Bio-QSARs 2.0: Unlocking a new level of predictive power for machine learning-based ecotoxicity predictions by exploiting chemical and biological information.

Practical, legal, and ethical reasons necessitate the development of methods to replace animal experiments. Computational techniques to acquire information that traditionally relied on animal testing are considered a crucial pillar among these so-called new approach methodologies. In this light, we recently introduced the Bio-QSAR concept for multispecies aquatic toxicity regression tasks. These machine learning models, trained on both chemical and biological information, are capable of both cross-chemical and cross-species predictions. Here, we significantly extend these models' applicability. This was realized by increasing the quantity of training data by a factor of approximately 20, accomplished by considering both additional chemicals and aquatic organisms. Additionally, variable test durations and associated random effects were accommodated by employing a machine learning algorithm that combines tree-boosting with mixed-effects modeling (i.e., Gaussian Process Boosting). We also explored various biological descriptors including Dynamic Energy Budget model parameters, taxonomic distances, as well as genus-specific traits and investigated the inclusion of mode-of-action information. Through these efforts, we developed Bio-QSARs for fish and aquatic invertebrates with exceptional predictive power (R squared of up to 0.92 on independent test sets). Moreover, we made considerable strides to make models applicable for a range of use cases in environmental risk assessment as well as research and development of chemicals. Models were made fully explainable by implementing an algorithmic multicollinearity correction combined with SHapley Additive exPlanations. Furthermore, we devised novel approaches for applicability domain construction that take feature importance into account. We are hence confident these models, which are available via open access, will make a significant contribution towards the implementation of new approach methodologies and ultimately have the potential to support "Green Chemistry" and "Green Toxicology".

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.

Developing prototypes of a modernized approach to assess crop protection chemical safety.

In 2019, the US EPA Administrator issued a directive directing the agency away from reliance on vertebrate tests by 2035, whilst maintaining high-quality human health and environmental risk assessments. There is no accepted approach to achieve this. The decade-long duration of the crop protection (CP) chemical R&D process therefore requires both the invention and application of a modernized approach to those CP chemical projects entering corporate research portfolios by the mid-2020s. We conducted problem formulation discussions with regulatory agency scientists which created the problem statement: "Develop, demonstrate, and implement a modern scientifically sound and robust strategy that applies appropriate and flexible exposure and effects characterization without chemical specific vertebrate tests to reliably address risk, uncertainties, and deficiencies in data and its interpretation with equivalent confidence as do the currently accepted test guidelines and meet the regulatory needs of the agencies". The solution must provide the knowledge needed to confidently conclude human health and environmental protective risk assessments. Exploring this led to a conceptual model involving the creation and parallel submission of a new approach without reliance on chemical-specific vertebrate tests. Assessment in parallel to a traditional package will determine whether it supports some, or all, of the necessary risk management actions. Analysis of any deficiencies will provide valuable feedback to focus development of tools or approaches for subsequent iterations. When found to provide sufficient information, it will form the technical foun­dation of stakeholder engagement to explore acceptance of a new approach to CP chemical risk assessment.

The US EPA, and other regulatory agencies, aim to reduce the use of vertebrate animal tests for assessing risks of crop protection chemicals. There is currently no accepted way to do this. We outline a proposal to perform both the assessment using traditional vertebrate testing and a set of new non-animal methods. These data sets must each be combined with a calculated estimate of user exposure to the pesticide based on its intended use. Comparing the outcome of these two assess­ments will show whether the set of non-animal methods needs to be improved further. When the new approach appears to reliably predict the risks, the different stakeholders must be brought together to assess whether the non-animal methods package is acceptable and can replace the tests on vertebrate animals while maintaining the same level of protection of human health and the environment.

Physiological variables in machine learning QSARs allow for both cross-chemical and cross-species predictions.

A major challenge in ecological risk assessment is estimating chemical-induced effects across taxa without species-specific testing. Where ecotoxicological data may be more challenging to gather, information on species physiology is more available for a broad range of taxa. Physiology is known to drive species sensitivity but understanding about the relative contribution of specific underlying processes is still elusive. Consequently, there remains a need to understand which physiological processes lead to differences in species sensitivity. The objective of our study was to utilize existing knowledge about organismal physiology to both understand and predict differences in species sensitivity. Machine learning models were trained to predict chemical- and species-specific endpoints as a function of both chemical fingerprints/descriptors and physiological properties represented by dynamic energy budget (DEB) parameters. We found that random forest models were able to predict chemical- and species-specific endpoints, and that DEB parameters were relatively important in the models, particularly for invertebrates. Our approach illuminates how physiological properties may drive species sensitivity, which will allow more realistic predictions of effects across species without the need for additional animal testing.

Lipidomics reveals multiple stressor effects (temperature × mitochondrial toxicant) in the zebrafish embryo toxicity test.

Aquatic organisms are exposed to multiple stressors in the environment, including contaminants and rising temperatures due to climate change. The objective of this study was to characterize the effect of increased temperature on chemical-induced toxicity and lipid profiles during embryonic development and hatch in fish. This is important because temperature and many environmental chemicals modulate cellular metabolism and lipids, both of which play integral roles for normal embryonic development. As such, we employed the zebrafish embryo toxicity test for multiple stressor exposures, using the mitochondrial toxicant 2,4-Dinitrophenol (DNP; 6-30 µM) in conjunction with different temperature treatments (28 °C and 33 °C). We found a positive relationship between temperature and lethality at lower DNP concentrations, suggesting temperature stress can increase toxicant sensitivity. Next, we used LC-MS/MS for lipidomics following exposure to sublethal stressor combinations. It was determined that temperature stress at 33 °C augmented DNP-induced effects on the lipidome, including the upregulation of bioactive lipids involved in apoptosis (e.g., ceramides). These data reveal potential implications for climate change and sensitivity to environmental pollution and demonstrate the utility of lipidomics to characterize metabolic pathways underlying toxicity. Data such as these are expected to advance adverse outcome pathways by establishing multiple stressor networks that include intermediate lipid responses.

Integrating Exposure and Effect Distributions with the Ecotoxicity Risk Calculator: Case Studies with Crop Protection Products.

Risk curves describe the relationship between cumulative probability and magnitude of effect and thus express far more information than risk quotients. However, their adoption has remained limited in ecological risk assessment. Therefore, we developed the Ecotoxicity Risk Calculator (ERC) to simplify the derivation of risk curves, which can be used to inform risk management decisions. Case studies are presented with crop protection products, highlighting the utility of the ERC at incorporating various data sources, including surface water modeling estimates, monitoring observations, and species sensitivity distributions. Integr Environ Assess Manag 2021;17:321-330. © 2020 Syngenta Crop Protection, LLC. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Ecotoxico-lipidomics: An emerging concept to understand chemical-metabolic relationships in comparative fish models.

Lipids play an essential role in development, homeostatic functions, immune signaling, reproduction, and growth. Although it is evident that changes in lipid biosynthesis and metabolism can affect organismal physiology, few studies have determined how environmental stressors affect lipid pathways, let alone alter global lipid profiles in fish. This is a significant research gap, as a number of environmental contaminants interact with lipid signaling and metabolic pathways. In this review, we highlight the utility of lipidomics as a tool in environmental toxicology, discussing the current state of knowledge regarding chemical-lipidomic perturbations. As with most oviparous animals, the processing and storage of lipids during oocyte development is also particularly important for embryogenesis in fish. Using largemouth bass (Micropterus salmoides) as an example, transcriptomics data suggest that various chemicals alter lipid metabolism and regulation, highlighting the need for more sophisticated investigations into how toxicants impact lipid responses. We also point out the challenges ahead; these include a lack of understanding about lipid processing and signaling in fish, tissue and species-specific lipid composition, and extraneous factors (e.g., nutrition, temperature) that confound interpretation. For example, toxicant exposure can lead to oxidative stress and lipid peroxidation, resulting in complex lipid byproducts that are challenging to measure. With the emergence of lipidomics in systems toxicology, multi-omics approaches are expected to more clearly define effects on physiology, creating stronger linkages between multiple molecular entities (gene-protein-lipid/metabolite). The development and implementation of novel technologies such as ion mobility-mass spectrometry and ozone-induced dissociation support the complete structural elucidation of lipid molecules. This has implications in the adverse outcome pathway framework, which will enhance the application of lipidomics in toxicology by linking these molecular changes to effects at higher levels of biological organization.

Twenty years of transcriptomics, 17alpha-ethinylestradiol, and fish.

In aquatic toxicology, perhaps no pharmaceutical has been investigated more intensely than 17alpha-ethinylestradiol (EE2), the active ingredient of the birth control pill. At the turn of the century, the fields of comparative endocrinology and endocrine disruption research witnessed the emergence of omics technologies, which were rapidly adapted to characterize potential hazards associated with exposures to environmental estrogens, such as EE2. Since then, significant advances have been made by the scientific community, and as a result, much has been learned about estrogen receptor signaling in fish from environmental xenoestrogens. Vitellogenin, the egg yolk precursor protein, was identified as a major estrogen-responsive gene, establishing itself as the premier biomarker for estrogenic exposures. Omics studies have identified a plethora of estrogen responsive genes, contributing to a wealth of knowledge on estrogen-mediated regulatory networks in teleosts. There have been ~40 studies that report on transcriptome responses to EE2 in a variety of fish species (e.g., zebrafish, fathead minnows, rainbow trout, pipefish, mummichog, stickleback, cod, and others). Data on the liver and testis transcriptomes dominate in the literature and have been the subject of many EE2 studies, yet there remain knowledge gaps for other tissues, such as the spleen, kidney, and pituitary. Inter-laboratory genomics studies have revealed transcriptional networks altered by EE2 treatment in the liver; networks related to amino acid activation and protein folding are increased by EE2 while those related to xenobiotic metabolism, immune system, circulation, and triglyceride storage are suppressed. EE2-responsive networks in other tissues are not as comprehensively defined which is a knowledge gap as regulated networks are expected to be tissue-specific. On the horizon, omics studies for estrogen-mediated effects in fish include: (1) Establishing conceptual frameworks for incorporating estrogen-responsive networks into environmental monitoring programs; (2) Leveraging in vitro and computational toxicology approaches to identify chemicals associated with estrogen receptor-mediated effects in fish (e.g., male vitellogenin production); (3) Discovering new tissue-specific estrogen receptor signaling pathways in fish; and (4) Developing quantitative adverse outcome pathway predictive models for estrogen signaling. As we look ahead, research into EE2 over the past several decades can serve as a template for the array of hormones and endocrine active substances yet to be fully characterized or discovered.

Toward Sustainable Environmental Quality: Priority Research Questions for North America.

Anticipating, identifying, and prioritizing strategic needs represent essential activities by research organizations. Decided benefits emerge when these pursuits engage globally important environment and health goals, including the United Nations Sustainable Development Goals. To this end, horizon scanning efforts can facilitate identification of specific research needs to address grand challenges. We report and discuss 40 priority research questions following engagement of scientists and engineers in North America. These timely questions identify the importance of stimulating innovation and developing new methods, tools, and concepts in environmental chemistry and toxicology to improve assessment and management of chemical contaminants and other diverse environmental stressors. Grand challenges to achieving sustainable management of the environment are becoming increasingly complex and structured by global megatrends, which collectively challenge existing sustainable environmental quality efforts. Transdisciplinary, systems-based approaches will be required to define and avoid adverse biological effects across temporal and spatial gradients. Similarly, coordinated research activities among organizations within and among countries are necessary to address the priority research needs reported here. Acquiring answers to these 40 research questions will not be trivial, but doing so promises to advance sustainable environmental quality in the 21st century. Environ Toxicol Chem 2019;38:1606-1624. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Linking Mitochondrial Dysfunction to Organismal and Population Health in the Context of Environmental Pollutants: Progress and Considerations for Mitochondrial Adverse Outcome Pathways.

Mitochondria are key targets of many environmental contaminants, because specific chemicals can interact directly with mitochondrial proteins, lipids, and ribonucleic acids. These direct interactions serve as molecular initiating events that impede adenosine triphosphate production and other critical functions that mitochondria serve within the cell (e.g., calcium and metal homeostasis, apoptosis, immune signaling, redox balance). A limited but growing number of adverse outcome pathways (AOPs) have been proposed to associate mitochondrial dysfunction with effects at organismal and population levels. These pathways involve key events such as altered membrane potential, mitochondrial fission/fusion, and mitochondrial DNA damage, among others. The present critical review and analysis reveals current progress on AOPs involving mitochondrial dysfunction, and, using a network-based computational approach, identifies the localization of mitochondrial molecular initiating events and key events within multiple existing AOPs. We also present 2 case studies, the first examining the interaction between mitochondria and immunotoxicity, and the second examining the role of early mitochondrial dysfunction in the context of behavior (i.e., locomotor activity). We discuss limitations in our current understanding of mitochondrial AOPs and highlight opportunities for clarifying their details. Advancing our knowledge of key event relationships within the AOP framework will require high-throughput datasets that permit the development and testing of chemical-agnostic AOPs, as well as high-resolution research that will enhance the mechanistic testing and validation of these key event relationships. Given the wide range of chemicals that affect mitochondria, and the centrality of energy production and signaling to ecologically important outcomes such as pathogen defense, homeostasis, growth, and reproduction, a better understanding of mitochondrial AOPs is expected to play a significant, if not central, role in environmental toxicology. Environ Toxicol Chem 2019;38:1625-1634. © 2019 SETAC.

Computational in Vitro Toxicology Uncovers Chemical Structures Impairing Mitochondrial Membrane Potential.

Technological advances in molecular biology have enabled high-throughput screening (HTS) of large chemical libraries. These approaches have provided valuable toxicity data for many physiological responses, including mitochondrial dysfunction. While several quantitative structure-activity relationship (QSAR) models have been developed for mitochondrial dysfunction, there remains a need to identify specific chemical features associated with this response. Thus, the objective of this study was to identify chemical structures associated with altered mitochondrial membrane potential (MMP). To achieve this, we developed computational models to examine the relationship between specific chemotypes (e.g., ToxPrints) and bioactivity in ToxCast/Tox21 HTS assays for altered MMP. The analysis revealed that the "bond:COH_alcohol_aromatic", "bond:COH_alcohol_aromatic_phenol", and "ring:aromatic_benzene" ToxPrints had the highest average correlations (phi coefficient) with ToxCast/Tox21 assay component endpoints for decreased MMP. These structures also constituted a "core" group of ToxPrints for decreased MMP in a force-directed network model and were the most important chemotypes in a random forest (RF) classification model for the "TOX21_MMP_ratio_down" assay component endpoint. Based on multiple lines of evidence, these structures, which are present in numerous chemicals (e.g., aromatic hydrocarbons, pesticides, and industrial chemicals) are likely involved in mitochondrial dysfunction. Because of the hierarchical structure of ToxPrints, these chemotypes were highly convergent and, when excluded from training data, had limited effects on the classification performance as related structures compensated for predictor loss. These results highlight the flexibility of the RF algorithm and ToxPrints for QSAR modeling, which is useful to identify chemicals affecting mitochondrial function.

Toward an adverse outcome pathway for impaired growth: Mitochondrial dysfunction impairs growth in early life stages of the fathead minnow (Pimephales promelas).

Chemical contaminants present in the environment can affect mitochondrial bioenergetics in aquatic organisms and can have substantial effects on individual fitness. As early life stages of fish are particularly vulnerable to environmental contaminants, they are ideal models for examining the relationship between impaired mitochondrial bioenergetics (ATP-dependent respiration, basal oxidative respiration) and apical endpoints such as growth. Here, early life stages of the fathead minnow (Pimephales promelas), an ecologically relevant North American species, were used to investigate the relationship between mitochondrial bioenergetics and growth following perturbation with model mitochondrial toxicants 2,4-dinitrophenol and octylamine. Fathead minnows were exposed to 2,4-dinitrophenol and octylamine at 3 concentrations for 24 h and endpoints related to mitochondrial bioenergetics were measured with the Agilent Seahorse XFe24 Bioanalyzer. In order to link changes in mitochondrial bioenergetics to growth, fathead minnows were exposed to the same chemical contaminants for 7-14 days and growth was measured by measuring total length on a weekly basis. There was a significant correlation between decrease in average length at 14 days and basal respiration (r = 0.997, p = 0.050, n = 3), as well as maximal respiration (r = 0.998, p-value = 0.043, n = 3) for embryos exposed to 2,4 dinitrophenol. For octylamine, ATP production was highly correlated with average length at 7 days (p-value = 0.1) and spare respiratory capacity and average length at 14 days were highly correlated (p-value = 0.1). These data improve understanding of how mitochondrial toxicants impair growth in fish larvae and may be useful for developing an adverse outcome pathway for growth.

How well can carcinogenicity be predicted by high throughput "characteristics of carcinogens" mechanistic data?

IARC has begun using ToxCast/Tox21 data in efforts to represent key characteristics of carcinogens to organize and weigh mechanistic evidence in cancer hazard determinations and this implicit inference approach also is being considered by USEPA. To determine how well ToxCast/Tox21 data can explicitly predict cancer hazard, this approach was evaluated with statistical analyses and machine learning prediction algorithms. Substances USEPA previously classified as having cancer hazard potential were designated as positives and substances not posing a carcinogenic hazard were designated as negatives. Then ToxCast/Tox21 data were analyzed both with and without adjusting for the cytotoxicity burst effect commonly observed in such assays. Using the same assignments as IARC of ToxCast/Tox21 assays to the seven key characteristics of carcinogens, the ability to predict cancer hazard for each key characteristic, alone or in combination, was found to be no better than chance. Hence, we have little scientific confidence in IARC's inference models derived from current ToxCast/Tox21 assays for key characteristics to predict cancer. This finding supports the need for a more rigorous mode-of-action pathway-based framework to organize, evaluate, and integrate mechanistic evidence with animal toxicity, epidemiological investigations, and knowledge of exposure and dosimetry to evaluate potential carcinogenic hazards and risks to humans.

Computational analysis of the ToxCast estrogen receptor agonist assays to predict vitellogenin induction by chemicals in male fish.

Endocrine disruptors, especially estrogen receptor (ER) agonists, have received considerable research attention. While there are several mechanistic endpoints for ER agonism in the Endocrine Disruptor Screening Program, there have been growing efforts to develop high-throughput screening assays and computational models to reduce testing cost, time, and animal use. For example, there are 16 ER agonist assays and an integrated computational model in ToxCast. In the present study, we examined the relationship between ToxCast ER agonist assays and model activity to male vitellogenin induction in the Fish-Short Term Reproduction Assay. It was found 15/16 of the assays significantly predicted potency ranks for 10 common ER agonists, and 7/16 of the assays had a significant linear correlation. The integrated model also provided comparable performance to most assays. Thus, the ToxCast ER agonist assays and model may be useful to identify endocrine disruptors and predict reproductive outcomes in fish.

Recommended approaches to the scientific evaluation of ecotoxicological hazards and risks of endocrine-active substances.

A SETAC Pellston Workshop® "Environmental Hazard and Risk Assessment Approaches for Endocrine-Active Substances (EHRA)" was held in February 2016 in Pensacola, Florida, USA. The primary objective of the workshop was to provide advice, based on current scientific understanding, to regulators and policy makers; the aim being to make considered, informed decisions on whether to select an ecotoxicological hazard- or a risk-based approach for regulating a given endocrine-disrupting substance (EDS) under review. The workshop additionally considered recent developments in the identification of EDS. Case studies were undertaken on 6 endocrine-active substances (EAS-not necessarily proven EDS, but substances known to interact directly with the endocrine system) that are representative of a range of perturbations of the endocrine system and considered to be data rich in relevant information at multiple biological levels of organization for 1 or more ecologically relevant taxa. The substances selected were 17α-ethinylestradiol, perchlorate, propiconazole, 17ß-trenbolone, tributyltin, and vinclozolin. The 6 case studies were not comprehensive safety evaluations but provided foundations for clarifying key issues and procedures that should be considered when assessing the ecotoxicological hazards and risks of EAS and EDS. The workshop also highlighted areas of scientific uncertainty, and made specific recommendations for research and methods-development to resolve some of the identified issues. The present paper provides broad guidance for scientists in regulatory authorities, industry, and academia on issues likely to arise during the ecotoxicological hazard and risk assessment of EAS and EDS. The primary conclusion of this paper, and of the SETAC Pellston Workshop on which it is based, is that if data on environmental exposure, effects on sensitive species and life-stages, delayed effects, and effects at low concentrations are robust, initiating environmental risk assessment of EDS is scientifically sound and sufficiently reliable and protective of the environment. In the absence of such data, assessment on the basis of hazard is scientifically justified until such time as relevant new information is available. Integr Environ Assess Manag 2017;13:267-279. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Challenges in assigning endocrine-specific modes of action: Recommendations for researchers and regulators.

As regulatory programs evaluate substances for their endocrine-disrupting properties, careful study design and data interpretation are needed to distinguish between responses that are truly endocrine specific and those that are not. This is particularly important in regulatory environments where criteria are under development to identify endocrine-disrupting properties to enable hazard-based regulation. Irrespective of these processes, most jurisdictions use the World Health Organization/International Programme on Chemical Safety definition of an endocrine disruptor, requiring that a substance is demonstrated to cause a change in endocrine function that consequently leads to an adverse effect in an intact organism. Such a definition is broad, and at its most cautious might capture many general mechanisms that would not specifically denote an endocrine disruptor. In addition, endocrine responses may be adaptive in nature, designed to maintain homeostasis rather than induce an irreversible adverse effect. The likelihood of indirect effects is increased in (eco)toxicological studies that require the use of maximum tolerated concentrations or doses, which must produce some adverse effect. The misidentification of indirect effects as truly endocrine mediated has serious consequences for prompting animal- and resource-intensive testing and regulatory consequences. To minimize the risk for misidentification, an objective and transparent weight-of-evidence procedure based on biological plausibility, essentiality, and empirical evidence of key events in an adverse outcome pathway is recommended to describe the modes of action that may be involved in toxic responses in nontarget organisms. Confounding factors such as systemic toxicity, general stress, and infection can add complexity to such an evaluation and should be considered in the weight of evidence. A recommended set of questions is proffered to help guide researchers and regulators in discerning endocrine and nonendocrine responses. Although many examples provided in this study are based on ecotoxicology, the majority of the concepts and processes are applicable to both environmental and human health assessments. Integr Environ Assess Manag 2017;13:280-292. © 2016 SETAC.

The influence of breeding strategy, reproductive stage, and tissue type on transcript variability in fish.

Characterizing factors that contribute to transcript variability is necessary before molecular endpoints are widely adopted as biomarkers for environmental monitoring programs and risk assessment. Here, we employed a meta-analysis approach to understand how reproductive stage, breeding strategy, and tissue type influence transcript variability in multiple fish species. Transcript abundance from the scientific literature was examined by method of quantification (qPCR or microarray), and the extracted data were used to calculate the coefficient of variation (CoV) for each transcript. Based on qPCR data, variability in the abundance of estrogen receptor 1 and hydroxysteroid dehydrogenase 3b was dependent upon reproductive stage and/or breeding strategy in the female ovaries. The variability of other transcripts in the steroid biosynthesis pathway as well as other steroid receptors did not depend upon sex, breeding strategy, or reproductive stage. Variability estimates were used to determine sample size requirements for detecting specific critical effects in molecular endpoints. It was estimated that only 37.8% of published studies used in the qPCR meta-analysis had sufficient experimental power (0.8) to detect a 2-fold expression difference in a transcript. To build upon these analyses, microarray data were used to measure overall variability of the transcriptome, and it was determined that the vitellogenic reproductive stage had the lowest transcriptomic variability compared to other reproductive stages. This variability was lower in a single-spawning species (largemouth bass) compared to a multiple-spawner (fathead minnow). Following this, a meta-analysis of 777 microarrays for multiple fish species was performed to determine the influence of breeding strategy and tissue type on transcriptomic variability. In this analysis, single-spawning fish showed lower gonadal and hepatic transcriptome variability compared to multiple-spawning species. Thus, these species may be more appropriate for sampling molecular endpoints in monitoring programs. Transcript variability was lowest in the brain, followed by the gonads and liver, which may reflect fewer morphological changes relative to these tissues. The results of this study should be used in conjunction with other experimental and sampling recommendations to optimize the use of molecular endpoints in regulatory ecotoxicology and environmental monitoring programs.

Comparative endpoint sensitivity of in vitro estrogen agonist assays.

Environmental and human health implications of endocrine disrupting chemicals (EDCs), particularly xenoestrogens, have received extensive study. In vitro assays are increasingly employed as diagnostic tools to comparatively evaluate chemicals, whole effluent toxicity and surface water quality, and to identify causative EDCs during toxicity identification evaluations. Recently, the U.S. Environmental Protection Agency (USEPA) initiated ToxCast under the Tox21 program to generate novel bioactivity data through high throughput screening. This information is useful for prioritizing chemicals requiring additional hazard information, including endocrine active chemicals. Though multiple in vitro and in vivo techniques have been developed to assess estrogen agonist activity, the relative endpoint sensitivity of these approaches and agreement of their conclusions remain unclear during environmental diagnostic applications. Probabilistic hazard assessment (PHA) approaches, including chemical toxicity distributions (CTD), are useful for understanding the relative sensitivity of endpoints associated with in vitro and in vivo toxicity assays by predicting the likelihood of chemicals eliciting undesirable outcomes at or above environmentally relevant concentrations. In the present study, PHAs were employed to examine the comparative endpoint sensitivity of 16 in vitro assays for estrogen agonist activity using a diverse group of compounds from the USEPA ToxCast dataset. Reporter gene assays were generally observed to possess greater endpoint sensitivity than other assay types, and the Tox21 ERa LUC BG1 Agonist assay was identified as the most sensitive in vitro endpoint for detecting an estrogenic response. When the sensitivity of this most sensitive ToxCast in vitro endpoint was compared to the human MCF-7 cell proliferation assay, a common in vitro model for biomedical and environmental monitoring applications, the ERa LUC BG1 assay was several orders of magnitude less sensitive than MCF-7. These observations highlight the importance of employing multiple assays with various molecular initiation and signaling events to inform selection, application, and interpretation of in vitro endpoint responses during future environmental diagnostic applications.