test concentrations for sublethal definitive studies.

Evaluating structure-based activity in a high-throughput assay for steroid biosynthesis

Data from a high-throughput human adrenocortical carcinoma assay (HT-H295R) for steroid hormone biosynthesis are available for >2000 chemicals in single concentration and 654 chemicals in multi-concentration (mc). Previously, a metric describing the effect size of a chemical on the biosynthesis of 11 hormones was derived using mc data referred to as the maximum mean Mahalanobis distance (maxmMd). However, mc HT-H295R assay data remain unavailable for many chemicals. This work leverages existing HT-H295R assay data by constructing structure-activity relationships to make predictions for data-poor chemicals, including: (1) identification of individual structural descriptors, known as ToxPrint chemotypes, associated with increased odds of affecting estrogen or androgen synthesis; (2) a random forest (RF) classifier using physicochemical property descriptors to predict HT-H295R maxmMd binary (positive or negative) outcomes; and, (3) a local approach to predict maxmMd binary outcomes using nearest neighbors (NNs) based on two types of chemical fingerprints (chemotype or Morgan). Individual chemotypes demonstrated high specificity (85-98%) for modulators of estrogen and androgen synthesis but with low sensitivity. The best RF model for maxmMd classification included 13 predicted physicochemical descriptors, yielding a balanced accuracy (BA) of 71% with only modest improvement when hundreds of structural features were added. The best two NN models for binary maxmMd prediction demonstrated BAs of 85 and 81% using chemotype and Morgan fingerprints, respectively. Using an external test set of 6302 chemicals (lacking HT-H295R data), 1241 were identified as putative estrogen and androgen modulators. Combined results across the three classification models (global RF model and two local NN models) predict that 1033 of the 6302 chemicals would be more likely to affect HT-H295R bioactivity. Together, these in silico approaches can efficiently prioritize thousands of untested chemicals for screening to further evaluate their effects on steroid biosynthesis.

A framework for chemical safety assessment incorporating new approach methodologies within REACH

The long-term investment in new approach methodologies (NAMs) within the EU and other parts of the world is beginning to result in an emerging consensus of how to use information from in silico, in vitro and targeted in vivo sources to assess the safety of chemicals. However, this methodology is being adopted very slowly for regulatory purposes. Here, we have developed a framework incorporating in silico, in vitro and in vivo methods designed to meet the requirements of REACH in which both hazard and exposure can be assessed using a tiered approach. The outputs from each tier are classification categories, safe doses, and risk assessments, and progress through the tiers depends on the output from previous tiers. We have exemplified the use of the framework with three examples. The outputs were the same or more conservative than parallel assessments based on conventional studies. The framework allows a transparent and phased introduction of NAMs in chemical safety assessment and enables science-based safety decisions which provide the same level of public health protection using fewer animals, taking less time, and using less financial and expert resource. Furthermore, it would also allow new methods to be incorporated as they develop through continuous selective evolution rather than periodic revolution.

Implementing in vitro bioactivity data to modernize priority setting of chemical inventories

Internationally, there are thousands of existing and newly introduced chemicals in commerce, highlighting the ongoing importance of innovative approaches to identify emerging chemicals of concern. For many chemicals, there is a paucity of hazard and exposure data. Thus, there is a crucial need for efficient and robust approaches to address data gaps and support risk-based prioritization. Several studies have demonstrated the utility of in vitro bioactivity data from the ToxCast program in deriving points of departure (PODs). ToxCast contains data for nearly 1,400 endpoints per chemical, and the bioactivity concentrations, indicative of potential adverse outcomes, can be converted to human-equivalent PODs using high-throughput toxicokinetics (HTTK) modeling. However, data gaps need to be addressed for broader application: the limited chemical space of HTTK and quantitative high-throughput screening data. Here we explore the applicability of in silico models to address these data needs. Specifically, we used ADMET predictor for HTTK predictions and a generalized read-across approach to predict ToxCast bioactivity potency. We applied these models to profile 5,801 chemicals on Canada’s Domestic Substances List (DSL). To evaluate the approach’s performance, bioactivity PODs were compared with in vivo results from the EPA Toxicity Values database for 1,042 DSL chemicals. Comparisons demonstrated that the bioac­tivity PODs, based on ToxCast data or read-across, were conservative for 95% of the chemicals. Comparing bioactivity PODs to human exposure estimates supports the identification of chemicals of potential interest for further work. The bioac­tivity workflow shows promise as a powerful screening tool to support effective triaging of chemical inventories.

Utilizing High-Throughput Screening Data, Integrative Toxicological Prioritization Index Score, and Exposure-Activity Ratios for Chemical Prioritization: A Case Study of Endocrine-Active Pesticides in Food Crops

Endocrine-active chemicals can directly act on nuclear receptors and trigger the disturbances of metabolism and a homeostatic system, which are important risk factors for complicating chronic diseases in humans. The endocrine-active potentials of pesticides acting on estrogen, androgen, and thyroid hormone receptors have been extensively evaluated for pesticides; however, the effects on other receptors are less understood. This study aims to comprehensively characterize and prioritize the endocrine-active pesticides using an exposure-activity ratio (EAR) method and toxicological prioritization index (ToxPi). The aggregate exposure assessment of pesticides was performed using a computational exposure model [stochastic human exposure and dose simulation high-throughput model (SHEDS-HT)]. Minimum in vitro point of departure values were converted to human oral equivalent doses via in vitro-to-in vivo extrapolation. The overall endocrine-disrupting potentials of pesticides were evaluated via 76 assays, representing 11 nuclear receptors. EARs and ToxPi scores were then derived to prioritize 79 pesticides in food. This case study demonstrates that EAR profiling can inform the regulatory agencies for a relevant chemical prioritization, which would direct in-depth health risk assessments in the future.

Tebuconazole induces liver injury coupled with ROS-mediated hepatic metabolism disorder

Tebuconazole, the most widely used fungicide, is reported to cause various environmental problems and have serious health risks in humans. Despite numerous advances in toxicity studies, its internal metabolic process and the underlying mechanisms have not been systemically studied. The present study administered low doses (0.02 g/kg bw and 0.06 g/kg bw) of tebuconazole to C57BL/6 mice in vivo. The high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was developed and validated to analyze the tebuconazole in different organs, and our data revealed that tebuconazole mainly accumulated in the liver and that histopathological damage were exhibited in this organ. Tebuconazole significantly dysregulated phase Ⅰ- and phase II-metabolizing enzymes, ATP-binding cassette (ABC) efflux transporters (Abcc2 and Abcc3) and fatty acid metabolism-related genes (Cdkn1a and Fasn), thereby directly causing liver hypertrophy and steatosis. Importantly, the excessive induction of reactive oxygen species (ROS) and oxidative stress partially accounted for the metabolic abnormalities mediated by tebuconazole. Moreover, these alterations were related to the abnormal transcriptional levels of peroxisome proliferator-activated receptor α (PPAR-α) and liver x receptor α (LXR-α), which were predicted to bind to tebuconazole via hydrogen bonding interactions. The current findings provide new insight into the molecular mechanisms of metabolic abnormalities induced by tebuconazole at low concentration, and are conducive to a better understanding of the environmental risk posed by this fungicide.

Paclobutrazol exposure induces apoptosis and impairs autophagy in hepatocytes via the AMPK/mTOR signaling pathway

Paclobutrazol (PBZ), one of the most widely used plant growth retardants in vegetables, fruits, and traditional Chinese medicine ingredients, exposes people to adverse events. In this study, HepaRG hepatocytes were cultured and exposed to PBZ (360 μM) in vitro to determine its mechanism. Results showed that PBZ exposure inhibited cell viability in a time- and dose-dependent manner and increased the oxidative stress and apoptosis ratio in HepaRG cells. These data revealed that the adenosine monophosphate-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR) has an important role in PBZ-induced cell apoptosis, which is mediated by impaired autophagy and blocked by the AMPK activator. In conclusion, PBZ exposure induces apoptosis and impairs autophagy in hepatocytes via the AMPK/mTOR signaling pathway.

Utility of In Vitro Bioactivity as a Lower Bound Estimate of In Vivo Adverse Effect Levels and in Risk-Based Prioritization

Use of high-throughput, in vitro bioactivity data in setting a point-of-departure (POD) has the potential to accelerate the pace of human health safety evaluation by informing screening-level assessments. The primary objective of this work was to compare PODs based on high-throughput predictions of bioactivity, exposure predictions, and traditional hazard information for 448 chemicals. PODs derived from new approach methodologies (NAMs) were obtained for this comparison using the 50th (PODNAM, 50) and the 95th (PODNAM, 95) percentile credible interval estimates for the steady-state plasma concentration used in in vitro to in vivo extrapolation of administered equivalent doses. Of the 448 substances, 89% had a PODNAM, 95 that was less than the traditional POD (PODtraditional) value. For the 48 substances for which PODtraditional < PODNAM, 95, the PODNAM and PODtraditional were typically within a factor of 10 of each other, and there was an enrichment of chemical structural features associated with organophosphate and carbamate insecticides. When PODtraditional < PODNAM, 95, it did not appear to result from an enrichment of PODtraditional based on a particular study type (eg, developmental, reproductive, and chronic studies). Bioactivity:exposure ratios, useful for identification of substances with potential priority, demonstrated that high-throughput exposure predictions were greater than the PODNAM, 95 for 11 substances. When compared with threshold of toxicological concern (TTC) values, the PODNAM, 95 was greater than the corresponding TTC value 90% of the time. This work demonstrates the feasibility, and continuing challenges, of using in vitro bioactivity as a protective estimate of POD in screening-level assessments via a case study.

Claustral colony founding does not prevent sensitivity to the detrimental effects of azole fungicides on the fecundity of ants

Azole fungicides (benzimidazoles, triazoles and imidazoles) are among the most widely used agrochemicals in the world. Unfortunately, azole fungicides are increasingly recognized for playing the role of endocrine disruptors in non-target organisms. Previously, the fecundity of ants with semi-claustral colony founding was found to be severely decreased in response to field-realistic concentrations of azole fungicides. However, during claustral colony founding, the ant queens do not feed and could therefore be protected against effects of agrochemicals applied during the colony founding. In the present study, we hypothesized that claustral colony founding is associated with a lower risk of oral exposure of ant queens to azole fungicides. We exposed queens of a common farmland ant species with claustral colony founding, Lasius niger, to four azole fungicides (epoxiconazole, flusilazole, prochloraz and thiophanate-methyl) that are commonly used in foliar applications and analyzed the differences in fecundity between fungicide-treated groups and the control water-treated group. We found that oral exposure to all four tested formulations of azole fungicides decreased the fecundity of L. niger queens. The decreases in fecundity ranged from 30.5% (epoxiconazole) to 40.3% (prochloraz), although the concentrations of fungicides used were several times lower than the minimum effective concentrations used to eliminate the target fungi by foliar applications of examined fungicides on various crops. Ants with both claustral and semi-claustral colony founding are highly vulnerable to field-realistic concentrations of azole fungicides that are sprayed in foliar applications. Azole fungicides substantially decrease the fitness of ant queens and may explain part of the recently observed decreases in farmland insect abundance and diversity.

High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures

The ToxCast in vitro screening program has provided concentration-response bioactivity data across more than a thousand assay endpoints for thousands of chemicals found in our environment and commerce. However, most ToxCast screening assays have evaluated individual biological targets in cancer cell lines lacking integrated physiological functionality (such as receptor signaling, metabolism). We evaluated differentiated HepaRGTM cells, a human liver-derived cell model understood to effectively model physiologically relevant hepatic signaling. Expression of 93 gene transcripts was measured by quantitative polymerase chain reaction using Fluidigm 96.96 dynamic arrays in response to 1060 chemicals tested in eight-point concentration-response. A Bayesian framework quantitatively modeled chemical-induced changes in gene expression via six transcription factors including: aryl hydrocarbon receptor, constitutive androstane receptor, pregnane X receptor, farnesoid X receptor, androgen receptor, and peroxisome proliferator-activated receptor alpha. For these chemicals the network model translates transcriptomic data into Bayesian inferences about molecular targets known to activate toxicological adverse outcome pathways. These data also provide new insights into the molecular signaling network of HepaRGTM cell cultures.

Metabolism-Disrupting Chemicals and the Constitutive Androstane Receptor CAR

During the last two decades, the constitutive androstane receptor (CAR; NR1I3) has emerged as a master activator of drug- and xenobiotic-metabolizing enzymes and transporters that govern the clearance of both exogenous and endogenous small molecules. Recent studies indicate that CAR participates, together with other nuclear receptors (NRs) and transcription factors, in regulation of hepatic glucose and lipid metabolism, hepatocyte communication, proliferation and toxicity, and liver tumor development in rodents. Endocrine-disrupting chemicals (EDCs) constitute a wide range of persistent organic compounds that have been associated with aberrations of hormone-dependent physiological processes. Their adverse health effects include metabolic alterations such as diabetes, obesity, and fatty liver disease in animal models and humans exposed to EDCs. As numerous xenobiotics can activate CAR, its role in EDC-elicited adverse metabolic effects has gained much interest. Here, we review the key features and mechanisms of CAR as a xenobiotic-sensing receptor, species differences and selectivity of CAR ligands, contribution of CAR to regulation hepatic metabolism, and evidence for CAR-dependent EDC action therein.

trans-2-Octenal, a single compound of a fungal origin, controls Sclerotium rolfsii, both in vitro and in soil

BACKGROUND

Sclerotium rolfsii is a soil-borne phytopathogenic fungus that causes diseases in economically important crops. Eradication of the fungus is hampered by its wide range of hosts, as well as its capacity to form sclerotia. Recently, we have shown that the endophytic fungus Daldinia cf. concentrica emits biologically active volatile organic compounds (VOCs); we also demonstrated that one VOC, trans-2-octenal, was the most effective against various phytopathogenic fungi. Thus, the aim of this study was to examine the potential of this compound to control hyphae and sclerotia of S. rolfsii, both in vitro and in soil.

RESULTS

We found that in vitro exposure of S. rolfsii mycelium to trans-2-octenal in air fully inhibits and kills the fungus. Elimination of sclerotia viability occurred at the same concentration, but direct contact between the sclerotia and the compound was needed. trans-2-Octenal also affected the viability of both hyphae and sclerotia of S. rolfsii in small pots containing loam soil.

CONCLUSION

We suggest the use of trans-2-octenal as a novel compound to control S. rolfsii. © 2020 Society of Chemical Industry.

KnowTox: pipeline and case study for confident prediction of potential toxic effects of compounds in early phases of development

Risk assessment of newly synthesised chemicals is a prerequisite for regulatory approval. In this context, in silico methods have great potential to reduce time, cost, and ultimately animal testing as they make use of the ever-growing amount of available toxicity data. Here, KnowTox is presented, a novel pipeline that combines three different in silico toxicology approaches to allow for confident prediction of potentially toxic effects of query compounds, i.e. machine learning models for 88 endpoints, alerts for 919 toxic substructures, and computational support for read-across. It is mainly based on the ToxCast dataset, containing after preprocessing a sparse matrix of 7912 compounds tested against 985 endpoints. When applying machine learning models, applicability and reliability of predictions for new chemicals are of utmost importance. Therefore, first, the conformal prediction technique was deployed, comprising an additional calibration step and per definition creating internally valid predictors at a given significance level. Second, to further improve validity and information efficiency, two adaptations are suggested, exemplified at the androgen receptor antagonism endpoint. An absolute increase in validity of 23% on the in-house dataset of 534 compounds could be achieved by introducing KNNRegressor normalisation. This increase in validity comes at the cost of efficiency, which could again be improved by 20% for the initial ToxCast model by balancing the dataset during model training. Finally, the value of the developed pipeline for risk assessment is discussed using two in-house triazole molecules. Compared to a single toxicity prediction method, complementing the outputs of different approaches can have a higher impact on guiding toxicity testing and de-selecting most likely harmful development-candidate compounds early in the development process.

Short-term toxicogenomics as an alternative approach to chronic in vivo studies for derivation of points of departure: A case study in the rat with a triazole fungicide

The derivation of an apical endpoint point of departure (POD) from animal-intensive testing programs has been the traditional cornerstone of human health risk assessment. Replacement of in vivo chronic studies with novel approaches, such as toxicogenomics, holds promise for future alternative testing paradigms that significantly reduce animal testing. We hypothesized that a toxicogenomic POD following a 14 day exposure in the rat would approximate the most sensitive apical endpoint POD derived from a battery of chronic, carcinogenicity, reproduction and endocrine guideline toxicity studies. To test this hypothesis, we utilized myclobutanil, a triazole fungicide, as a model compound. In the 14 day study, male rats were administered 0 (vehicle), 30, 150, or 400 mg/kg/day myclobutanil via oral gavage. Endpoints evaluated included traditional apical, hormone, and liver and testis transcriptomic (whole genome RNA sequencing) data. From the transcriptomic data, liver and testis biological effect POD (BEPOD) values were derived. Myclobutanil exposure for 14 days resulted in increased liver weight, altered serum hormones, liver histopathology, and differential gene expression in liver and testis. The liver and testis BEPODs from the short-term study were 22.2 and 25.4 mg/kg/day, respectively. These BEPODs were approximately an order of magnitude higher than the most sensitive apical POD identified from the two year cancer bioassay based on testis atrophy (1.4 mg/kg/day). This study demonstrates the promise of using a short-term study BEPOD to derive a POD for human health risk assessment while substantially reducing animal testing.

A Case Study with Triazole Fungicides to Explore Practical Application of Next-Generation Hazard Assessment Methods for Human Health

The ongoing developments in chemical risk assessment have led to new concepts building on integration of sophisticated nonanimal models for hazard characterization. Here we explore a pragmatic approach for implementing such concepts, using a case study of three triazole fungicides, namely, flusilazole, propiconazole, and cyproconazole. The strategy applied starts with evaluating the overall level of concern by comparing exposure estimates to toxicological potential, followed by a combination of in silico tools and literature-derived high-throughput screening assays and computational elaborations to obtain insight into potential toxicological mechanisms and targets in the organism. Additionally, some targeted in vitro tests were evaluated for their utility to confirm suspected mechanisms of toxicity and to generate points of departure. Toxicological mechanisms instead of the current "end point-by-end point" approach should guide the selection of methods and assays that constitute a toolbox for next-generation risk assessment. Comparison of the obtained in silico and in vitro results with data from traditional in vivo testing revealed that, overall, nonanimal methods for hazard identification can produce adequate qualitative hazard information for risk assessment. Follow-up studies are needed to further refine the proposed approach, including the composition of the toolbox, toxicokinetics models, and models for exposure assessment.

Establishment of cumulative assessment groups of pesticides for their effects on the thyroid

Cumulative assessment groups of pesticides have been established for two specific effects on the thyroid: firstly hypothyroidism, and secondly parafollicular cell (C-cell) hypertrophy, hyperplasia and neoplasia. Sources of uncertainties resulting from the methodological approach and from the limitations in available data and scientific knowledge have been identified and considered. This report supports the publication of a scientific report on cumulative risk assessment to pesticides affecting the thyroid, in which all uncertainties identified for either the exposure assessment or the establishment of the cumulative assessment groups are incorporated into a consolidated risk characterisation.

Synergistic potential of fenvalerate and triadimefon on endocrine disruption and oxidative stress during rare minnow embryo development

Pyrethroids have been reported to interact synergistically when co-exposed with azoles fungicides in different organisms. In the present study, we investigated the mixture toxicity of fenvalerate (FEN) and triadimefon (TDF) toward embryos of Gobiocypris rarus after 96 h exposure. Results demonstrated that TDF enhanced the acute toxicity of FEN. Exposure to binary mixtures of FEN and TDF resulted in synergistic responses of endocrine disruption by inducing the transcripts of several genes including vtg, erα, erβ1, erβ2, cyp19a, cyp1a, cyp4, cyp11a, gnrh3, gnrhr1a, star, and dmrt1. Furthermore, FEN and TDF mixture increased the VTG level and aromatase activity in rare minnow embryos. FEN and TDF co-exposure also regulated the mRNA of vezf, hsp70, p53, gadd45α, induced the synthesis of ROS and activity of GST, suggesting the synergistic potential of oxidative stress induced by FEN and TDF co-exposure. The results indicated that binary mixtures of FEN and TDF could simultaneously induce endocrine disruption and oxidative stress in a synergistic manner during rare minnow embryo development.

High-Throughput H295R Steroidogenesis Assay: Utility as an Alternative and a Statistical Approach to Characterize Effects on Steroidogenesis

The U.S. Environmental Protection Agency Endocrine Disruptor Screening Program and the Organization for Economic Co-operation and Development (OECD) have used the human adrenocarcinoma (H295R) cell-based assay to predict chemical perturbation of androgen and estrogen production. Recently, a high-throughput H295R (HT-H295R) assay was developed as part of the ToxCast program that includes measurement of 11 hormones, including progestagens, corticosteroids, androgens, and estrogens. To date, 2012 chemicals have been screened at 1 concentration; of these, 656 chemicals have been screened in concentration-response. The objectives of this work were to: (1) develop an integrated analysis of chemical-mediated effects on steroidogenesis in the HT-H295R assay and (2) evaluate whether the HT-H295R assay predicts estrogen and androgen production specifically via comparison with the OECD-validated H295R assay. To support application of HT-H295R assay data to weight-of-evidence and prioritization tasks, a single numeric value based on Mahalanobis distances was computed for 654 chemicals to indicate the magnitude of effects on the synthesis of 11 hormones. The maximum mean Mahalanobis distance (maxmMd) values were high for strong modulators (prochloraz, mifepristone) and lower for moderate modulators (atrazine, molinate). Twenty-five of 28 reference chemicals used for OECD validation were screened in the HT-H295R assay, and produced qualitatively similar results, with accuracies of 0.90/0.75 and 0.81/0.91 for increased/decreased testosterone and estradiol production, respectively. The HT-H295R assay provides robust information regarding estrogen and androgen production, as well as additional hormones. The maxmMd from this integrated analysis may provide a data-driven approach to prioritizing lists of chemicals for putative effects on steroidogenesis.

Toxicological analysis of triadimefon on endocrine disruption and oxidative stress during rare minnow (Gobiocypris rarus) larvae development

Triadimefon (TDF) is a systemic wide-spectrum antifungal compound that is widely used in agriculture to inhibit fungal growth on various crops. Since previous studies focused on the embryo and adult life stages in the investigation of ecological impact, here we investigated the long-term effects of TDF (1, 10, 100 μg/L) on rare minnow during its larvae development. TDF caused an anti-estrogenic effect by decreasing vitellogenin (VTG) and CYP19a mRNA level, and inhibiting the aromatase activity and VTG levels after a 3, 6, 10, or 14-day exposure in rare minnow larvae. TDF also disturbed the endocrine disruption by regulating the transcription of estrogen receptors ERα, ERβ1 and ERβ2, CYP1a, CYP11, CYP17, steroidogenic acute regulator (STAR), doublesex and mab-3 related transcription factor (DMRT1), gonadotropin-releasing hormone (GnRH2), GnRH3, GnRHR1A, and GnRHR1B. Furthermore, TDF induced the accumulation of reactive oxygen species (ROS) and the activity of antioxidant proteins glutathione peroxidase (GPX), superoxide dismutase (SOD), and catalase (CAT), and significantly increased the transcriptions of stress response genes P53, growth arrest and DNA damage-inducible 45 alpha (Gadd45α), and COX1, suggested that TDF might cause oxidative stress during larvae development. The changes in transcript and biological levels represented the potential adaptive or compensatory responses to impaired oxidative stress and endocrine system after TDF exposure in rare minnow during its larvae development.

Endocrine Disruptor Compounds (EDCs) and agriculture: The case of pesticides

A number of pesticides are suspected or proved to act as endocrine disruptor compounds (EDCs). In the present survey of the literature, we try to define the main issues to be considered to classify individual pesticides as EDC or not.

Development and Validation of a Computational Model for Androgen Receptor Activity

Testing thousands of chemicals to identify potential androgen receptor (AR) agonists or antagonists would cost millions of dollars and take decades to complete using current validated methods. High-throughput in vitro screening (HTS) and computational toxicology approaches can more rapidly and inexpensively identify potential androgen-active chemicals. We integrated 11 HTS ToxCast/Tox21 in vitro assays into a computational network model to distinguish true AR pathway activity from technology-specific assay interference. The in vitro HTS assays probed perturbations of the AR pathway at multiple points (receptor binding, coregulator recruitment, gene transcription, and protein production) and multiple cell types. Confirmatory in vitro antagonist assay data and cytotoxicity information were used as additional flags for potential nonspecific activity. Validating such alternative testing strategies requires high-quality reference data. We compiled 158 putative androgen-active and -inactive chemicals from a combination of international test method validation efforts and semiautomated systematic literature reviews. Detailed in vitro assay information and results were compiled into a single database using a standardized ontology. Reference chemical concentrations that activated or inhibited AR pathway activity were identified to establish a range of potencies with reproducible reference chemical results. Comparison with existing Tier 1 AR binding data from the U.S. EPA Endocrine Disruptor Screening Program revealed that the model identified binders at relevant test concentrations (<100 μM) and was more sensitive to antagonist activity. The AR pathway model based on the ToxCast/Tox21 assays had balanced accuracies of 95.2% for agonist (n = 29) and 97.5% for antagonist (n = 28) reference chemicals. Out of 1855 chemicals screened in the AR pathway model, 220 chemicals demonstrated AR agonist or antagonist activity and an additional 174 chemicals were predicted to have potential weak AR pathway activity.