Expanding non-invasive approaches for fish-health monitoring: A survey of the epidermal mucous metabolomes of phylogenetically diverse freshwater fish species.

There is a pressing need for more-holistic approaches to fisheries assessments along with growing demand to reduce the health impacts of sample collections. Metabolomic tools enable the use of sample matrices that can be collected with minimal impact on the organism (e.g., blood, urine, and mucus) and provide high-throughput, untargeted biochemical information without the requirement of a sequenced genome. These qualities make metabolomics ideal for monitoring a wide range of fish species, particularly those under protected status. In the current study, we surveyed the relative abundances of 120 endogenous metabolites in epidermal mucus across eight freshwater fish species belonging to seven phylogenetic orders. Principal component analysis was used to provide an overview of the data set, revealing strong interspecies relationships in the epidermal mucous metabolome. Normalized relative abundances of individual endogenous metabolites were then used to identify commonalities across multiple species, as well as those metabolites that showed notable species specificity. For example, taurine was measured in high relative abundance in the epidermal mucus of common carp (Cyprinus carpio), northern pike (Esox lucius), golden shiner (Notemigonus crysoleucas), rainbow trout (Oncorhynchus mykiss), and rainbow smelt (Osmerus mordax), whereas γ-amino butyric acid (GABA) exhibited a uniquely high relative abundance in flathead catfish (Pylodictis olivaris). Finally, hierarchical cluster analysis was used to evaluate species relatedness as characterized by both the epidermal mucous metabolome (phenotype) and genetic phylogeny (genotype). This comparison revealed species for which relatedness in the epidermal mucous metabolome composition closely aligns with phylogenetic relatedness (e.g., N. crysoleucas and C. carpio), as well as species for which these two measures are not well aligned (e.g., P. olivaris and Polyodon spathula). These, and other findings reported here, highlight novel areas for future research with fish, including development of epidermal mucous-based markers for non-invasive health monitoring, sex determination, and hypoxia tolerance.

The Eco-Exposome Concept: Supporting an Integrated Assessment of Mixtures of Environmental Chemicals.

Organisms are exposed to ever-changing complex mixtures of chemicals over the course of their lifetime. The need to more comprehensively describe this exposure and relate it to adverse health effects has led to formulation of the exposome concept in human toxicology. Whether this concept has utility in the context of environmental hazard and risk assessment has not been discussed in detail. In this Critical Perspective, we propose-by analogy to the human exposome-to define the eco-exposome as the totality of the internal exposure (anthropogenic and natural chemicals, their biotransformation products or adducts, and endogenous signaling molecules that may be sensitive to an anthropogenic chemical exposure) over the lifetime of an ecologically relevant organism. We describe how targeted and nontargeted chemical analyses and bioassays can be employed to characterize this exposure and discuss how the adverse outcome pathway concept could be used to link this exposure to adverse effects. Available methods, their limitations, and/or requirement for improvements for practical application of the eco-exposome concept are discussed. Even though analysis of the eco-exposome can be resource-intensive and challenging, new approaches and technologies make this assessment increasingly feasible. Furthermore, an improved understanding of mechanistic relationships between external chemical exposure(s), internal chemical exposure(s), and biological effects could result in the development of proxies, that is, relatively simple chemical and biological measurements that could be used to complement internal exposure assessment or infer the internal exposure when it is difficult to measure. Environ Toxicol Chem 2022;41:30-45. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The Role of Omics in the Application of Adverse Outcome Pathways for Chemical Risk Assessment.

In conjunction with the second International Environmental Omics Symposium (iEOS) conference, held at the University of Liverpool (United Kingdom) in September 2014, a workshop was held to bring together experts in toxicology and regulatory science from academia, government and industry. The purpose of the workshop was to review the specific roles that high-content omics datasets (eg, transcriptomics, metabolomics, lipidomics, and proteomics) can hold within the adverse outcome pathway (AOP) framework for supporting ecological and human health risk assessments. In light of the growing number of examples of the application of omics data in the context of ecological risk assessment, we considered how omics datasets might continue to support the AOP framework. In particular, the role of omics in identifying potential AOP molecular initiating events and providing supportive evidence of key events at different levels of biological organization and across taxonomic groups was discussed. Areas with potential for short and medium-term breakthroughs were also discussed, such as providing mechanistic evidence to support chemical read-across, providing weight of evidence information for mode of action assignment, understanding biological networks, and developing robust extrapolations of species-sensitivity. Key challenges that need to be addressed were considered, including the need for a cohesive approach towards experimental design, the lack of a mutually agreed framework to quantitatively link genes and pathways to key events, and the need for better interpretation of chemically induced changes at the molecular level. This article was developed to provide an overview of ecological risk assessment process and a perspective on how high content molecular-level datasets can support the future of assessment procedures through the AOP framework.

Use of gene expression, biochemical and metabolite profiles to enhance exposure and effects assessment of the model androgen 17ß-trenbolone in fish.

The impact of exposure by water to a model androgen, 17ß-trenbolone (TRB), was assessed in fathead minnows using an integrated molecular approach. This included classical measures of endocrine exposure such as impacts on testosterone (T), 17ß-estradiol (E2), and vitellogenin (VTG) concentrations in plasma, as well as determination of effects on the hepatic metabolome using proton nuclear magnetic resonance spectroscopy. In addition, the rates of production of T and E2 in ovary explants were measured, as were changes in a number of ovarian gene transcripts hypothesized to be relevant to androgen exposure. A temporally intensive 16-d test design was used to assess responses both during and after the TRB exposure (i.e., depuration/recovery). This strategy revealed time-dependent responses in females (little impact was seen in the males), in which changes in T and E2 production in the ovary, as well as levels in plasma, declined rapidly (within 1 d), followed shortly by a return to control levels. Gene expression measurements revealed dynamic control of transcript levels in the ovary and suggested potential mechanisms for compensation during the exposure phase of the test. Proton nuclear magnetic resonance spectroscopy revealed a number of hepatic metabolite changes that exhibited strong time and dose dependence. Furthermore, TRB appeared to induce the hepatic metabolome of females to become more like that of males at both high test concentrations of TRB (472 ng/L) and more environmentally relevant levels (33 ng/L).

A computational model of the hypothalamic-pituitary-gonadal axis in male fathead minnows exposed to 17alpha-ethinylestradiol and 17beta-estradiol.

Estrogenic chemicals in the aquatic environment have been shown to cause a variety of reproductive anomalies in fish including full sex reversal, intersex, and altered population sex ratios. Two estrogens found in the aquatic environment, 17alpha-ethinylestradiol (EE(2)) and 17beta-estradiol (E(2)), have been measured in wastewater treatment effluents and have been shown to cause adverse effects in fish. To further our understanding of how estrogen exposure affects reproductive endpoints in the male fathead minnow (FHM, Pimephales promelas), a physiologically based computational model was developed of the hypothalamic-pituitary-gonadal (HPG) axis. Apical reproductive endpoints in the model include plasma steroid hormone and vitellogenin concentrations. Using Markov chain Monte Carlo simulation, the model was calibrated with data from unexposed FHM, and FHM exposed to EE(2) and E(2). Independent experimental data sets were used to evaluate model predictions. We found good agreement between our model predictions and a variety of measured reproductive endpoints, although the model underpredicts unexposed FHM reproductive endpoint variances, and overpredicts variances in estrogen-exposed FHM. We conclude that this model provides a robust representation of the HPG axis in male FHM.