Cross-species sensitivity to a novel androgen receptor agonist of potential environmental concern, spironolactone

Analytical Interference in Chemiluminescence Assay-Measured Angiotensin I, Angiotensin II, Aldosterone, and Renin

BACKGROUND

The interference can be a significant source of laboratory errors with the potential to cause immunoassay results to drift. Therefore, we evaluated the interference in various endogenous and exogenous substances on immunoassay for angiotensin I (Ang I), angiotensin II (Ang II), aldosterone, and renin in vitro.

METHODS

Ten endogenous and eight exogenous substances were evaluated at supraphysiologic or supratherapeutic plasma levels using the screening study to identify potential interfering substances. Subsequently, potential interfering substances were further tested within maximum pathological or therapeutic plasma concentration ranges using the dose-response study to determine whether the interference has a significant bias. According to preset acceptance criteria, the interference in potential interfering substances for Ang I, Ang II, and renin and aldosterone assays was determined.

RESULTS

Six potential interfering substances for Ang I immunoassays were identified, namely valsartan, nifedipine, spironolactone, cholesterol, hemoglobin, and triglyceride. Meanwhile, ethanol, nifedipine, spironolactone, heparin sodium, warfarin, hemoglobin, uric acid, cholesterol, and triglyceride appeared to have potential interference in the Ang II assay. Three identified as possible interferents for aldosterone immunoassays were glucose, valsartan, and spironolactone. Moreover, warfarin, valsartan, spironolactone, uric acid, cholesterol, bilirubin unconjugated, triglyceride, and hemoglobin were potential interfering substances for renin immunoassays. However, only spironolactone of these potential interfering substances exceeded preset mean bias limits (less than ±10.0%) in aldosterone immunoassays.

CONCLUSION

Exogenous spironolactone caused clinically significant interference in aldosterone immunoassays. Moreover, the interference in other substances was acceptable in Ang I, Ang II, and renin and aldosterone immunoassays.

Towards Precision Ecotoxicology: Leveraging Evolutionary Conservation of Pharmaceutical and Personal Care Product Targets to Understand Adverse Outcomes Across Species and Life Stages

Translation of environmental science to the practice aims to protect biodiversity and ecosystem services, and our future ability to do so relies on the development of a precision ecotoxicology approach wherein we leverage the genetics and informatics of species to better understand and manage the risks of global pollution. A little over a decade ago, a workshop focusing on the risks of pharmaceuticals and personal care products (PPCPs) in the environment identified a priority research question, "What can be learned about the evolutionary conservation of PPCP targets across species and life stages in the context of potential adverse outcomes and effects?" We review the activities in this area over the past decade, consider prospects of more recent developments, and identify future research needs to develop next-generation approaches for PPCPs and other global chemicals and waste challenges. Environ Toxicol Chem 2024;43:526-536. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

A systematic review of the evaluation of endocrine-disrupting chemicals in the Japanese medaka (Oryzias latipes) fish

Japanese medaka (Oryzias latipes) is an acceptable small laboratory fish model for the evaluation and assessment of endocrine-disrupting chemicals (EDCs) found in the environment. In this research, we used this fish as a potential tool for the identification of EDCs that have a significant impact on human health. We conducted an electronic search in PubMed (http://www.ncbi.nlm.nih.gov/pubmed) and Google Scholar (https://scholar.google.com/) using the search terms, Japanese medaka, Oryzias latipes, and endocrine disruptions, and sorted 205 articles consisting of 128 chemicals that showed potential effects on estrogen-androgen-thyroid-steroidogenesis (EATS) pathways of Japanese medaka. From these chemicals, 14 compounds, namely, 17β-estradiol (E2), ethinylestradiol (EE2), tamoxifen (TAM), 11-ketotestosterone (11-KT), 17β-trenbolone (TRB), flutamide (FLU), vinclozolin (VIN), triiodothyronine (T3), perfluorooctanoic acid (PFOA), tetrabromobisphenol A (TBBPA), terephthalic acid (TPA), trifloxystrobin (TRF), ketoconazole (KTC), and prochloraz (PCZ), were selected as references and used for the identification of apical endpoints within the EATS modalities. Among these endpoints, during classification, priorities are given to sex reversal (masculinization of females and feminization of males), gonad histology (testis-ova or ovotestis), secondary sex characteristics (anal fin papillae of males), plasma and liver vitellogenin (VTG) contents in males, swim bladder inflation during larval development, hepatic vitellogenin (vtg) and choriogenin (chg) genes in the liver of males, and several genes, including estrogen-androgen-thyroid receptors in the hypothalamus-pituitary-gonad/thyroid axis (HPG/T). After reviewing 205 articles, we identified 108 (52.68%), 46 (22.43%), 19 (9.26%), 22 (17.18%), and 26 (12.68%) papers that represented studies on estrogen endocrine disruptors (EEDs), androgen endocrine disruptors (AEDs), thyroid endocrine disruptors (TEDs), and/or steroidogenesis modulators (MOS), respectively. Most importantly, among 128 EDCs, 32 (25%), 22 (17.18%), 15 (11.8%), and 14 (10.93%) chemicals were classified as EEDs, AEDs, TEDs, and MOS, respectively. We also identified 43 (33.59%) chemicals as high-priority candidates for tier 2 tests, and 13 chemicals (10.15%) show enough potential to be considered EDCs without any further tier-based studies. Although our literature search was unable to identify the EATS targets of 45 chemicals (35%) studied in 60 (29.26%) of the 205 articles, our approach has sufficient potential to further move the laboratory-based research data on Japanese medaka for applications in regulatory risk assessments in humans.

Are changes in vitellogenin concentrations in fish reliable indicators of chemical-induced endocrine activity?

Vitellogenin (VTG), a biomarker for endocrine activity, is a mechanistic component of the regulatory assessment of potential endocrine-disrupting properties of chemicals. This review of VTG data is based on changes reported for 106 substances in standard fish species. High intra-study and inter-laboratory variability in VTG concentrations was confirmed, as well as discrepancies in interpretation of results based on large differences between fish in the dilution water versus solvent control, or due to the presence of outlier measurements. VTG responses in fish were ranked against predictions for estrogen receptor agonist activity and aromatase inhibition from bioactivity model output and ToxCast in vitro assay results, respectively. These endocrine mechanisms explained most of the VTG responses in the absence of systemic toxicity, the magnitude of the VTG response being proportional to the in vitro potency. Interpretation of the VTG data was sometimes confounded by an alternative endocrine mechanism of action. There was evidence for both false positive and negative responses for VTG synthesis, but overall, it was rare for substances without endocrine activity in vitro to cause a concentration-dependent VTG response in fish in the absence of systemic toxicity. To increase confidence in the VTG results, we recommend improvements in the VTG measurement methodologies and greater transparency in reporting of VTG data (including quality control criteria for assay performance). This review supports the application of New Approach Methodologies (NAMs) by demonstrating that endocrine activity in vitro from mammalian cell lines is predictive for in vivo VTG response in fish, suggesting that in vitro mechanistic data could be used more broadly in decision-making to help reduce animal testing.

Detection of anti-androgenic activity of chemicals in fish studies: a data review

A systematic review was conducted on the sensitivity of fish testing guidelines to detect the anti-androgenic activity of substances. Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) was used to investigate the conservation of the androgen receptor (AR) between humans and fish, and among fish species recommended in test guidelines. The AR is conserved between fish species and humans (i.e. ligand binding domain [LBD] homology ≥70%) and among the recommended fish species (LBD homology >85%). For model anti-androgens, we evaluated literature data on in vitro anti-androgenic activity in fish-specific receptor-based assays and changes in endpoints indicative of endocrine modulation from in vivo studies. Anti-androgenic activity was most consistently and reliably detected in in vitro and in vivo mechanistic studies with co-exposure to an androgen (spiggin in vitro assay, Rapid Androgen Disruption Activity Reporter [RADAR] Assay, and Androgenised Female Stickleback Screen). Regardless of study design (Fish Short-Term Reproduction Assay [FSTRA], Fish Sexual Development Test [FSDT], partial or full life-cycle tests), or endpoint (vitellogenin, secondary sexual characteristics, gonadal histopathology, sex ratio), there was no consistent evidence for detecting anti-androgenic activity in studies without androgen co-exposure, even for the most potent substances (while less potent substances may induce no (clear) response). Therefore, based on studies without androgen co-exposure (35 FSTRAs and 22 other studies), the other studies (including the FSDT) do not outperform the FSTRA for detecting potent anti-androgenic activity, which if suspected, would be best addressed with a RADAR assay. Overall, fish do not appear particularly sensitive to mammalian anti-androgens.

Chronic Embryo-Larval Exposure of Fathead Minnows to the Pharmaceutical Drug Metformin: Survival, Growth, and Microbiome Responses

Metformin is a glucose-lowering drug commonly found in municipal wastewater effluents (MWWEs). The present study investigated the chronic effects of metformin in early-life stages of the fathead minnow (Pimephales promelas). Endpoints assessed were growth, survival, and deformities. The larval gut microbiome was also examined using 16 S ribosomal RNA gene amplicon sequencing to determine microbial community composition and alpha and beta diversity. Eggs and larvae were exposed to metformin measured concentrations (mean [standard deviation]) of 0.020 (0.017) μg/L (for controls) and 3.44 (0.23), 33.6 (1.6), and 269 (11) μg/L in a daily static-renewal setup, with 20 embryos per beaker. The low and middle metformin exposure concentrations represent river and MWWE concentrations of metformin. To detect small changes in growth, we used 18 replicate beakers for controls and 9 replicates for each metformin treatment. Over the 21-d exposure (5 d as embryos and 16 d posthatch [dph]), metformin did not affect survival or growth of larval fish. Hatch success, time to hatch, deformities in hatched fry, and survival were similar across all treatments. Growth (wet wt, length, and condition factor) assessed at 9 and 16 dph was also unaffected by metformin. Assessment of the microbiome showed that the larvae microbiome was dominant in Proteobacteria and Firmicutes, with small increases in Proteobacteria and decreases in Firmicutes with increasing exposure to metformin. No treatment effects were found for microbiome diversity measures. Control fish euthanized with the anesthetic tricaine methane sulfonate had decreased alpha diversity compared to those sampled by spinal severance. This experiment demonstrates that metformin at environmentally relevant concentrations (3.44 and 33.6 μg/L) and at 10 times MWWE concentrations (269 µg/L) does not adversely affect larval growth or gut microbiome in this ubiquitous freshwater fish species. Environ Toxicol Chem 2022;41:635-647. © 2021 Her Majesty the Queen in Right of Canada. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Reproduced with the permission of the Minister of Environment and Climate Change Canada.

Combined Naïve Bayesian, Chemical Fingerprints and Molecular Docking Classifiers to Model and Predict Androgen Receptor Binding Data for Environmentally- and Health-Sensitive Substances

Many chemicals that enter the environment, food chain, and the human body can disrupt androgen-dependent pathways and mimic hormones and therefore, may be responsible for multiple diseases from reproductive to tumor. Thus, modeling and predicting androgen receptor activity is an important area of research. The aim of the current study was to find a method or combination of methods to predict compounds that can bind to and/or disrupt the androgen receptor, and thereby guide decision making and further analysis. A stepwise procedure proceeded from analysis of protein structures from human, chimp, and rat, followed by docking and subsequent ligand, and statistics based techniques that improved classification gradually. The best methods used multivariate logistic regression of combinations of chimpanzee protein structural docking scores, extended connectivity fingerprints, and naïve Bayesians of known binders and non-binders. Combination or consensus methods included data from a variety of procedures to improve the final model accuracy.

Toxicity of the pharmaceuticals finasteride and melengestrol acetate to benthic invertebrates

The toxicity of endocrinologically active pharmaceuticals finasteride (FIN) and melengestrol acetate (MGA) was assessed in freshwater mussels, including acute (48 h) aqueous tests with glochidia from Lampsilis siliquoidea, sub-chronic (14 days) sediment tests with gravid female Lampsilis fasciola, and chronic (28 days) sediment tests with juvenile L. siliquoidea, and in chronic (42 days) sediment tests with the amphipod Hyalella azteca and the mayfly Hexagenia spp. Finasteride was not toxic in acute aqueous tests with L. siliquoidea glochidia (up to 23 mg/L), whereas significant toxicity to survival and burial ability was detected in chronic sediment tests with juvenile L. siliquoidea (chronic value (ChV, the geometric mean of LOEC and NOEC) = 58 mg/kg (1 mg/L)). Amphipods (survival, growth, reproduction, and sex ratio) and mayflies (growth) were similarly sensitive (ChV = 58 mg/kg (1 mg/L)). Melengestrol acetate was acutely toxic to L. siliquoidea glochidia at 4 mg/L in aqueous tests; in sediment tests, mayflies were the most sensitive species, with significant growth effects observed at 37 mg/kg (0.25 mg/L) (ChV = 21 mg/kg (0.1 mg/L)). Exposure to sublethal concentrations of FIN and MGA had no effect on the (luring and filtering) behaviour of gravid L. fasciola, or the viability of their brooding glochidia. Based on the limited number of measured environmental concentrations of both chemicals, and their projected concentrations, no direct effects are expected by these compounds individually on the invertebrates tested. However, organisms are exposed to contaminant mixtures in the aquatic environment, and thus, the effects of FIN and MGA as components of these mixtures require further investigation.

Critical Review of Read-Across Potential in Testing for Endocrine-Related Effects in Vertebrate Ecological Receptors

Recent regulatory testing programs have been designed to evaluate whether a chemical has the potential to interact with the endocrine system and could cause adverse effects. Some endocrine pathways are highly conserved among vertebrates, providing a potential to extrapolate data generated for one vertebrate taxonomic group to others (i.e., biological read-across). To assess the potential for biological read-across, we reviewed tools and approaches that support species extrapolation for fish, amphibians, birds, and reptiles. For each of the estrogen, androgen, thyroid, and steroidogenesis (EATS) pathways, we considered the pathway conservation across species and the responses of endocrine-sensitive endpoints. The available data show a high degree of confidence in the conservation of the hypothalamus-pituitary-gonadal axis between fish and mammals and the hypothalamus-pituitary-thyroid axis between amphibians and mammals. Comparatively, there is less empirical evidence for the conservation of other EATS pathways between other taxonomic groups, but this may be due to limited data. Although more information on sensitive pathways and endpoints would be useful, current developments in the use of molecular target sequencing similarity tools and thoughtful application of the adverse outcome pathway concept show promise for further advancement of read-across approaches for testing EATS pathways in vertebrate ecological receptors. Environ Toxicol Chem 2020;39:739-753. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Occurrence of Glucocorticoids, Mineralocorticoids, and Progestogens in Various Treated Wastewater, Rivers, and Streams

In the current study a high sensitive analytical method was developed for the determination of 60 steroids including glucocorticoids (GC), mineralocorticoids (MC), and progestogens (PG) in WWTP effluents and surface water using liquid chromatography with tandem mass spectrometry detection (LC-MS/MS). The limits of quantification (LOQ) ranged between 0.02 ng/L (cortisone) to 0.5 ng/L (drospirenone) in surface water and from 0.05 ng/L (betamethasone) to 5 ng/L (chlormadinone) in treated wastewater. After optimization, the developed method was applied to WWTP effluents, rivers, and streams around Germany. Numerous steroids have been detected during the sampling campaign and predominant analytes from all steroid types were determined. Moreover, the occurrence of dienogest, mometasone furoate, flumethasone pivalate, and the metabolites 6β-hydroxy dienogest, 6β-hydroxy triamcinolone acetonide, 7α-thiomethyl spironolactone, and 11α-hydroxy canrenone is reported for the first time. In addition, this study revealed the ubiquitous presence of topically applied GC monoesters betamethasone propionate, betamethasone valerate, and 6α-methylprednisolone propionate in WWTP effluents and surface water.

Estimating Intermittent Individual Spawning Behavior via Disaggregating Group Data

In order to understand fish biology and reproduction, it is important to know the fecundity patterns of individual fish, as frequently established by recording the output of mixed-sex groups of fish in a laboratory setting. However, for understanding individual reproductive health and modeling purposes it is important to estimate individual fecundity from group fecundity. We created a multistage method that disaggregates group-level data into estimates for individual-level clutch size and spawning interval distributions. The first stage of the method develops estimates of the daily spawning probability of fish. Daily spawning probabilities are then used to calculate the log likelihood of candidate distributions of clutch size. Selecting the best candidate distribution for clutch size allows for a Monte Carlo resampling of annotations of the original data which state how many fish spawned on which day. We verify this disaggregation technique by combining data from fathead minnow pairs, and checking that the disaggregation method reproduced the original clutch sizes and spawning intervals. This method will allow scientists to estimate individual clutch size and spawning interval distributions from group spawning data without specialized or elaborate experimental designs.

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.

Adverse Outcome Pathway (AOP) Informed Modeling of Aquatic Toxicology: QSARs, Read-Across, and Interspecies Verification of Modes of Action

Alternative approaches have been promoted to reduce the number of vertebrate and invertebrate animals required for the assessment of the potential of compounds to cause harm to the aquatic environment. A key philosophy in the development of alternatives is a greater understanding of the relevant adverse outcome pathway (AOP). One alternative method is the fish embryo toxicity (FET) assay. Although the trends in potency have been shown to be equivalent in embryo and adult assays, a detailed mechanistic analysis of the toxicity data has yet to be performed; such analysis is vital for a full understanding of the AOP. The research presented herein used an updated implementation of the Verhaar scheme to categorize compounds into AOP-informed categories. These were then used in mechanistic (quantitative) structure-activity relationship ((Q)SAR) analysis to show that the descriptors governing the distinct mechanisms of acute fish toxicity are capable of modeling data from the FET assay. The results show that compounds do appear to exhibit the same mechanisms of toxicity across life stages. Thus, this mechanistic analysis supports the argument that the FET assay is a suitable alternative testing strategy for the specified mechanisms and that understanding the AOPs is useful for toxicity prediction across test systems.

Application of in silico and in vitro methods in the development of adverse outcome pathway constructs in wildlife

There is a long history of using both in silico and in vitro methods to predict adverse effects in humans and environmental species where toxicity data are lacking. Currently, there is a great deal of interest in applying these methods to the development of so-called 'adverse outcome pathway' (AOP) constructs. The AOP approach provides a framework for organizing information at the chemical and biological level, allowing evidence from both in silico and in vitro studies to be rationally combined to fill gaps in knowledge concerning toxicological events. Fundamental to this new paradigm is a greater understanding of the mechanisms of toxicity and, in particular, where these mechanisms may be conserved across taxa, such as between model animals and related wild species. This presents an opportunity to make predictions across diverse species, where empirical data are unlikely to become available as is the case for most species of wildlife.

Leveraging existing data for prioritization of the ecological risks of human and veterinary pharmaceuticals to aquatic organisms

Medicinal innovation has led to the discovery and use of thousands of human and veterinary drugs. With this comes the potential for unintended effects on non-target organisms exposed to pharmaceuticals inevitably entering the environment. The impracticality of generating whole-organism chronic toxicity data representative of all species in the environment has necessitated prioritization of drugs for focused empirical testing as well as field monitoring. Current prioritization strategies typically emphasize likelihood for exposure (i.e. predicted/measured environmental concentrations), while incorporating only rather limited consideration of potential effects of the drug to non-target organisms. However, substantial mammalian pharmacokinetic and mechanism/mode of action (MOA) data are produced during drug development to understand drug target specificity and efficacy for intended consumers. An integrated prioritization strategy for assessing risks of human and veterinary drugs would leverage available pharmacokinetic and toxicokinetic data for evaluation of the potential for adverse effects to non-target organisms. In this reiview, we demonstrate the utility of read-across approaches to leverage mammalian absorption, distribution, metabolism and elimination data; analyse cross-species molecular target conservation and translate therapeutic MOA to an adverse outcome pathway(s) relevant to aquatic organisms as a means to inform prioritization of drugs for focused toxicity testing and environmental monitoring.

Adverse outcome pathway development II: best practices

Organization of existing and emerging toxicological knowledge into adverse outcome pathway (AOP) descriptions can facilitate greater application of mechanistic data, including those derived through high-throughput in vitro, high content omics and imaging, and biomarker approaches, in risk-based decision making. The previously ad hoc process of AOP development is being formalized through development of internationally harmonized guidance and principles. The goal of this article was to outline the information content desired for formal AOP description and some rules of thumb and best practices intended to facilitate reuse and connectivity of elements of an AOP description in a knowledgebase and network context. For example, key events (KEs) are measurements of change in biological state that are indicative of progression of a perturbation toward a specified adverse outcome. Best practices for KE description suggest that each KE should be defined as an independent measurement made at a particular level of biological organization. The concept of "functional equivalence" can help guide both decisions about how many KEs to include in an AOP and the specificity with which they are defined. Likewise, in describing both KEs and evidence that supports a causal linkage or statistical association between them (ie, a key event relationship; KER), best practice is to build from and contribute to existing KE or KER descriptions in the AOP knowledgebase rather than creating redundant descriptions. The best practices proposed address many of the challenges and uncertainties related to AOP development and help promote a consistent and reliable, yet flexible approach.

Quantitative cross-species extrapolation between humans and fish: the case of the anti-depressant fluoxetine

Fish are an important model for the pharmacological and toxicological characterization of human pharmaceuticals in drug discovery, drug safety assessment and environmental toxicology. However, do fish respond to pharmaceuticals as humans do? To address this question, we provide a novel quantitative cross-species extrapolation approach (qCSE) based on the hypothesis that similar plasma concentrations of pharmaceuticals cause comparable target-mediated effects in both humans and fish at similar level of biological organization (Read-Across Hypothesis). To validate this hypothesis, the behavioural effects of the anti-depressant drug fluoxetine on the fish model fathead minnow (Pimephales promelas) were used as test case. Fish were exposed for 28 days to a range of measured water concentrations of fluoxetine (0.1, 1.0, 8.0, 16, 32, 64 µg/L) to produce plasma concentrations below, equal and above the range of Human Therapeutic Plasma Concentrations (H_TPCs). Fluoxetine and its metabolite, norfluoxetine, were quantified in the plasma of individual fish and linked to behavioural anxiety-related endpoints. The minimum drug plasma concentrations that elicited anxiolytic responses in fish were above the upper value of the H_TPC range, whereas no effects were observed at plasma concentrations below the H_TPCs. In vivo metabolism of fluoxetine in humans and fish was similar, and displayed bi-phasic concentration-dependent kinetics driven by the auto-inhibitory dynamics and saturation of the enzymes that convert fluoxetine into norfluoxetine. The sensitivity of fish to fluoxetine was not so dissimilar from that of patients affected by general anxiety disorders. These results represent the first direct evidence of measured internal dose response effect of a pharmaceutical in fish, hence validating the Read-Across hypothesis applied to fluoxetine. Overall, this study demonstrates that the qCSE approach, anchored to internal drug concentrations, is a powerful tool to guide the assessment of the sensitivity of fish to pharmaceuticals, and strengthens the translational power of the cross-species extrapolation.

Molecular target sequence similarity as a basis for species extrapolation to assess the ecological risk of chemicals with known modes of action

It is not feasible to conduct toxicity tests with all species that may be impacted by chemical exposures. Therefore, cross-species extrapolation is fundamental to environmental risk assessment. Recognition of the impracticality of generating empirical, whole organism, toxicity data for the extensive universe of chemicals in commerce has been an impetus driving the field of predictive toxicology. We describe a strategy that leverages expanding databases of molecular sequence information together with identification of specific molecular chemical targets whose perturbation can lead to adverse outcomes to support predictive species extrapolation. This approach can be used to predict which species may be more (or less) susceptible to effects following exposure to chemicals with known modes of action (e.g., pharmaceuticals, pesticides). Primary amino acid sequence alignments are combined with more detailed analyses of conserved functional domains to derive the predictions. This methodology employs bioinformatic approaches to automate, collate, and calculate quantitative metrics associated with cross-species sequence similarity of key molecular initiating events (MIEs). Case examples focused on the actions of (a) 17α-ethinyl estradiol on the human (Homo sapiens) estrogen receptor; (b) permethrin on the mosquito (Aedes aegypti) voltage-gated para-like sodium channel; and (c) 17β-trenbolone on the bovine (Bos taurus) androgen receptor are presented to demonstrate the potential predictive utility of this species extrapolation strategy. The examples compare empirical toxicity data to cross-species predictions of intrinsic susceptibility based on analyses of sequence similarity relevant to the MIEs of defined adverse outcome pathways. Through further refinement, and definition of appropriate domains of applicability, we envision practical and routine utility for the molecular target similarity-based predictive method in chemical risk assessment, particularly where testing resources are limited.