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.

A Comparison of Two Macroinvertebrate Multi-Plate Sampling Methods to Inform Great Lakes Monitoring and Remediation Efforts.

Hester-Dendy (HD) multi-plate samplers have been widely used by state and federal government agencies for bioassessment of water quality through use of macroinvertebrate community data. To help guide remediation and restoration efforts at the Niagara River Great Lakes Area of Concern site, a multi-agency study was conducted in 2014 to assess the contribution of seven major urban tributaries on the US side of the river toward the impairment of the Niagara River. As part of this study, macroinvertebrate communities were sampled using two co-located versions of HD samplers: one version used by the New York State Department of Environmental Conservation (NYSDEC) and another by the US Environmental Protection Agency Office of Research and Development. Samplers were deployed in tributaries in highly developed watersheds with high percent impervious surface. The two sampling methods varied in terms of number and size of plates, between-plate spacing, and deployment method. Comparison of the similarity/grouping of communities with multivariate ordination techniques, Nonmetric Multidimensional Scaling and Multi-Response Permutation Procedure, showed that both methods were able to detect differences in communities at stations, despite some grouping by month and method. The indices and metrics derived from the two HD methods were found to give comparable but not identical assessments of water quality. Despite their differences, the methods were robust with respect to water quality categories derived from indices used nationally (HBI) and by NY state (BAP). For the common richness metrics, total taxa and EPT richness, there was no statistical difference between means from 3 samplings. Some metrics, especially percent tolerant collector-gatherer individuals, did show significant differences at certain stations. Indicator Species Analysis showed some taxa associated with each method. The observed community differences were thought mostly due to the difference in sampler deployment position.

Characterization of polycyclic aromatic hydrocarbons in the Great Lakes Basin using dreissenid mussels.

The National Oceanic and Atmospheric Administration (NOAA), National Centers for Coastal Ocean Science (NCCOS) Mussel Watch Program (MWP), conducts basin-wide monitoring and place-based assessments using dreissenid mussels as bioindicators of chemical contamination in the Laurentian Great Lakes. Polycyclic aromatic hydrocarbons (PAHs) body burden results for the period 2009-2018 were combined into one dataset from multiple MWP studies allowing for a robust characterization of PAH contamination. Patterns in PAH data were identified using descriptive statistics and machine learning techniques. Relationships between total PAH concentration in dreissenid mussel tissue, impervious surface percentages, and PAH relative concentration were identified and used to build a predictive model for the Great Lakes Basin. Significant positive correlation was identified by the Spearman's rank correlation test between total PAH concentration and percent impervious surface. The findings support the paradigm that PAHs are primarily derived from land-based sources. Offshore and riverine locations had the lowest and highest median total PAH concentrations, respectively. PAH assemblages and ratios indicated that pyrogenic sources were more predominant than petrogenic sources and that PAHs at offshore sites exhibited relatively more weathering compared to inshore sites.

Biomarkers of oxidatively induced DNA damage in dreissenid mussels: A genotoxicity assessment tool for the Laurentian Great Lakes.

Activities of fast growing human population are altering freshwater ecosystems, endangering their inhabitants and public health. Organic and trace compounds have a high potential for adverse impacts on aquatic organisms in some Great Lakes tributaries. Toxic compounds in tissues of organisms living in contaminated environments change their metabolism and alter cellular components. We measured oxidatively induced DNA damage in the soft tissues of dreissenid mussels to check on the possible contaminant-induced impact on their DNA. The animals were obtained from archived samples of the National Oceanic and Atmospheric Administration (NOAA) Mussel Watch Program. Mussels were collected from the harbor of Ashtabula River in Ohio, and a reference area located at the Lake Erie shore. Using gas chromatography-tandem mass spectrometry with isotope dilution, we identified and quantified numerous oxidatively modified DNA bases and 8,5'-cyclopurine-2'-deoxynucleosides. We found significant differences in the concentrations of these potentially mutagenic and/or lethal lesions in the DNA of mussels from the harbor as compared to the animals collected at the reference site. These results align NOAA's data showing that elevated concentrations of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and heavy metals were found in mussels within the harbor as compared to mussels collected in the reference site. The measured DNA lesions can be used as biomarkers for identifying DNA damage in mussels from polluted and reference sites. Such biomarkers are needed to identify the bioeffects of contaminants in affected organisms, as well as whether remedial actions have proven successful in reducing observed toxic effects.

The Mussel Watch California pilot study on contaminants of emerging concern (CECs): synthesis and next steps.

A multiagency pilot study on mussels (Mytilus spp.) collected at 68 stations in California revealed that 98% of targeted contaminants of emerging concern (CECs) were infrequently detectable at concentrations ≤ 1 ng/g. Selected chemicals found in commercial and consumer products were more frequently detected at mean concentrations up to 470 ng/g dry wt. The number of CECs detected and their concentrations were greatest for stations categorized as urban or influenced by storm water discharge. Exposure to a broader suite of CECs was also characterized by passive sampling devices (PSDs), with estimated water concentrations of hydrophobic compounds correlated with Mytilus concentrations. The results underscore the need for focused CEC monitoring in coastal ecosystems and suggest that PSDs are complementary to bivalves in assessing water quality. Moreover, the partnership established among participating agencies led to increased spatial coverage, an expanded list of analytes and a more efficient use of available resources.

Refocusing Mussel Watch on contaminants of emerging concern (CECs): the California pilot study (2009-10).

To expand the utility of the Mussel Watch Program, local, regional and state agencies in California partnered with NOAA to design a pilot study that targeted contaminants of emerging concern (CECs). Native mussels (Mytilus spp.) from 68 stations, stratified by land use and discharge scenario, were collected in 2009-10 and analyzed for 167 individual pharmaceuticals, industrial and commercial chemicals and current use pesticides. Passive sampling devices (PSDs) and caged Mytilus were co-deployed to expand the list of CECs, and to assess the ability of PSDs to mimic bioaccumulation by Mytilus. A performance-based quality assurance/quality control (QA/QC) approach was developed to ensure a high degree of data quality, consistency and comparability. Data management and analysis were streamlined and standardized using automated software tools. This pioneering study will help shape future monitoring efforts in California's coastal ecosystems, while serving as a model for monitoring CECs within the region and across the nation.