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Revised fish aging techniques improve fish contaminant trend analyses in the face of changing Great Lakes food webs.

ABSTRACT: Incorporation of fish age into the assessment of status and trends for persistent, bioaccumulative and toxic chemicals in the Great Lakes has become an important step for the U.S. EPA's Great Lakes Fish Monitoring and Surveillance Program (GLFMSP). A slowing in the rate of decline for total PCBs in Lake Huron beginning in 2000, led the Program to complete a retrospective analysis to assess how chemical contamination may be influenced by fish age. Analytical results suggest that fish age is an important variable when assessing contaminant trends and that the Program needed to revise its compositing scheme to group fish according to age, rather than by length, prior to homogenization and chemical analysis. An Interlaboratory comparison study of multiple age structures was performed to identify the most appropriate age estimation structure for the Program. The lake trout (Salvelinus namaycush) maxillae was selected, over the otolith, as the most precise, accurate, and rapidly assessed structure for the Program when compared between laboratories and against the known age from the coded wire tag (CWT). Age-normalization practices can now be implemented when assessing contaminant concentrations and trends for the GLFMSP.

SUBMITTER: Murphy EW

PROVIDER: S-EPMC6178836 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Revised fish aging techniques improve fish contaminant trend analyses in the face of changing Great Lakes food webs.

Murphy Elizabeth W EW Smith Marian L ML He Ji X JX Wellenkamp William W Barr Edward E Downey Philip C PC Miller Kenneth M KM Meyer Kathryn A KA

Journal of Great Lakes research 20180801 4

Incorporation of fish age into the assessment of status and trends for persistent, bioaccumulative and toxic chemicals in the Great Lakes has become an important step for the U.S. EPA's Great Lakes Fish Monitoring and Surveillance Program (GLFMSP). A slowing in the rate of decline for total PCBs in Lake Huron beginning in 2000, led the Program to complete a retrospective analysis to assess how chemical contamination may be influenced by fish age. Analytical results suggest that fish age is an im ...[more]

PMID: 30319172

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Project description:In a study of 44 diverse sampling sites across 16 Great Lakes tributaries, 110 pharmaceuticals were detected of 257 monitored. The present study evaluated the ecological relevance of detected chemicals and identified heavily impacted areas to help inform resource managers and guide future investigations. Ten pharmaceuticals (caffeine, nicotine, albuterol, sulfamethoxazole, venlafaxine, acetaminophen, carbamazepine, gemfibrozil, metoprolol, and thiabendazole) were distinguished as having the greatest potential for biological effects based on comparison to screening-level benchmarks derived using information from two biological effects databases, the ECOTOX Knowledgebase and the ToxCast database. Available evidence did not suggest substantial concern for 75% of the monitored pharmaceuticals, including 147 undetected pharmaceuticals and 49 pharmaceuticals with screening-level alternative benchmarks. However, because of a lack of biological effects information, screening values were not available for 51 detected pharmaceuticals. Samples containing the greatest pharmaceutical concentrations and having the highest detection frequencies were from Lake Erie, southern Lake Michigan, and Lake Huron tributaries. Samples collected during low-flow periods had higher pharmaceutical concentrations than those collected during increased-flow periods. The wastewater-treatment plant effluent content in streams correlated positively with pharmaceutical concentrations. However, deviation from this correlation demonstrated that secondary factors, such as multiple pharmaceutical sources, were likely present at some sites. Further research could investigate high-priority pharmaceuticals as well as those for which alternative benchmarks could not be developed. Environ Toxicol Chem 2022;41:2221-2239. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Project description:Today, many contaminants of emerging concern can be measured in waters across the United States, including the tributaries of the Great Lakes. However, just because the chemicals can be measured does not mean that they necessarily result in harm to fish and other aquatic species. Complicating risk assessment in these waters is the fact that aquatic species are encountering the chemicals as mixtures, which may have additive or synergistic risks that cannot be calculated using single chemical hazard and concentration-response information. We developed an in vitro effects-based screening approach to help us predict potential liver toxicity and cancer in aquatic organisms using water from specific Great Lakes tributaries: St. Louis River (MN), Bad River (WI), Fox River (WI), Manitowoc River (WI), Milwaukee River (WI), Indiana Harbor Canal (IN), St. Joseph River (MI), Grand River (MI), Clinton River (MI), River Rouge (MI), Maumee River (OH), Vermilion River (OH), Cuyahoga River (OH), Genesee River (NY), and Oswego River (NY). We exposed HepG2 cells for 48hrs to medium spiked with either field collected water (final concentration of environmental samples in the exposure medium were 75% of the field-collected water samples) or purified water. Using a deep neural network we clustered our collection sites from each tributary based on water chemistry. We also performed high throughput transcriptomics on the RNA obtained from the HepG2 cells. We used the transcriptomics data with our Bayesian Inferene for Sustance and Chemical Toxicity (BISCT) Bayesian Network for Steatosis to predict the probability of the field samples yielding a gene expression pattern consistent with predicting steatosis as an outcome. Surprisingly, we found that the probability of steatosis did not correspond to the surface water chemistry clustering. Our analysis suggests that chemical signatures are not informative in predicting biological effects. Furthermore, recent reports published after we obtained our samples, suggest that chemical levels in the sediment may be more relevant for predicting potential biological effects in the fish species developing tumors in the Great Lakes basin.

Dataset Information

Revised fish aging techniques improve fish contaminant trend analyses in the face of changing Great Lakes food webs.

Publications

Revised fish aging techniques improve fish contaminant trend analyses in the face of changing Great Lakes food webs.

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