Linking field-based metabolomics and chemical analyses to prioritize contaminants of emerging concern in the Great Lakes basin

High-efficiency effect-directed analysis (EDA) advancing toxicant identification in aquatic environments: Latest progress and application status

Facing the great threats to ecosystems and human health posed by the continuous release of chemicals into aquatic environments, effect-directed analysis (EDA) has emerged as a powerful tool for identifying causative toxicants. However, traditional EDA shows problems of low-coverage, labor-intensive and low-efficiency. Currently, a number of high-efficiency techniques have been integrated into EDA to improve toxicant identification. In this review, the latest progress and current limitations of high-efficiency EDA, comprising high-coverage effect evaluation, high-resolution fractionation, high-coverage chemical analysis, high-automation causative peak extraction and high-efficiency structure elucidation, are summarized. Specifically, high-resolution fractionation, high-automation data processing algorithms and in silico structure elucidation techniques have been well developed to enhance EDA. While high-coverage effect evaluation and chemical analysis should be further emphasized, especially omics tools and data-independent mass acquisition. For the application status in aquatic environments, high-efficiency EDA is widely applied in surface water and wastewater. Estrogenic, androgenic and aryl hydrocarbon receptor-mediated activities are the most concerning, with causative toxicants showing the typical structural features of steroids and benzenoids. A better understanding of the latest progress and application status of EDA would be beneficial to further advance in the field and greatly support aquatic environment monitoring.

High-Efficiency Effect-Directed Analysis Leveraging Five High Level Advancements: A Critical Review

Organic contaminants are ubiquitous in the environment, with mounting evidence unequivocally connecting them to aquatic toxicity, illness, and increased mortality, underscoring their substantial impacts on ecological security and environmental health. The intricate composition of sample mixtures and uncertain physicochemical features of potential toxic substances pose challenges to identify key toxicants in environmental samples. Effect-directed analysis (EDA), establishing a connection between key toxicants found in environmental samples and associated hazards, enables the identification of toxicants that can streamline research efforts and inform management action. Nevertheless, the advancement of EDA is constrained by the following factors: inadequate extraction and fractionation of environmental samples, limited bioassay endpoints and unknown linkage to higher order impacts, limited coverage of chemical analysis (i.e., high-resolution mass spectrometry, HRMS), and lacking effective linkage between bioassays and chemical analysis. This review proposes five key advancements to enhance the efficiency of EDA in addressing these challenges: (1) multiple adsorbents for comprehensive coverage of chemical extraction, (2) high-resolution microfractionation and multidimensional fractionation for refined fractionation, (3) robust in vivo/vitro bioassays and omics, (4) high-performance configurations for HRMS analysis, and (5) chemical-, data-, and knowledge-driven approaches for streamlined toxicant identification and validation. We envision that future EDA will integrate big data and artificial intelligence based on the development of quantitative omics, cutting-edge multidimensional microfractionation, and ultraperformance MS to identify environmental hazard factors, serving for broader environmental governance.

Evidence of interregional similarity in crayfish metabolomes at reference sites: Progress towards the metabolome as a biomonitoring tool

It has been proposed that biomonitoring may benefit from the use of metabolomics (the study of all small molecules in an organism) to detect sub-lethal organism stress through changes in the metabolite profile (i.e., the metabolome). However, to integrate the metabolome into biomonitoring programs the amount of natural variability among and within populations of indicator taxa must be established prior to generating a reference condition. This study determined variation in the metabolome among ecoregion and stream of origin in the northern crayfish (Faxonius virilis) and if that variation inhibited detection of stressor effects at sites exposed to human activities. We collected crayfish from seven minimally disturbed streams (i.e., reference streams), distributed across three level II ecoregions in central Canada and compared their metabolomes. We found ecoregion and stream origin were poor predictors of crayfish metabolomes. This result suggests crayfish metabolomes were similar, despite differing environmental conditions. Metabolomes of crayfish collected from three stream sites exposed to agricultural activity and municipal wastewater (i.e., test sites) were then compared to the crayfish metabolomes from the seven reference streams. Findings showed that crayfish metabolomes from test sites were strongly differentiated from those at all reference sites. The consistency in the northern crayfish metabolome at the studied reference streams indicates that a single reference condition may effectively detect impacts of human activities across the sampled ecoregions.

Contaminants of Concern and Spatiotemporal Metabolomic Changes in Quagga Mussels (Dreissena bugensis rostriformis) from the Milwaukee Estuary (Wisconsin, USA)

Environmental metabolomics has emerged as a promising technique in the field of biomonitoring and as an indicator of aquatic ecosystem health. In the Milwaukee Estuary (Wisconsin, USA), previous studies have used a nontargeted metabolomic approach to distinguish between zebra mussels (Dreissena polymorpha) collected from sites of varying contamination. To further elucidate the potential effects of contaminants on bivalve health in the Milwaukee Estuary, the present study adopted a caging approach to study the metabolome of quagga mussels (Dreissena bugensis rostriformis) deployed in six sites of varying contamination for 2, 5, or 55 days. Caged mussels were co-deployed with two types of passive sampler (polar organic chemical integrative samplers and semipermeable membrane devices) and data loggers. In conjunction, in situ quagga mussels were collected from the four sites studied previously and analyzed for residues of contaminants and metabolomics using a targeted approach. For the caging study, temporal differences in the metabolomic response were observed with few significant changes observed after 2 and 5 days, but larger differences (up to 97 significantly different metabolites) to the metabolome in all sites after 55 days. A suite of metabolic pathways were altered, including biosynthesis and metabolism of amino acids, and upmodulation of phospholipids at all sites, suggesting a potential biological influence such as gametogenesis. In the caging study, average temperatures appeared to have a greater effect on the metabolome than contaminants, despite a large concentration gradient in polycyclic aromatic hydrocarbons residues measured in passive samplers and mussel tissue. Conversely, significant differences between the metabolome of mussels collected in situ from all three contaminated sites and the offshore reference site were observed. Overall, these findings highlight the importance of contextualizing the effects of environmental conditions and reproductive processes on the metabolome of model organisms to facilitate the wider use of this technique for biomonitoring and environmental health assessments. Environ Toxicol Chem 2024;43:307-323. © 2023 The Authors. 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.

Assessing Contaminants of Emerging Concern in the Great Lakes Ecosystem: A Decade of Method Development and Practical Application

Assessing the ecological risk of contaminants in the field typically involves consideration of a complex mixture of compounds which may or may not be detected via instrumental analyses. Further, there are insufficient data to predict the potential biological effects of many detected compounds, leading to their being characterized as contaminants of emerging concern (CECs). Over the past several years, advances in chemistry, toxicology, and bioinformatics have resulted in a variety of concepts and tools that can enhance the pragmatic assessment of the ecological risk of CECs. The present Focus article describes a 10+- year multiagency effort supported through the U.S. Great Lakes Restoration Initiative to assess the occurrence and implications of CECs in the North American Great Lakes. State-of-the-science methods and models were used to evaluate more than 700 sites in about approximately 200 tributaries across lakes Ontario, Erie, Huron, Michigan, and Superior, sometimes on multiple occasions. Studies featured measurement of up to 500 different target analytes in different environmental matrices, coupled with evaluation of biological effects in resident species, animals from in situ and laboratory exposures, and in vitro systems. Experimental taxa included birds, fish, and a variety of invertebrates, and measured endpoints ranged from molecular to apical responses. Data were integrated and evaluated using a diversity of curated knowledgebases and models with the goal of producing actionable insights for risk assessors and managers charged with evaluating and mitigating the effects of CECs in the Great Lakes. This overview is based on research and data captured in approximately about 90 peer-reviewed journal articles and reports, including approximately about 30 appearing in a virtual issue comprised of highlighted papers published in Environmental Toxicology and Chemistry or Integrated Environmental Assessment and Management. Environ Toxicol Chem 2023;42:2506-2518. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Multi-omic responses of fish exposed to complex chemical mixtures in the Shenandoah River watershed

To evaluate relationships between different anthropogenic impacts, contaminant occurrence, and fish health, we conducted in situ fish exposures across the Shenandoah River watershed at five sites with different land use. Exposure water was analyzed for over 500 chemical constituents, and organismal, metabolomic, and transcriptomic endpoints were measured in fathead minnows. Adverse reproductive outcomes were observed in fish exposed in the upper watershed at both wastewater treatment plant (WWTP) effluent- and agriculture-impacted sites, including decreased gonadosomatic index and altered secondary sex characteristics. This was accompanied with increased mortality at the site most impacted by agricultural activities. Molecular biomarkers of estrogen exposure were unchanged and consistent with low or non-detectable concentrations of common estrogens, indicating that alternative mechanisms were involved in organismal adverse outcomes. Hepatic metabolomic and transcriptomic profiles were altered in a site-specific manner, consistent with variation in land use and contaminant profiles. Integrated biomarker response data were useful for evaluating mechanistic linkages between contaminants and adverse outcomes, suggesting that reproductive endocrine disruption, altered lipid processes, and immunosuppression may have been involved in these organismal impacts. This study demonstrated linkages between human-impact, contaminant occurrence, and exposure effects in the Shenandoah River watershed and showed increased risk of adverse outcomes in fathead minnows exposed to complex mixtures at sites impacted by municipal wastewater discharges and agricultural practices.

Evaluation of Complex Mixture Toxicity in the Milwaukee Estuary (WI, USA) Using Whole-Mixture and Component-Based Evaluation Methods

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.

Contaminants of emerging concern in the Maumee River and their effects on freshwater mussel physiology

Contaminants of emerging concern pose a serious hazard to aquatic wildlife, especially freshwater mussels. The growing number of contaminants in aquatic systems requires scientists and managers to prioritize contaminants that are most likely to elicit a biological response for further monitoring and toxicological testing. The objectives of this study were to identify a sub-category of contaminants most likely to affect Pyganodon grandis and to describe alterations in metabolites and gene expression between various sites. Mussels were deployed in cages for two weeks at four sites along the Maumee River Basin, Ohio, USA. Water samples were analyzed for the presence of 220 contaminants. Hemolymph samples were collected for metabolomics and analyzed using mass spectrometry. Contaminants that significantly covaried with metabolites were identified using partial least-squares (PLS) regression. Tissue samples were collected for transcriptomics, RNA was sequenced using an Illumina HiSeq 2500, and differential expression analysis was performed on assembled transcripts. Of the 220 targeted contaminants, 69 were detected in at least one water sample. Of the 186 metabolites detected in mussel hemolymph, 43 showed significant differences between the four sites. The PLS model identified 44 contaminants that significantly covaried with changes in metabolites. A total of 296 transcripts were differentially expressed between two or more sites, 107 received BLAST hits, and 52 were annotated and assigned to one or more Gene Ontology domains. Our analyses reveal the contaminants that significantly covaried with changes in metabolites and are most likely to negatively impact freshwater mussel health and contribute to ongoing population declines in this group of highly endangered animals. Our integration of "omics" technologies provides a broad and in-depth assessment of the short-term effects of contaminants on organismal physiology. Our findings highlight which contaminants are most likely to be causing these changes and should be prioritized for more extensive toxicological testing.

A Multi-Matrix Metabolomic Approach in Ringed Seals and Beluga Whales to Evaluate Contaminant and Climate-Related Stressors

As a high trophic-level species, ringed seals (Pusa hispida) and beluga whales (Delphinapterus leucas) are particularly vulnerable to elevated concentrations of biomagnifying contaminants, such as polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and mercury (Hg). These species also face climate-change-related impacts which are leading to alterations in their diet and associated contaminant exposure. The metabolomic profile of marine mammal tissues and how it changes to environmental stressors is poorly understood. This study characterizes the profiles of 235 metabolites across plasma, liver, and inner and outer blubber in adult ringed seals and beluga whales and assesses how these profiles change as a consequence of contaminants and dietary changes. In both species, inner and outer blubber were characterized by a greater proportion of lipid classes, whereas the dominant metabolites in liver and plasma were amino acids, carbohydrates, biogenic amines and lysophosphatidylcholines. Several metabolite profiles in ringed seal plasma correlated with δ13C, while metabolite profiles in blubber were affected by hexabromobenzene in ringed seals and PBDEs and Hg in belugas. This study provides insight into inter-matrix similarities and differences across tissues and suggests that plasma and liver are more suitable for studying changes in diet, whereas liver and blubber are more suitable for studying the impacts of contaminants.

Fish metabolome from sub-urban lakes of the Paris area (France) and potential influence of noxious metabolites produced by cyanobacteria

The recent democratization of high-throughput molecular phenotyping allows the rapid expansion of promising untargeted multi-dimensional approaches (e.g. epigenomics, transcriptomics, proteomics, and/or metabolomics). Indeed, these emerging omics tools, processed for ecologically relevant species, may present innovative perspectives for environmental assessments, that could provide early warning of eco(toxico)logical impairments. In a previous pilot study (Sotton et al., Chemosphere 2019), we explore by ¹H NMR the bio-indicative potential of metabolomics analyses on the liver of 2 sentinel fish species (Perca fluviatilis and Lepomis gibbosus) collected in 8 water bodies of the peri-urban Paris' area (France). In the present study, we further investigate on the same samples the high potential of high-throughput UHPLC-HRMS/MS analyses. We show that the LC-MS metabolome investigation allows a clear separation of individuals according to the species, but also according to their respective sampling lakes. Interestingly, similar variations of Perca and Lepomis metabolomes occur locally indicating that site-specific environmental constraints drive the metabolome variations which seem to be influenced by the production of noxious molecules by cyanobacterial blooms in certain lakes. Thus, the development of such reliable environmental metabolomics approaches appears to constitute an innovative bio-indicative tool for the assessment of ecological stress, such as toxigenic cyanobacterial blooms, and aim at being further follow up.

In Silico Methods for Environmental Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives

This chapter aims to introduce the reader to the basic principles of environmental risk assessment of chemicals and highlights the usefulness of tiered approaches within weight of evidence approaches in relation to problem formulation i.e., data availability, time and resource availability. In silico models are then introduced and include quantitative structure-activity relationship (QSAR) models, which support filling data gaps when no chemical property or ecotoxicological data are available. In addition, biologically-based models can be applied in more data rich situations and these include generic or species-specific models such as toxicokinetic-toxicodynamic models, dynamic energy budget models, physiologically based models, and models for ecosystem hazard assessment i.e. species sensitivity distributions and ultimately for landscape assessment i.e. landscape-based modeling approaches. Throughout this chapter, particular attention is given to provide practical examples supporting the application of such in silico models in real-world settings. Future perspectives are discussed to address environmental risk assessment in a more holistic manner particularly for relevant complex questions, such as the risk assessment of multiple stressors and the development of harmonized approaches to ultimately quantify the relative contribution and impact of single chemicals, multiple chemicals and multiple stressors on living organisms.

Pathway-Based Approaches for Assessing Biological Hazards of Complex Mixtures of Contaminants: A Case Study in the Maumee River

Assessment of ecological risks of chemicals in the field usually involves complex mixtures of known and unknown compounds. We describe the use of pathway-based chemical and biological approaches to assess the risk of chemical mixtures in the Maumee River (OH, USA), which receives a variety of agricultural and urban inputs. Fathead minnows (Pimephales promelas) were deployed in cages for 4 d at a gradient of sites along the river and adjoining tributaries in 2012 and during 2 periods (April and June) in 2016, in conjunction with an automated system to collect composite water samples. More than 100 industrial chemicals, pharmaceuticals, and pesticides were detected in water at some of the study sites, with the greatest number typically found near domestic wastewater treatment plants. In 2016, there was an increase in concentrations of several herbicides from April to June at upstream agricultural sites. A comparison of chemical concentrations in site water with single chemical data from vitro high-throughput screening (HTS) assays suggested the potential for perturbation of multiple biological pathways, including several associated with induction or inhibition of different cytochrome P450 (CYP) isozymes. This was consistent with direct effects of water extracts in an HTS assay and induction of hepatic CYPs in caged fish. Targeted in vitro assays and measurements in the caged fish suggested minimal effects on endocrine function (e.g., estrogenicity). A nontargeted mass spectroscopy-based analysis suggested that hepatic endogenous metabolite profiles in caged fish covaried strongly with the occurrence of pesticides and pesticide degradates. These studies demonstrate the application of an integrated suite of measurements to help understand the effects of complex chemical mixtures in the field. Environ Toxicol Chem 2021;40:1098-1122. © 2020 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Disentangling of the ecotoxicological signal using "omics" analyses, a lesson from the survey of the impact of cyanobacterial proliferations on fishes

Omics technologies offer unprecedented perspectives for the rational investigation of complex biological systems. Indeed, omics present the ability of offering an extensive perception of the biochemistry and physiology of the cell and of any perturbing consequences of contaminants through the joint investigation of thousands of molecular responses simultaneously; then it has recently conducted to a fervent attention by research ecotoxicologists. Beyond the presentation of latest advances, exemplified here by omics investigation of cyanobacterial deleterious effects on various fishes (at various experimental and biological scales and with various analytical tools and pipeline), the present review paper re-explores the promising perspectives and also the pitfalls of such holistic investigations of the ecotoxicological response of organisms for environmental assessment.

Gonad metabolomics and blood biochemical analysis reveal differences associated with testicular oocytes in wild largemouth bass (Micropterus salmoides)

Adverse reproductive effects associated with gonadal intersex among freshwater fish could hold considerable implications for population sustainability. Presence of testicular oocytes (TO) is the most common form of intersex and is widespread among centrarchids (sunfishes) of North America and other freshwater teleosts. Placing TO within the toxicological context of adverse outcome pathways (AOPs) to assess ecological risk is a priority for ecotoxicologists due to the association of TO with harmful chemical exposure and adverse reproductive effects in some cases. However, key event relationships between EDC exposure, incidence of TO, and apical outcomes have yet to be fully elucidated - in part due to a lack of knowledge of relationships between intersex gonad physiology and fish health. Understanding the physiological status of intersex fish is critical to assess ecological risk, understand mechanisms of induction, and to establish biomarkers of intersex in fish. In the present study, features of gonad metabolite profiles associated with TO in largemouth bass (LMB, Micropterus salmoides) from an impoundment in Georgia (USA) were determined using GC-MS-based metabolomics. Clinical blood biochemical screens were used to evaluate markers of fish health associated with TO. Results suggest that physiological changes in energy expenditure as well as relatively 'feminized' gonad lipid and protein metabolism may be related to the occurrence of TO in male LMB, and highlight the need to understand relationships between intersex and physical stressors such as elevated temperature and hypoxia. These results provide novel insight to AOPs associated with TO and identify candidate analytes for biomarker discovery.

Mechanistic studies of congener-specific adsorption and bioaccumulation of polycyclic aromatic hydrocarbons and phthalates in soil by novel QSARs

Polycyclic aromatic hydrocarbons (PAHs) and phthalic acid esters (PAEs) which are structurally featured with one or more aromatic skeletons are often regarded as two important groups of organic pollutants due to the widespread distribution and notorious toxic effects in soils. Relative to the great number of structural analogues or congeners detected in soil, however, the soil adsorption and bioaccumulation of PAHs/PAEs by plant is far less studied for the insufficiency of experimental determinations or lack of insights into the inherent structural requirements. To mechanistically evaluate the congener-specific soil adsorption and bioaccumulation for PAHs/PAEs, the quantitative structure-activity relationships (QSARs) were successfully developed by density functional theory (DFT) computation and partial least squares (PLS) analysis. As verified with the higher cumulative variance coefficients and cross-validated correlation coefficients for strong stability, interpretability and predictability, the QSARs could be used for prediction of unknown adsorption potency or bioavailability within the specified applicability domain, respectively. It was indicated by QSAR that the structural requirements of PAHs/PAEs necessary for strengthening the soil adsorption were mainly attributed to the molecular polarizability and the associated dispersion interaction with soil. As regards the bioaccumulation by carrot, the aggravation of spherical polarity change of molecules and the involved electrostatic interaction with soil entity or electron transfer from the highest occupied molecular orbital (HOMO) of PAHs/PAEs was implied to be inherently decisive for the variance of bioavailability among congeners. Based on the holistic view of negative correlation relationship, the soil adsorption seemed to act as the forceful constraint in decreasing the bioaccumulation of PAHs/PAEs and could also be alternatively gauged as the preliminary evaluation of bioavailability and risks on soil ecosystem. It would thus help better understand the soil adsorption and bioaccumulation with the informative mechanistic insights and provide data support for ecological risk assessment of PAHs/PAEs in soils.

N,N-Diethyl-m-Toluamide Exposure at an Environmentally Relevant Concentration Influences River Microbial Community Development

Studies of the South Saskatchewan River confirmed that N,N-diethyl-m-toluamide (DEET) is ubiquitous at 10 to 20 ng/L, whereas in effluent-dominated Wascana Creek, levels of 100 to 450 ng/L were observed. Effects of DEET exposure were assessed in microbial communities using a wide variety of measures. Communities developed in rotating annular reactors with either 100 or 500 ng/L DEET, verified using gas chromatography-mass spectrometry analyses. Microscale analyses indicated that both DEET concentrations resulted in significant (p < 0.05) declines in photosynthetic biomass, whereas bacterial biomass was unaffected. There was no detectable effect of DEET on the levels of chlorophyll a. However, pigment analyses indicated substantial shifts in algal-cyanobacterial community structure, with reductions of green algae and some cyanobacterial groups at 500 ng/L DEET. Protozoan/micrometazoan grazers increased in communities exposed to 500 ng/L, but not 100 ng/L, DEET. Based on thymidine incorporation or utilization of carbon sources, DEET had no significant effects on metabolic activities. Fluorescent lectin-binding analyses showed significant (p < 0.05) changes in glycoconjugate composition at both DEET concentrations, consistent with altered community structure. Principal component cluster analyses of denaturing gradient gel electrophoresis indicated that DEET exposure at either concentration significantly changed the bacterial community (p < 0.05). Analyses based on 16S ribosomal RNA of community composition confirmed changes with DEET exposure, increasing detectable beta-proteobacteria, whereas actinobacteria and acidimicrobia became undetectable. Further, cyanobacteria in the subclass Oscillatoriophycideae were similarly not detected. Thus, DEET can alter microbial community structure and function, supporting the need for further evaluation of its effects in aquatic habitats. Environ Toxicol Chem 2019;38:2414-2425. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Predictive Analysis Using Chemical-Gene Interaction Networks Consistent with Observed Endocrine Activity and Mutagenicity of U.S. Streams

In a recent U.S. Geological Survey/U.S. Environmental Protection Agency study assessing more than 700 organic compounds in 38 streams, in vitro assays indicated generally low estrogen, androgen, and glucocorticoid receptor activities, with 13 surface waters with 17β-estradiol-equivalent (E2Eq) activities greater than a 1-ng/L estimated effects-based trigger value for estrogenic effects in male fish. Among the 36 samples assayed for mutagenicity in the Salmonella bioassay (reported here), 25% had low mutagenic activity and 75% were not mutagenic. Endocrine and mutagenic activities of the water samples were well correlated with each other and with the total number and cumulative concentrations of detected chemical contaminants. To test the predictive utility of knowledge-base-leveraging approaches, site-specific predicted chemical-gene (pCGA) and predicted analogous pathway-linked (pPLA) association networks identified in the Comparative Toxicogenomics Database were compared with observed endocrine/mutagenic bioactivities. We evaluated pCGA/pPLA patterns among sites by cluster analysis and principal component analysis and grouped the pPLA into broad mode-of-action classes. Measured E2eq and mutagenic activities correlated well with predicted pathways. The pPLA analysis also revealed correlations with signaling, metabolic, and regulatory groups, suggesting that other effects pathways may be associated with chemical contaminants in these waters and indicating the need for broader bioassay coverage to assess potential adverse impacts.

Cell-Based Metabolomics for Untargeted Screening and Prioritization of Vertebrate-Active Stressors in Streams Across the United States

The U.S. Geological Survey and the U.S. Environmental Protection Agency have assessed contaminants in 38 streams across the U.S., using an extensive suite of target-chemical analysis methods along with a variety of biological effects tools. Here, we report zebrafish liver (ZFL) cell-culture based NMR metabolomic analysis of these split stream samples. We used this untargeted approach to evaluate the sites according to overall impact on the ZFL metabolome and found that neither the total number of organics detected at the sites, nor their cumulative concentrations, were good predictors of these impacts. Further, we used partial least squares regression to compare ZFL endogenous metabolite profiles to values for 455 potential stressors (organics, inorganics, and physical properties) measured in these waters and found that the profiles covaried with at most 280 of the stressors, which were subsequently ranked into quartiles based on the strength of their covariance. While contaminants of emerging concern (CECs) were well represented in the top, most strongly covarying quartile-suggesting considerable potential for eliciting biological responses at these sites-there was even higher representation of various well-characterized legacy contaminants (e.g., PCBs). These results emphasize the importance of complementing chemical analysis with untargeted bioassays to help focus regulatory efforts on the most significant ecosystem threats.

Metabolomic responses to pre-chlorinated and final effluent wastewater with the addition of a sub-lethal persistent contaminant in Daphnia magna

Consumer products such as perfluorooctanesulfonic acid (PFOS) and pharmaceuticals (PCPPs) enter aquatic ecosystems through inefficient removal during wastewater treatment. Often, the sterilization process of wastewater includes the addition of sodium hypochlorite that can react with PCPPs and other organic matter (i.e., dissolve organic matter) to generate disinfection by-products and can cause the final effluent to be more harmful to aquatic organisms. Here, we exposed Daphnia magna to two stages of wastewater, the pre-chlorinated wastewater (PreCl) and the final effluent. In addition, we exposed D. magna, to the final effluent with a concentration gradient of added PFOS, to investigate if this persistent contaminant altered the toxicity of the final effluent. After 48 h of contaminant exposure, we measured the daphnids metabolic responses to the different stages of wastewater treatment, and with the addition of PFOS, utilizing proton nuclear magnetic resonance spectroscopy and liquid chromatography tandem mass spectrometry. We found few significant changes to the metabolic profile of animals exposed to the PreCl wastewater; however, animals exposed to the final effluent displayed increases in many amino acids and decreases in some sugar metabolites. With the addition of PFOS to the final effluent, the metabolic profile shifted from increased amino acids and decreased sugar metabolites and energy molecules especially at the low and high concentrations of PFOS. Overall, our results demonstrate the metabolome is sensitive to changes in the final effluent that are caused by sterilization, and with the addition of a persistent contaminant, the metabolic profile is further altered.

Concentrations of legacy and new contaminants are related to metabolite profiles in Hudson Bay polar bears

There are very few metabolomics assessments based on field accumulated, uncontrolled contaminant exposures in wildlife, particularly in the Arctic. In the present study, targeted metabolomics and contaminant data were analyzed together to assess potential influences of contaminant exposure on the hepatic metabolome of male polar bears (n = 29) from the southern and western Hudson Bay (SHB and WHB respectively), Canada. The 29 metabolites identified as important in the differentiation of the two subpopulations after partial least squares discriminant analysis (PLS-DA) included phosphatidylcholines (PCs), acylcarnitines (ACs; involved in β-oxidation of fatty acids), and the fatty acid (FA) arachidonic acid (ARA). Perfluorinated alkyl substances, polybrominated diphenyl ethers, dichlorodiphenyldichloroethylene (p,p'-DDE) and some highly chlorinated ortho-polychlorinated biphenyl congeners were greater in the SHB bears and were consistently inversely correlated with discriminating ACs and PCs between the subpopulations. The concentrations of discriminatory, legacy organochlorine pesticides along with one tetrachlorobiphenyl were greater in the WHB and were directly correlated with the VIP-identified ACs and PCs. ARA, glycerophospholipid and several amino acid metabolic pathways were identified as different between subpopulations and/or were impacted. ARA is an important, conditionally essential, dietary n-6 FA and is also part of the inflammation response, and elevated concentrations in the SHB could be related to differences in chronic contaminant exposure and/or differences in diet and/or season, among a number of possible explanations. Dietary tracers (stable isotopes of carbon and nitrogen) were correlated with some discriminatory metabolites, supporting the hypothesis that dietary variation was also an important factor in the differentiation of the subpopulations. The results suggest linkages between contaminant exposure in Hudson Bay polar bears and elements of the hepatic metabolome, particularly those related to lipid metabolism.

Multiresidue analytical method for the determination of 41 multiclass organic pollutants in mussel and fish tissues and biofluids by liquid chromatography coupled to tandem mass spectrometry

In this work, the full optimisation and validation procedure to analyse a wide set of emerging organic contaminants in biotissues (mussel and fish muscle, liver, gills and brain) and biofluids (fish plasma and bile) is described. The target families include artificial sweeteners, industrial products, hormones, pharmaceutical and personal care products, pesticides and phytoestrogens. Different clean-up strategies (hydrophilic-lipophilic-balanced (HLB) solid-phase extraction, Florisil solid-phase extraction and liquid-liquid extraction followed by HLB solid-phase extraction and microextraction based on polyethersulfone polymer) were evaluated for the clean-up of focused ultrasonic solid-liquid extraction (FUSLE) extracts before the analysis by liquid chromatography-triple quadrupole tandem mass spectrometry (LC-QqQ-MS/MS). The methods afforded satisfactory apparent recovery values (71-126%) using isotopically labelled analytes and matrix-matched calibration approach, regardless of the matrix. Method detection limits in the range of 4-48 ng/g and 0.3-111 ng/L were obtained for biotissues and biofluids, respectively. The developed method was applied to determine the uptake and tissue distribution in juvenile gilt-head bream (Sparus aurata) during 7 days in seawater, and unexpectedly, perfluoro-1-butanesulfonate tended to accumulate in liver and, to a lesser extent, in muscle and gills. Furthermore, real mussel samples collected in the Basque coast were also analysed and the presence of the highly consumed valsartan (7 ng/g) and telmisartan (6.8 ng/g) compounds in bivalves is reported for the first time here. Graphical abstract ᅟ.

Sublethal metabolic responses to contaminant mixture toxicity in Daphnia magna

Anthropogenic activity is increasing the presence of contaminants that enter waterways through wastewater effluent and urban and/or agricultural runoff, generally in complex mixtures. Depending on the mode of action of the individual contaminant within the mixture, toxicity can occur due to contaminants having similar or dissimilar modes of action. However, it is unknown how the metabolome responds to sublethal contaminant mixtures in the keystone genus Daphnia. In the present study we examined D. magna metabolic responses to acute sublethal exposure of propranolol, carbamazepine, and perfluorooctanesulfonic acid (PFOS) as well as in binary (propranolol-carbamazepine, propranolol-PFOS, carbamazepine-PFOS) and tertiary mixtures (carbamazepine-propranolol-PFOS), all at 10% of the median lethal concentration of the population (LC50). The metabolome was measured using ¹ H nuclear magnetic resonance (NMR) and characterized using principal component analysis, regression analysis, and fold changes in metabolite relative to the unexposed (control) group. The averaged principal component analysis scores plots revealed that carbamazepine-PFOS and carbamazepine-propranolol-PFOS exposures were significantly different from the control treatment. After normalizing the toxicity of each contaminant, we found that some metabolites responded monotonically, whereas others displayed a nonmonotonic response with increasing toxicity units. The single contaminant exposures and 2 binary mixtures (propranolol-carbamazepine, and propranolol-PFOS) resulted in minimal changes in the identified metabolites, whereas the carbamazepine-PFOS and carbamazepine-propranolol-PFOS displayed increases in several amino acid metabolites and decreases in glucose. Overall, our results highlight the sensitivity of the metabolome to distinguish the composition of the contaminant mixtures, with some mixtures displaying heightened responses versus others. Environ Toxicol Chem 2018;37:2448-2457. © 2018 SETAC.

Evaluation of targeted and untargeted effects-based monitoring tools to assess impacts of contaminants of emerging concern on fish in the South Platte River, CO

Rivers in the arid Western United States face increasing influences from anthropogenic contaminants due to population growth, urbanization, and drought. To better understand and more effectively track the impacts of these contaminants, biologically-based monitoring tools are increasingly being used to complement routine chemical monitoring. This study was initiated to assess the ability of both targeted and untargeted biologically-based monitoring tools to discriminate impacts of two adjacent wastewater treatment plants (WWTPs) on Colorado's South Platte River. A cell-based estrogen assay (in vitro, targeted) determined that water samples collected downstream of the larger of the two WWTPs displayed considerable estrogenic activity in its two separate effluent streams. Hepatic vitellogenin mRNA expression (in vivo, targeted) and NMR-based metabolomic analyses (in vivo, untargeted) from caged male fathead minnows also suggested estrogenic activity downstream of the larger WWTP, but detected significant differences in responses from its two effluent streams. The metabolomic results suggested that these differences were associated with oxidative stress levels. Finally, partial least squares regression was used to explore linkages between the metabolomics responses and the chemical contaminants that were detected at the sites. This analysis, along with univariate statistical approaches, identified significant covariance between the biological endpoints and estrone concentrations, suggesting the importance of this contaminant and recommending increased focus on its presence in the environment. These results underscore the benefits of a combined targeted and untargeted biologically-based monitoring strategy when used alongside contaminant monitoring to more effectively assess ecological impacts of exposures to complex mixtures in surface waters.

Are we closer to the vision? A proposed framework for incorporating omics into environmental assessments

Environmental science has benefited a great deal from omics-based technologies. High-throughput toxicology has defined adverse outcome pathways (AOPs), prioritized chemicals of concern, and identified novel actions of environmental chemicals. While many of these approaches are conducted under rigorous laboratory conditions, a significant challenge has been the interpretation of omics data in "real-world" exposure scenarios. Clarity in the interpretation of these data limits their use in environmental monitoring programs. In recent years, one overarching objective of many has been to address fundamental questions concerning experimental design and the robustness of data collected under the broad umbrella of environmental genomics. These questions include: (1) the likelihood that molecular profiles return to a predefined baseline level following remediation efforts, (2) how reference site selection in an urban environment influences interpretation of omics data and (3) what is the most appropriate species to monitor in the environment from an omics point of view. In addition, inter-genomics studies have been conducted to assess transcriptome reproducibility in toxicology studies. One lesson learned from inter-genomics studies is that there are core molecular networks that can be identified by multiple laboratories using the same platform. This supports the idea that "omics-networks" defined a priori may be a viable approach moving forward for evaluating environmental impacts over time. Both spatial and temporal variability in ecosystem structure is expected to influence molecular responses to environmental stressors, and it is important to recognize how these variables, as well as individual factor (i.e. sex, age, maturation), may confound interpretation of network responses to chemicals. This mini-review synthesizes the progress made towards adopting these tools into environmental monitoring and identifies future challenges to be addressed, as we move into the next era of high throughput sequencing. A conceptual framework for validating and incorporating molecular networks into environmental monitoring programs is proposed. As AOPs become more defined and their potential in environmental monitoring assessments becomes more recognized, the AOP framework may prove to be the conduit between omics and penultimate ecological responses for environmental risk assessments.

Prioritization of Contaminants of Emerging Concern in Wastewater Treatment Plant Discharges Using Chemical:Gene Interactions in Caged Fish

We examined whether contaminants present in surface waters could be prioritized for further assessment by linking the presence of specific chemicals to gene expression changes in exposed fish. Fathead minnows were deployed in cages for 2, 4, or 8 days at three locations near two different wastewater treatment plant discharge sites in the Saint Louis Bay, Duluth, MN and one upstream reference site. The biological impact of 51 chemicals detected in the surface water of 133 targeted chemicals was determined using biochemical endpoints, exposure activity ratios for biological and estrogenic responses, known chemical:gene interactions from biological pathways and knowledge bases, and analysis of the covariance of ovary gene expression with surface water chemistry. Thirty-two chemicals were significantly linked by covariance with expressed genes. No estrogenic impact on biochemical endpoints was observed in male or female minnows. However, bisphenol A (BPA) was identified by chemical:gene covariation as the most impactful estrogenic chemical across all exposure sites. This was consistent with identification of estrogenic effects on gene expression, high BPA exposure activity ratios across all test sites, and historical analysis of the study area. Gene expression analysis also indicated the presence of nontargeted chemicals including chemotherapeutics consistent with a local hospital waste stream. Overall impacts on gene expression appeared to be related to changes in treatment plant function during rain events. This approach appears useful in examining the impacts of complex mixtures on fish and offers a potential route in linking chemical exposure to adverse outcomes that may reduce population sustainability.

An "EAR" on Environmental Surveillance and Monitoring: A Case Study on the Use of Exposure-Activity Ratios (EARs) to Prioritize Sites, Chemicals, and Bioactivities of Concern in Great Lakes Waters

Current environmental monitoring approaches focus primarily on chemical occurrence. However, based on concentration alone, it can be difficult to identify which compounds may be of toxicological concern and should be prioritized for further monitoring, in-depth testing, or management. This can be problematic because toxicological characterization is lacking for many emerging contaminants. New sources of high-throughput screening (HTS) data, such as the ToxCast database, which contains information for over 9000 compounds screened through up to 1100 bioassays, are now available. Integrated analysis of chemical occurrence data with HTS data offers new opportunities to prioritize chemicals, sites, or biological effects for further investigation based on concentrations detected in the environment linked to relative potencies in pathway-based bioassays. As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast effects database were used to calculate exposure-activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Prioritized bioactivities from the EAR analysis were linked to discrete adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts.

Expanded Target-Chemical Analysis Reveals Extensive Mixed-Organic-Contaminant Exposure in U.S. Streams

Surface water from 38 streams nationwide was assessed using 14 target-organic methods (719 compounds). Designed-bioactive anthropogenic contaminants (biocides, pharmaceuticals) comprised 57% of 406 organics detected at least once. The 10 most-frequently detected anthropogenic-organics included eight pesticides (desulfinylfipronil, AMPA, chlorpyrifos, dieldrin, metolachlor, atrazine, CIAT, glyphosate) and two pharmaceuticals (caffeine, metformin) with detection frequencies ranging 66-84% of all sites. Detected contaminant concentrations varied from less than 1 ng L-1 to greater than 10 μg L-1, with 77 and 278 having median detected concentrations greater than 100 ng L-1 and 10 ng L-1, respectively. Cumulative detections and concentrations ranged 4-161 compounds (median 70) and 8.5-102 847 ng L-1, respectively, and correlated significantly with wastewater discharge, watershed development, and toxic release inventory metrics. Log10 concentrations of widely monitored HHCB, triclosan, and carbamazepine explained 71-82% of the variability in the total number of compounds detected (linear regression; p-values: < 0.001-0.012), providing a statistical inference tool for unmonitored contaminants. Due to multiple modes of action, high bioactivity, biorecalcitrance, and direct environment application (pesticides), designed-bioactive organics (median 41 per site at μg L-1 cumulative concentrations) in developed watersheds present aquatic health concerns, given their acknowledged potential for sublethal effects to sensitive species and lifecycle stages at low ng L-1.

Re-evaluating the Significance of Estrone as an Environmental Estrogen

Studies worldwide have demonstrated the occurrence of feminized male fish at sites impacted by human and animal wastes. A variety of chemicals could contribute to this phenomenon, but those receiving the greatest attention in terms of research and monitoring have been 17β-estradiol (β-E2) and 17α-ethinylestradiol, due both to their prevalence in the environment and strong estrogenic potency. A third steroid, estrone (E1), also can occur at high concentrations in surface waters but generally has been of lesser concern due to its relatively lower affinity for vertebrate estrogen receptors. In an initial experiment, male fathead minnow (Pimephales promelas) adults were exposed for 4-d to environmentally relevant levels of waterborne E1, which resulted in plasma β-E2 concentrations similar to those found in reproductively active females. In a second exposure we used ¹³C-labeled E1, together with liquid chromatography-tandem mass spectrometry, to demonstrate that elevated β-E2 measured in the plasma of the male fish was indeed derived from the external environment, most likely via a conversion catalyzed by one or more 17β-hydroxysteroid dehydrogenases. The results of our studies suggest that the potential impact of E1 as an environmental estrogen currently is underestimated.

A Community Multi-Omics Approach towards the Assessment of Surface Water Quality in an Urban River System

A multi-omics approach was applied to an urban river system (the Brisbane River (BR), Queensland, Australia) in order to investigate surface water quality and characterize the bacterial population with respect to water contaminants. To do this, bacterial metagenomic amplicon-sequencing using Illumina next-generation sequencing (NGS) of the V5-V6 hypervariable regions of the 16S rRNA gene and untargeted community metabolomics using gas chromatography coupled with mass spectrometry (GC-MS) were utilized. The multi-omics data, in combination with fecal indicator bacteria (FIB) counts, trace metal concentrations (by inductively coupled plasma mass spectrometry (ICP-MS)) and in-situ water quality measurements collected from various locations along the BR were then used to assess the health of the river ecosystem. Sites sampled represented the transition from less affected (upstream) to polluted (downstream) environments along the BR. Chemometric analysis of the combined datasets indicated a clear separation between the sampled environments. Burkholderiales and Cyanobacteria were common key factors for differentiation of pristine waters. Increased sugar alcohol and short-chain fatty acid production was observed by Actinomycetales and Rhodospirillaceae that are known to form biofilms in urban polluted and brackish waters. Results from this study indicate that a multi-omics approach enables a deep understanding of the health of an aquatic ecosystem, providing insight into the bacterial diversity present and the metabolic output of the population when exposed to environmental contaminants.

Metabolomics for informing adverse outcome pathways: Androgen receptor activation and the pharmaceutical spironolactone

One objective in developing adverse outcome pathways (AOPs) is to connect biological changes that are relevant to risk assessors (i.e., fecundity) to molecular and cellular-level alterations that might be detectable at earlier stages of a chemical exposure. Here, we examined biochemical responses of fathead minnows (Pimephales promelas) to inform an AOP relevant to spironolactone's activation of the androgen receptor, as well as explore other biological impacts possibly unrelated to this receptor. Liquid chromatography with high resolution mass spectrometry (LC-MS) was used to measure changes in endogenous polar metabolites in livers of male and female fish that were exposed to five water concentrations of spironolactone (0, 0.05, 0.5, 5, or 50μgL^-1) for 21days. Metabolite profiles were affected at the two highest concentrations (5 and 50μgL^-1), but not in the lower-level exposures, which agreed with earlier reported results of reduced female fecundity and plasma vitellogenin (VTG) levels. We then applied partial least squares regression to assess whether metabolite alterations covaried with changes in fecundity, VTG gene expression and protein concentrations, and plasma 17β-estradiol and testosterone concentrations. Metabolite profiles significantly covaried with all measured endpoints in females, but only with plasma testosterone in males. Fecundity reductions occurred in parallel with changes in metabolites important in osmoregulation (e.g., betaine), membrane transport (e.g., l-carnitine), and biosynthesis of carnitine (e.g., methionine) and VTG (e.g., glutamate). Based on a network analysis program (i.e., mummichog), spironolactone also affected amino acid, tryptophan, and fatty acid metabolism. Thus, by identifying possible key events related to changes in biochemical pathways, this approach built upon an established AOP describing spironolactone's androgenic properties and highlighted broader implications potentially unrelated to androgen receptor activation, which could form a basis for the development of an AOP network.