Dataset Information

Contaminants of emerging concern in tributaries to the Laurentian Great Lakes: II. Biological consequences of exposure.

ABSTRACT: The Laurentian Great Lakes contain one fifth of the world's surface freshwater and have been impacted by human activity since the Industrial Revolution. In addition to legacy contaminants, nitrification and invasive species, this aquatic ecosystem is also the recipient of Contaminants of Emerging Concern (CECs) with poorly understood biological consequences. In the current study, we documented the presence, concentrations, and biological effects of CECs across 27 field sites in six Great Lakes tributaries by examining over 2250 resident and caged sunfish (Lepomis ssp.) for a variety of morphological and physiological endpoints and related these results to CEC occurrence. CEC were ubiquitous across studies sites and their presence and concentrations in water and sediment were highest in effluent dominated rivers and downstream of municipal wastewater treatment plant discharges. However, even putative upstream reference sites were not free of CEC presence and fish at these sites exhibited biological effects consistent with CEC exposure. Only the Fox River exhibited consistent adverse biological effects, including increased relative liver size, greater prominence of hepatocyte vacuoles and increased plasma glucose concentrations. Canonical Redundancy Analysis revealed consistent patterns of biological consequences of CEC exposure across all six tributaries. Increasing plasma glucose concentrations, likely as a result of pollutant-induced metabolic stress, were associated with increased relative liver size and greater prominence of hepatocyte vacuoles. These indicators of pollutant exposure were inversely correlated with indicators of reproductive potential including smaller gonad size and less mature gametes. The current study highlights the need for greater integration of chemical and biological studies and suggests that CECs in the Laurentian Great Lakes Basin may adversely affect the reproductive potential of exposed fish populations.

SUBMITTER: Thomas LM

PROVIDER: S-EPMC5617166 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Contaminants of emerging concern in tributaries to the Laurentian Great Lakes: II. Biological consequences of exposure.

Thomas Linnea M LM Jorgenson Zachary G ZG Brigham Mark E ME Choy Steven J SJ Moore Jeremy N JN Banda Jo A JA Gefell Daniel J DJ Minarik Thomas A TA Schoenfuss Heiko L HL

PloS one 20170927 9

The Laurentian Great Lakes contain one fifth of the world's surface freshwater and have been impacted by human activity since the Industrial Revolution. In addition to legacy contaminants, nitrification and invasive species, this aquatic ecosystem is also the recipient of Contaminants of Emerging Concern (CECs) with poorly understood biological consequences. In the current study, we documented the presence, concentrations, and biological effects of CECs across 27 field sites in six Great Lakes t ...[more]

PMID: 28953953

Similar Datasets

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.

Project description:Contaminants of emerging concern (CECs; e.g., pharmaceuticals, flame retardants, pesticides, and industrial chemicals) are omnipresent throughout tributaries to the Great Lakes. Furthermore, CECs are often present at concentrations that are potentially hazardous to aquatic species. Since 2010, we characterized the presence of CECs at 309 sites within 47 Great Lakes tributaries and characterized responses of fathead minnow (Pimephales promelas) exposed to river water at a subset of 26 sites within four tributaries. Our work resulted in three independent lines of evidence related to the potential hazards of CEC exposure to fish. First, vulnerability (where vulnerability refers to likelihood) of surface waters to CEC presence was predicted using select watershed characteristics. Second, hazard to fish (where hazard means the potential for adverse biological responses) was predicted using screening values for a subset of CECs. Third, biological responses of fathead minnow exposed to river water in streamside exposures were measured. We assessed the congruence of these three lines of evidence for identifying sites with elevated hazards to CEC exposure. Predicted vulnerability and hazards agreed at 66% of all sites. Where the two indices did not agree, vulnerability often underestimated predicted hazard. When compared with measured biological responses from streamside exposures, predicted hazards agreed for 42% of samples. Furthermore, when predicted hazards for specific effect categories were compared with similar measured biomarkers, 26% and 46% of samples agreed for reproductive and physiological effect categories, respectively. Overall, vulnerability and hazard predictions tended to overestimate the measured biological responses, providing a protective estimate of the potential hazards of CEC exposure to fish. When used together, these three approaches can help resource managers prioritize management activities in minimizing hazards of CEC exposure and can be used by researchers to prioritize studies focused on understanding the hazards of CEC exposure to fish. Integr Environ Assess Manag 2022;18:1246-1259. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by US Government employees and their work is in the public domain in the USA.

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:Waterborne contaminants were monitored in 69 tributaries of the Laurentian Great Lakes in 2010 and 2014 using semipermeable membrane devices (SPMDs) and polar organic chemical integrative samplers (POCIS). A risk-based screening approach was used to prioritize chemicals and chemical mixtures, identify sites at greatest risk for biological impacts, and identify potential hazards to monitor at those sites. Analyses included 185 chemicals (143 detected) including polycyclic aromatic hydrocarbons (PAHs), legacy and current-use pesticides, fire retardants, pharmaceuticals, and fragrances. Hazard quotients were calculated by dividing detected concentrations by biological effect concentrations reported in the ECOTOX Knowledgebase (toxicity quotients) or ToxCast database (exposure-activity ratios [EARs]). Mixture effects were estimated by summation of EAR values for chemicals that influence ToxCast assays with common gene targets. Nineteen chemicals-atrazine, N,N-diethyltoluamide, di(2-ethylhexyl)phthalate, dl-menthol, galaxolide, p-tert-octylphenol, 3 organochlorine pesticides, 3 PAHs, 4 pharmaceuticals, and 3 phosphate flame retardants-had toxicity quotients >0.1 or EARs for individual chemicals >10-3 at 10% or more of the sites monitored. An additional 4 chemicals (tributyl phosphate, triethyl citrate, benz[a]anthracene, and benzo[b]fluoranthene) were present in mixtures with EARs >10-3 . To evaluate potential apical effects and biological endpoints to monitor in exposed wildlife, in vitro bioactivity data were compared to adverse outcome pathway gene ontology information. Endpoints and effects associated with endocrine disruption, alterations in xenobiotic metabolism, and potentially neuronal development would be relevant to monitor at the priority sites. The EAR threshold exceedance for many chemical classes was correlated with urban land cover and wastewater effluent influence, whereas herbicides and fire retardants were also correlated to agricultural land cover. Environ Toxicol Chem 2021;40:2165-2182. Published 2021. 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.

Dataset Information

Contaminants of emerging concern in tributaries to the Laurentian Great Lakes: II. Biological consequences of exposure.

Publications

Contaminants of emerging concern in tributaries to the Laurentian Great Lakes: II. Biological consequences of exposure.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets