It is logistically impossible to perform toxicity testing of all chemicals in all species. Therefore, chemical safety evaluations must find ways to make inferences about toxicity in untested species based on observations from model species. Development of bioinformatics tools that create scientific lines of evidence for extrapolation of toxicity knowledge across species are gaining traction in decision-making surrounding chemical safety. These approaches take advantage of computational power and allow for incorporation of large-scale omics data to infer conservation of biological pathways across species to enable predictions of chemical susceptibility and further understand potential toxicity. As comparative toxicity data from such approaches are integrated into regulatory decisions to support surrogacy challenges it is important that the tools being developed for and applied in regulation meet necessary standards identified by hazard and risk assessment practitioners. The International Consortium to Advance Cross Species Extrapolation in Regulation (ICACSER), which consists of researchers, tool developers, and regulatory decision-makers seeks to highlight the foundational role of bioinformatics for enhanced scientific evidence to inform chemical safety decisions across species. To articulate essential standards and define best practices in development and application of bioinformatics approaches specific to this context, three existing tools are examined, and their key attributes are highlighted and connections to the adverse outcome pathway framework are discussed. These practices are intended to act as a guide for current and future tool development.

Zebrafish are widely leveraged for investigating per- and polyfluoroalkyl substance (PFAS) toxicity; however, there exists a data gap for employing zebrafish transcriptomic data for PFAS quantitative risk assessment. The present study exposed developing zebrafish at different start times and durations to 0 to 100 µM of perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexanesulfonic acid (PFHxS) to examine chemical-specific effects on transcriptomics-based point of departure estimates (tPODs). Study goals were to investigate if the tPODs were robust to differences in exposure start and duration, were protective of zebrafish apical outcomes, and were similar to recently published PFAS tPODs in other model organisms. Zebrafish tPODs were within 1.5 orders of magnitude across the 3 chemicals, exposure durations, and start times, except for the shortest and earliest exposure (6 to 24 h post fertilization) for PFOS/PFOA. Although corresponding apical endpoints were influenced by exposure scenario, tPODs were generally lower, and thus protective of zebrafish mortality and sublethal endpoints. The relationship between our tPODs and literature zebrafish toxicity effects was chemical-specific; only the PFOA tPODs were protective of all apical effects together, and PFOS/PFHxS tPODs were generally within the interquartile range of the effects concentrations. The zebrafish PFAS tPODs were also similar to previously published fathead minnow tPODs, whereas only the PFOS zebrafish tPODs were within one order of magnitude of the Daphnia magna PFOS tPOD. Our study emphasizes that the high-throughput-compatible, in vivo developmental zebrafish platform is a feasible tool for detecting dose-dependent gene expression responses that can be leveraged for higher-tier assessments.

The U.S. Environmental Protection Agency's web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to evaluate protein conservation across species through sequence and structural alignments to gather lines of evidence for predicting chemical susceptibility. Although SeqAPASS can rapidly generate predictions of species susceptibility in terms of a "yes" or "no" output, there is a growing interest in deriving more quantitative metrics for enhancing these predictions. To do this, a bioinformatics workflow was developed that combined SeqAPASS results with molecular docking and molecular dynamics (MD) simulations. This workflow was developed using transthyretin (TTR) and a per- and polyfluoroalkyl substance, with an emphasis on perfluorooctanoic acid (PFOA) as it is known that PFOA binds to TTR in humans and other experimental animals. This workflow was applied to generate quantitative information as additional lines of evidence for the conservation of the PFOA-TTR interaction across species. The SeqAPASS analysis predicted hundreds of species as susceptible based on conservation of the PFOA-TTR interaction (Level 1: 952 species, Level 2: 976 species, Level 3: 750 species). Predicted TTR structures from a subset of the species predicted as susceptible by SeqAPASS were used in molecular docking and MD simulations. The simulations supported that Lysine-15 is a key residue for the PFOA-TTR interaction. Quantitatively there was no significant difference in the species tested regarding their predicted binding affinities or other metrics specific to the chemical-protein interactions. These results demonstrated that the interaction between TTR and PFOA is likely conserved across various vertebrate taxonomic groups. Overall, this work provides a template for how advanced bioinformatics tools like MD simulations can be applied within ecotoxicology for improving cross-species predictions of chemical susceptibility. Importantly, our efforts aim to demonstrate applicability of these computational methods for integration in next-generation risk assessments.

Historic animal-based toxicity testing methods cannot keep pace with the need for prioritizing new and existing chemicals for comprehensive risk assessment. New approach methodologies such as high-throughput in vitro transcriptomics screening have emerged to address this challenge. However, most in vitro methods were developed using mammalian cell lines, including human, and may not adequately represent environmental species, potentially limiting the utility of this methodology for supporting environmental risk assessment. The objective of this study was to evaluate whether zebrafish cell lines can generate biologically meaningful chemical effects data in a high-throughput transcriptomics pipeline that is protective of toxicologically relevant aquatic apical endpoints. Forty-two test chemicals were screened in 2 commercially available zebrafish cell lines (ZFL liver and ZEM2S embryonic fibroblast) using the TempO-Seq zS1500+ platform. Transcriptomic points-of-departure (tPODs) were derived using 2 methods: Gene-level analysis (tPODgenes) with BMDExpress software and biological pathway-altering concentrations (BPACs/tPODsignatures) from signature-based dose-response analysis. When converted to predicted external water concentrations using quantitative in vitro-in vivo extrapolation models, tPODs were generally protective of aquatic in vivo endpoints from the ECOTOX Knowledgebase. Differential gene expression and biological pathway analysis revealed potential cell-type-specific effects for several chemicals, highlighting the value of using multiple cell types for capturing tissue-specific responses. Lastly, the biological pathway information was used to extrapolate the chemical effects data across species through an integration of protein-protein interaction network analysis and the Sequence Alignment to Predict Across Species Susceptibility tool, which has significant implications for improving the ecological relevance of these methods.

Diamide insecticides, specifically chlorantraniliprole (CHL), have been rising in popularity over the past decade, becoming one of the most widely used insecticide classes globally. These insecticides target the ryanodine receptor (RyR), primarily for control of lepidopteran agricultural pests. Field studies have revealed that some lepidopteran species have developed mutations where a methionine in a particular position (e.g., I4790M) increases resistance to CHL. The toxicity data for CHL across species is limited, as is the case for many chemicals, which creates an opportunity to apply both traditional toxicity test methods and new approach methods (NAMs) to address data gaps. Here, the U.S. Environmental Protection Agency's Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was used to query the RyR to generate susceptibility predictions for species exposed to CHL to fill those data gaps. These SeqAPASS results generated testable hypotheses that were used to guide focused acute aquatic toxicity studies using Daphnia magna, Daphnia pulex, Pimephales promelas, and Danio rerio. The fish species were not sensitive to CHL, whereas D. magna and D. pulex were found to be sensitive to CHL at environmentally relevant concentrations, despite having the methionine residue in the position of the I4790M resistance mutation. Additional SeqAPASS results showed that many other species, including beneficial pollinators and Lepidoptera, are predicted as likely susceptible to CHL. This study provided multiple lines of evidence toward the unlikelihood for the I4790M mutation to be the primary cause of resistance across species, filled knowledge gaps concerning CHL toxicity across species, and generated predictions of susceptibility for nontarget species that are not generally amenable to toxicity testing. This work presents a case example that demonstrates how NAMs can be used in combination with other types of data to direct targeted testing and build confidence in predictive approaches for their use in risk assessment.

A healthy ocean is a crucial life support system that regulates the global climate, is a source of oxygen and supports major economic activities. A vast and understudied biodiversity from micro- to macro-organisms is integral to ocean health. However, the impact of pollutants that reach the ocean daily is understudied for marine taxa, which are also absent or poorly represented in regulatory test guidelines for chemical hazard assessment. Inspired by the United Nations Decade of Ocean Science, which aims to reverse the decline in ocean health, this communication calls for global coordination in building resources for studying the effects of marine pollution. The bibliographic analysis, a collective product of scientists from diverse backgrounds, focused on endocrine-disrupting chemicals (EDCs). In this review, we (i) critically analyse the literature on endocrine signalling pathways and high-level physiological impacts of EDCs across 20 representative marine taxa; (ii) identify knowledge and regulatory gaps; (iii) apply bioinformatics approaches to marine species genomic resources, with relevance for predictions of susceptibility; and (iv) provide recommendations of priority actions for different stakeholders. We reveal that the scientific literature on EDCs is biased towards terrestrial and/or freshwater organisms, is limited to a handful of animal taxa, and marine organisms are dramatically underrepresented. Our bibliographic analysis also confirmed that only a small number of (neuro) endocrine pathways are covered for all animals, whilst basic knowledge on endocrine systems/endocrine disruption for most marine invertebrate phyla is minimal. Despite significant gaps in genomic resources for marine animals, endocrine-related protein conservation was evident across more than 500 species from diverse marine taxa, highlighting that they are at risk from EDCs. Despite recent technological advances, translation of existing knowledge into international regulatory test guidelines for chemical hazard assessment and monitoring programs is limited. Furthermore, the current understanding is confounded in part by transposing vertebrate endocrinology onto non-vertebrate taxa. In this context, specific recommendations are provided for all stakeholders, including academia (e.g. to expand knowledge across metazoan taxa and endocrine targets and translate it to New Approach Methodologies and Adverse Outcome Pathways; to increase and improve tools for comparative species-sensitivity distributions and cross-species extrapolations), regulators (e.g. increase awareness of specific risks for the marine environment, prioritise international standardisation of testing methods for marine species and request evidence for absence of endocrine disruption in marine phyla), policy makers (e.g. implement sustained, long-term international marine monitoring programs and increase global co-operation) and the public or non-governmental organisations (e.g. foster public engagement and behaviours that prevent marine chemical pollution; promote citizen science activities; and drive political actions towards protective and restorative marine policies). We hope that this and past reviews can contribute towards meeting ambitious international plans for marine water quality assurance, mitigation of marine pollution impacts and protection of marine biodiversity. The importance of marine biodiversity for climate change mitigation, food security and sustainable ecosystem services calls for urgent, cooperative action.

The advancement of protein structural prediction tools, exemplified by AlphaFold and Iterative Threading ASSEmbly Refinement, has enabled the prediction of protein structures across species based on available protein sequence and structural data. In this study, we introduce an innovative molecular docking method that capitalizes on this wealth of structural data to enhance predictions of chemical susceptibility across species. We demonstrated this method using the androgen receptor as a pertinent modulator of endocrine function. By using protein structures, this method contextualizes species susceptibility within a functional framework and helps to integrate molecular docking into the repertoire of New Approach Methodologies (NAMs) that support the Next-Generation Risk Assessment (NGRA) paradigm through the novel integration of various open-source tools.

Background: Zoonotic transmission of severe acute respiratory coronavirus 2 (SARS-CoV-2) has been found to result in infections in more than 30 mammalian species. The SARS-CoV-2 spike protein binds to the host’s angiotensin converting enzyme 2 (ACE2) cell surface receptor to gain entry into the cell. ACE2 protein sequence conservation has therefore been evaluated across species, and species with amino acid substitutions in ACE2 were ranked low for susceptibility to SARS-CoV-2 infection. However, many of these species have become infected by the virus. Methods: This study investigated the conservation of 24 host protein targets, including the entry proteins ACE2 and transmembrane serine protease 2 (TMPRSS2); 21 proteins in the interferon-I (IFN-I) antiviral response pathway; and tethrin, a protein that suppresses new virion release from cells. Bioinformatics approaches including Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS), Molecular Operating Environment (MOE), and iCn3D software were used to compare protein sequence similarity, conserved domains, and critical amino acids for host-viral protein-protein interactions. The types of bonding interactions were scored, and the results were compared with empirical data indicating which species have or have not become infected. Results: This pathway approach revealed that 1) 13 proteins were conserved, whereas five lacked data sufficient to determine specific critical amino acids; 2) variation in protein-protein interfaces is tolerated for many amino acid substitutions, and these substitutions follow taxonomic clades rather than correlating with empirically determined species infection status; and 3) four proteins (MDA5, NEMO, IRF3, and ISG15) contained potential domains or specific amino acids whose substitution may result in PPI disruption. Conclusion: This work provides evidence that certain substitutions in four IFN-I antiviral pathway proteins appear able to disrupt interactions and may be distinctive to resistant species, thus potentially aiding in determining species’ likelihood of transmitting SARS-CoV-2.

Accounting for intraspecific and interspecific competition when assessing the effects of chemical and nonchemical stressors is an important uncertainty in ecological risk assessments. We developed novel projection of interspecific competition (PIC) matrices that allow for analysis of population dynamics of two or more species exposed to a given stressor(s) that compete for shared resources within a landscape. We demonstrate the application of PIC matrices to investigate the population dynamics of two hypothetical fish species that compete with one another and have differences in net reproductive rate and intrinsic rate of population increase. Population status predictions were made under scenarios that included exposure to a chemical stressor that reduced fecundity for one or both species. The results of our simulations demonstrated that measures obtained from the life table and Leslie matrix of an organism, including net reproductive rate and intrinsic rate of increase, can result in erroneous conclusions of population status and viability in the absence of a consideration of resource limitation and interspecific competition. This modeling approach can be used in conjunction with field monitoring efforts and/or laboratory testing to link effects due to stressors to possible outcomes within an ecosystem. In addition, PIC matrices could be combined with adverse outcome pathways to allow for ecosystem projection based on taxonomic conservation of molecular targets of chemicals to predict the likelihood of relative cross-species susceptibility. Overall, the present study shows how PIC matrices can integrate effects across the life cycles of multiple species, provide a linkage between endpoints observed in individual and population-level responses, and project outcomes at the community level for multiple generations for multiple species that compete for limited resources. Environ Toxicol Chem 2024;43:1406-1422. Published 2024. This article is a U.S. Government work and is in the public domain in the USA.

Biological Evaluations support Endangered Species Act (ESA) consultation with the US Fish and Wildlife Service and National Marine Fisheries Service by federal action agencies, such as the USEPA, regarding impacts of federal activities on threatened or endangered species. However, they are often time-consuming and challenging to conduct. The identification of pollutant benchmarks or guidance to protect taxa for states and tribes when USEPA has not yet developed criteria recommendations is also of importance to ensure a streamlined approach to Clean Water Act program implementation. Due to substantial workloads, tight regulatory timelines, and the often-protracted length of ESA consultations, there is a need to streamline the development of biological evaluation toxicity assessments for determining the impact of chemical pollutants on ESA-listed species. Moreover, there is limited availability of species-specific toxicity data for many contaminants, further complicating the consultation process. New approach methodologies are being increasingly used in toxicology and chemical safety assessment to rapidly and cost-effectively provide data that can fill gaps in hazard and/or exposure characterization. Here, we present the development of an automated computational pipeline-RASRTox (Rapidly Acquire, Score, and Rank Toxicological data)-to rapidly extract and categorize ecological toxicity benchmark values from curated data sources (ECOTOX, ToxCast) and well-established quantitative structure-activity relationships (TEST, ECOSAR). As a proof of concept, points-of-departure (PODs) generated in RASRTox for 13 chemicals were compared against benchmark values derived using traditional methods-toxicity reference values (TRVs) and water quality criteria (WQC). The RASRTox PODs were generally within an order of magnitude of corresponding TRVs, though less concordant compared with WQC. The greatest utility of RASRTox, however, lies in its ability to quickly and systematically identify critical studies that may serve as a basis for screening value derivation by toxicologists as part of an ecological hazard assessment. As such, the strategy described in this case study can potentially be adapted for other risk assessment contexts and stakeholder needs. Integr Environ Assess Manag 2024;20:2203-2217. © 2024 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Thyroid hormone system disrupting compounds are considered potential threats for human and environmental health. Multiple adverse outcome pathways (AOPs) for thyroid hormone system disruption (THSD) are being developed in different taxa. Combining these AOPs results in a cross-species AOP network for THSD which may provide an evidence-based foundation for extrapolating THSD data across vertebrate species and bridging the gap between human and environmental health. This review aimed to advance the description of the taxonomic domain of applicability (tDOA) in the network to improve its utility for cross-species extrapolation. We focused on the molecular initiating events (MIEs) and adverse outcomes (AOs) and evaluated both their plausible domain of applicability (taxa they are likely applicable to) and empirical domain of applicability (where evidence for applicability to various taxa exists) in a THSD context. The evaluation showed that all MIEs in the AOP network are applicable to mammals. With some exceptions, there was evidence of structural conservation across vertebrate taxa and especially for fish and amphibians, and to a lesser extent for birds, empirical evidence was found. Current evidence supports the applicability of impaired neurodevelopment, neurosensory development (eg, vision) and reproduction across vertebrate taxa. The results of this tDOA evaluation are summarized in a conceptual AOP network that helps prioritize (parts of) AOPs for a more detailed evaluation. In conclusion, this review advances the tDOA description of an existing THSD AOP network and serves as a catalog summarizing plausible and empirical evidence on which future cross-species AOP development and tDOA assessment could build.

New approach methodologies (NAMs) are being developed to reduce and replace vertebrate animal testing in support of ecotoxicology and risk assessment. The US Environmental Protection Agency's Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) bioinformatic tool was used to evaluate amino acid sequence conservation of the type 3 iodothyronine deiodinase (DIO3) enzyme across species to demonstrate NAM applications for understanding effects of chemical interactions with a specific protein target. Existing literature was used to identify critical amino acids for thyroid hormone binding and interaction with a reducing cofactor. The SeqAPASS tool identifies whether known critical amino acids involved in ligand binding are exact, partial, or not matches across species compared with a template species based on molecular weight and side chain classification. This evaluation guided the design of variant proteins representing critical amino acid substitutions found in various species. Site-directed mutagenesis of the wild-type (WT) human DIO3 gene sequence was used to create six variant proteins expressed in cell culture, which were then tested in vitro for chemical inhibition. Significant differences in in vitro median inhibitory concentration results were observed among variants for potential competitive inhibitors. A molecular model representing the WT human DIO3 was constructed using Molecular Operating Environment (MOE) software and mutated in silico to create the six variants. The MOE Site Finder tool identified the proposed catalytic and cofactor sites and potential alternative binding sites. Virtual docking did not provide affinity scores with sufficient resolution to rank the potency of the chemical inhibitors. Chemical characteristics, function and location of substituted amino acids, and complexities of the protein target are important considerations in developing NAMs to evaluate chemical susceptibility across species. Environ Toxicol Chem 2023;00:1-17. (c) 2023 University of Wisconsin-Madison. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Anthropogenic activities introduce complex mixtures into aquatic environments, necessitating mixture toxicity evaluation during risk assessment. There are many alternative approaches that can be used to complement traditional techniques for mixture assessment. Our study aimed to demonstrate how these approaches could be employed for mixture evaluation in a target watershed. Evaluations were carried out over 2 years (2017–2018) across 8–11 study sites in the Milwaukee Estuary (WI, USA). Whole mixtures were evaluated on a site‐specific basis by deploying caged fathead minnows ( Pimephales promelas ) alongside composite samplers for 96 h and characterizing chemical composition, in vitro bioactivity of collected water samples, and in vivo effects in whole organisms. Chemicals were grouped based on structure/mode of action, bioactivity, and pharmacological activity. Priority chemicals and mixtures were identified based on their relative contributions to estimated mixture pressure (based on cumulative toxic units) and via predictive assessments (random forest regression). Whole mixture assessments identified target sites for further evaluation including two sites targeted for industrial/urban chemical mixture effects assessment; three target sites for pharmaceutical mixture effects assessment; three target sites for further mixture characterization; and three low‐priority sites. Analyses identified 14 mixtures and 16 chemicals that significantly contributed to cumulative effects, representing high or medium priority targets for further ecotoxicological evaluation, monitoring, or regulatory assessment. Overall, our study represents an important complement to single‐chemical prioritizations, providing a comprehensive evaluation of the cumulative effects of mixtures detected in a target watershed. Furthermore, it demonstrates how different tools and techniques can be used to identify diverse facets of mixture risk and highlights strategies that can be considered in future complex mixture assessments. Environ Toxicol Chem 2023;42:1229–1256. © 2023 SETAC

Computational screening for potentially bioactive molecules using advanced molecular modeling approaches including molecular docking and molecular dynamic simulation is mainstream in certain fields like drug discovery. Significant advances in computationally predicting protein structures from sequence information have also expanded the availability of structures for nonmodel species. Therefore, the objective of the present study was to develop an analysis pipeline to harness the power of these bioinformatics approaches for cross‐species extrapolation for evaluating chemical safety. The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool compares protein‐sequence similarity across species for conservation of known chemical targets, providing an initial line of evidence for extrapolation of toxicity knowledge. However, with the development of structural models from tools like the Iterative Threading ASSEmbly Refinement (ITASSER), analyses of protein structural conservation can be included to add further lines of evidence and generate protein models across species. Models generated through such a pipeline could then be used for advanced molecular modeling approaches in the context of species extrapolation. Two case examples illustrating this pipeline from SeqAPASS sequences to I‐TASSER‐generated protein structures were created for human liver fatty acid–binding protein (LFABP) and androgen receptor (AR). Ninety‐nine LFABP and 268 AR protein models representing diverse species were generated and analyzed for conservation using template modeling (TM)‐align. The results from the structural comparisons were in line with the sequence‐based SeqAPASS workflow, adding further evidence of LFABL and AR conservation across vertebrate species. The present study lays the foundation for expanding the capabilities of the web‐based SeqAPASS tool to include structural comparisons for species extrapolation, facilitating more rapid and efficient toxicological assessments among species with limited or no existing toxicity data. Environ Toxicol Chem 2023;42:463–474. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

The US Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool is a fast, freely available, online screening application that allows researchers and regulators to extrapolate toxicity information across species. For biological targets in model systems such as human cells, mice, rats, and zebrafish, toxicity data are available for a variety of chemicals. Through the evaluation of protein target conservation, this tool can be used to extrapolate data generated from such model systems to thousands of other species lacking toxicity data, yielding predictions of relative intrinsic chemical susceptibility. The latest releases of the tool (versions 2.0-6.1) have incorporated new features that allow for the rapid synthesis, interpretation, and use of the data for publication plus presentation -quality graphics.Among these features are customizable data visualizations and a comprehensive summary report designed to summarize SeqAPASS data for ease of interpretation. This paper describes the protocol to guide users through submitting jobs, navigating the various levels of protein sequence comparisons, and interpreting and displaying the resulting data. New features of SeqAPASS v2.0-6.0 are highlighted. Furthermore, two use-cases focused on transthyretin and opioid receptor protein conservation using this tool are described. Finally, SeqAPASS' strengths and limitations are discussed to define the domain of applicability for the tool and highlight different applications for cross-species extrapolation.

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.

Multiple in vivo test guidelines focusing on the estrogen, androgen, thyroid, and steroidogenesis pathways have been developed and validated for mammals, amphibians, or fish. However, these tests are resource‐intensive and often use a large number of laboratory animals. Developing alternatives for in vivo tests is consistent with the replacement, reduction, and refinement principles for animal welfare considerations, which are supported by increasing mandates to move toward an “animal‐free” testing paradigm worldwide. New approach methodologies (NAMs) hold great promise to identify molecular, cellular, and tissue changes that can be used to predict effects reliably and more efficiently at the individual level (and potentially on populations) while reducing the number of animals used in (eco)toxicological testing for endocrine disruption. In a collaborative effort, experts from government, academia, and industry met in 2020 to discuss the current challenges of testing for endocrine activity assessment for fish and amphibians. Continuing this cross‐sector initiative, our review focuses on the current state of the science regarding the use of NAMs to identify chemical‐induced endocrine effects. The present study highlights the challenges of using NAMs for safety assessment and what work is needed to reduce their uncertainties and increase their acceptance in regulatory processes. We have reviewed the current NAMs available for endocrine activity assessment including in silico, in vitro, and eleutheroembryo models. New approach methodologies can be integrated as part of a weight‐of‐evidence approach for hazard or risk assessment using the adverse outcome pathway framework. The development and utilization of NAMs not only allows for replacement, reduction, and refinement of animal testing but can also provide robust and fit‐for‐purpose methods to identify chemicals acting via endocrine mechanisms. Environ Toxicol Chem 2023;42:757–777. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Several adverse outcome pathways (AOPs) have linked molecular initiating events like aromatase inhibition, androgen receptor (AR) agonism, and estrogen receptor (ER) antagonism to reproductive impairment in adult fish. Estrogen receptor agonists can also cause adverse reproductive effects, however, the early key events (KEs) in an AOP leading to this are mostly unknown. The primary aim of this study was to develop hypotheses regarding the potential mechanisms through which exposure to ER agonists might lead to reproductive impairment in female fish. Mature fathead minnows were exposed to 1 or 10 ng 17 & alpha;-ethynylestradiol (EE2)/L or 10 or 100 & mu;g bisphenol A (BPA)/L for 14 d. The response to EE2 and BPA was contrasted with the effects of 500 ng/L of 1713-trenbolone (TRB), an AR agonist, as well as TRB combined with the low and high concentrations of EE2 or BPA tested individually. Exposure to 10 ng EE2/L, 100 & mu;g BPA/L, TRB, or the various mixtures with TRB caused significant decreases in plasma concentrations of 1713-estradiol. Exposure to TRB alone caused a significant reduction in plasma vitellogenin (VTG), but VTG was unaffected or even increased in females exposed to EE2 or BPA alone or, in most cases, in mixtures with TRB. Over the course of the 14-d exposure, the only treatments that clearly did not affect egg production were 1 ng EE2/L and 10 & mu;g BPA/L. Based on these results and knowledge of hypothalamic-pituitary-gonadal axis function, we hypothesize an AOP whereby decreased production of maturation-inducing steroid leading to impaired oocyte maturation and ovulation, possibly due to negative feedback or direct inhibitory effects of membrane ER activation, could be responsible for causing adverse reproductive impacts in female fish exposed to ER agonists.

The U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program (EDSP) is tasked with assessing chemicals for their potential to perturb endocrine pathways, including those controlled by androgen receptor (AR). To address challenges associated with traditional testing strategies, EDSP is considering in vitro high-throughput screening assays to screen and prioritize chemicals more efficiently. The ability of these assays to accurately reflect chemical interactions in nonmammalian species remains uncertain. Therefore, a goal of the EDSP is to evaluate how broadly results can be extrapolated across taxa. To assess the cross-species conservation of AR-modulated pathways, computational analyses and systematic literature review approaches were used to conduct a comprehensive analysis of existing in silico, in vitro, and in vivo data. First, molecular target conservation was assessed across 585 diverse species based on the structural similarity of ARs. These results indicate that ARs are conserved across vertebrates and are predicted to share similarly susceptibility to chemicals that interact with the human AR. Systematic analysis of over 5000 published manuscripts was used to compile in vitro and in vivo cross-species toxicity data. Assessment of in vitro data indicates conservation of responses occurs across vertebrate ARs, with potential differences in sensitivity. Similarly, in vivo data indicate strong conservation of the AR signaling pathways across vertebrate species, although sensitivity may vary. Overall, this study demonstrates a framework for utilizing bioinformatics and existing data to build weight of evidence for cross-species extrapolation and provides a technical basis for extrapolating hAR-based data to prioritize hazard in nonmammalian vertebrate species.

The ability to predict which chemicals are of concern for environmental safety is dependent, in part, on the ability to extrapolate chemical effects across many species. This work investigated the complementary use of two computational new approach methodologies to support cross-species predictions of chemical susceptibility: the US Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool and Unilever's recently developed Genes to Pathways – Species Conservation Analysis (G2P-SCAN) tool. These stand-alone tools rely on existing biological knowledge to help understand chemical susceptibility and biological pathway conservation across species. The utility and challenges of these combined computational approaches were demonstrated using case examples focused on chemical interactions with peroxisome proliferator activated receptor alpha (PPARα), estrogen receptor 1 (ESR1), and gamma-aminobutyric acid type A receptor subunit alpha (GABRA1). Overall, the biological pathway information enhanced the weight of evidence to support cross-species susceptibility predictions. Through comparisons of relevant molecular and functional data gleaned from adverse outcome pathways (AOPs) to mapped biological pathways, it was possible to gain a toxicological context for various chemical-protein interactions. The information gained through this computational approach could ultimately inform chemical safety assessments by enhancing cross-species predictions of chemical susceptibility. It could also help fulfill a core objective of the AOP framework by potentially expanding the biologically plausible taxonomic domain of applicability of relevant AOPs.