Anthropogenic activities introduce complex mixtures into aquatic environments, necessitating the evaluation of mixture toxicity during ecological risk assessments. There are many new approach methodologies (NAMs) that can be used to complement traditional approaches for conducting mixture assessments. This study aimed to demonstrate how traditional approaches and NAMs can be integrated and employed for mixture evaluation in a target watershed. Assessments were carried out over two 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, and in vivo effects in collected water and tissue samples. Chemicals were grouped based on structure/mode of action, bioactivity, and pharmacological actions. Significant chemical/mixtures were identified by assessing contributions to cumulative toxicity units (maximum cumulative ratio analyses) and predictive relationships with measured effects (random Forest regression). Whole mixture assessments identified specific target sites for further evaluation in the Milwaukee Estuary, including four sites impacted by industrial chemical/fuel/polycyclic aromatic hydrocarbon mixtures, four sites impacted by pharmaceutical mixtures, two sites requiring further experimental evaluation, and one low impact site. Constituent-based and predictive analyses identified twelve mixtures and twelve chemicals which significantly contributed to and/or predicted cumulative effects, thus representing priority targets for further ecotoxicological evaluation, monitoring, or regulatory assessment. Overall, this study represents an important complement to single-chemical prioritizations, providing a more comprehensive evaluation of cumulative effects of chemicals detected in a target watershed. Furthermore, it demonstrates diverse tools and techniques that can be employed and adapted for future mixture risk assessments in aquatic environments. This dataset is associated with the following publication: Maloney, E., D. Villeneuve, K. Jensen, B. Blackwell, M. Kahl, S. Poole, K. Vitense, D. Feifarek, G. Patlewicz, K. Dean, C. Tilton, E. Randolph, J. Cavallin, C. Lalone, D. Blatz, C. Schaupp, and G. Ankley. Evaluation of Complex Mixture Toxicity in the Milwaukee Estuary (WI, USA) Using Whole-Mixture and Component-Based Evaluation Methods. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 42(6): 1229-1256, (2023).

In vitro biological activity data from a extracts of a nationwide survey of US streams. This dataset is associated with the following publication: Blackwell, B., G. Ankley, P. Bradley, K. Houck, S.S. Makarov, A. Medvedev, J. Swintek, and D. Villeneuve. Potential toxicity of complex mixtures in surface waters from a nationwide survey of United States streams: Identifying in vitro bioactivities and causative chemicals. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(2): 973-983, (2019).

Water-borne 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). Analyses included 185 chemicals (143 detected) including PAHs, legacy and current-use pesticides, fire retardants, pharmaceuticals, fragrances, and others. Hazard quotients were calculated by dividing detected concentrations by biological effect concentrations reported in the ECOTOX Knowledgebase (Toxicity quotients, TQs) or ToxCast database (Exposure Activity Ratios, EARs). This dataset is associated with the following publication: Alvarez, D., S. Corsi, L. De Cicco, D. Villeneuve, and A. Baldwin. Identifying chemicals and mixtures of potential biological concern detected in passive samplers from Great Lakes tributaries using high-throughput data and biological pathways. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA,

Water-borne 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). Analyses included 185 chemicals (143 detected) including PAHs, legacy and current-use pesticides, fire retardants, pharmaceuticals, fragrances, and others. Hazard quotients were calculated by dividing detected concentrations by biological effect concentrations reported in the ECOTOX Knowledgebase (Toxicity quotients, TQs) or ToxCast database (Exposure Activity Ratios, EARs). This dataset is associated with the following publication: Alvarez, D., S. Corsi, L. De Cicco, D. Villeneuve, and A. Baldwin. Identifying chemicals and mixtures of potential biological concern detected in passive samplers from Great Lakes tributaries using high-throughput data and biological pathways. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA,

We describe screening level estimates of potential aquatic toxicity posed by 227 chemical analytes that were measured in 25 ambient water samples collected as part of a joint USGS/USEPA drinking water plant study. Measured concentrations were compared to biological effect concentration (EC) estimates, including USEPA aquatic life criteria, effective plasma concentrations of pharmaceuticals, published toxicity data summarized in the USEPA ECOTOX database, and chemical structure-based predictions. Potential dietary exposures were estimated using a generic 3-tiered food web accumulation scenario. This dataset is associated with the following publication: Kostich , M., R. Flick , A. Batt , H. Mash , S. Boone , E. Furlong, D. Kolpin, and S. Glassmeyer. Aquatic concentrations of chemical analytes compared to ecotoxicity estimates. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 579: 1649-1657, (2017).

We describe screening level estimates of potential aquatic toxicity posed by 227 chemical analytes that were measured in 25 ambient water samples collected as part of a joint USGS/USEPA drinking water plant study. Measured concentrations were compared to biological effect concentration (EC) estimates, including USEPA aquatic life criteria, effective plasma concentrations of pharmaceuticals, published toxicity data summarized in the USEPA ECOTOX database, and chemical structure-based predictions. Potential dietary exposures were estimated using a generic 3-tiered food web accumulation scenario. This dataset is associated with the following publication: Kostich , M., R. Flick , A. Batt , H. Mash , S. Boone , E. Furlong, D. Kolpin, and S. Glassmeyer. Aquatic concentrations of chemical analytes compared to ecotoxicity estimates. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 579: 1649-1657, (2017).

Prioritization of chemicals was performed on two Areas of Concerns in the Great Lakes An integrated risk surveillance and monitoring approach was applied Bio-effect prediction methodologies were used to identify additional biological pathways. Environmental assessment of complex mixtures typically requires integration of chemical and biological measurements. This study demonstrates the use of a combination of instrumental chemical analyses, effects-based monitoring, and bio-effects prediction approaches to help identify potential hazards and priority contaminants in two Great Lakes Areas of Concern (AOCs), the Lower Green Bay/Fox River located near Green Bay, WI, USA and the Milwaukee Estuary, located near Milwaukee, WI, USA. Fathead minnows were caged at four sites within each AOC (eight sites total). Following 4 d of in situ exposure, tissues and biofluids were sampled and used for targeted biological effects analyses. Additionally, 4 d composite water samples were collected concurrently at each caged fish site and analyzed for 132 analytes as well as evaluated for total estrogenic and androgenic activity using cell-based bioassays. Of the analytes examined, 75 were detected in composite samples from at least one site. Based on multiple analyses, one site in the East River and another site near a paper mill discharge in the Lower Green Bay/Fox River AOC, were prioritized due to their estrogenic and androgenic activity, respectively. The water samples from other sites generally did not exhibit significant estrogenic or androgenic activity, nor was there evidence for endocrine disruption in the fish exposed at these sites as indicated by the lack of alterations in ex vivo steroid production, circulating steroid concentrations, or vitellogenin mRNA expression in males. Induction of hepatic cyp1a mRNA expression was detected at several sites, suggesting the presence of chemicals that activate the Ah receptor. To expand the scope beyond targeted investigation of endpoints selected a priori, several bio-effects prediction approaches were employed to identify other potentially disturbed biological pathways and related chemical constituents that may warrant future monitoring at these sites. For example, several chemicals such as diethylphthalate and naphthalene , and genes and related pathways, such as cholinergic receptor muscarinic 3 (CHRM3), estrogen receptor alpha1 (esr1), chemokine ligand 10 protein (CXCL10), tumor protein p53 (p53), and monoamine oxidase B (Maob), were identified as candidates for future assessments at these AOCs. Overall, this study demonstrates that a better prioritization of contaminants and associated hazards can be achieved through integrated evaluation of multiple lines of evidence. Such prioritization can guide more comprehensive follow-up risk assessment efforts. This dataset is associated with the following publication: Li, S., D. Villeneuve, J. Berninger, B. Blackwell, J. Cavallin, M. Hughes, K. Jensen, Z. Jorgenson, M. Kahl, A. Schroeder, K. Stevens, L. Thomas, M. Weberg, and G. Ankley. An integrated approach for identifying priority contaminant in the Great Lakes Basin -Investigations in the Lower Green Bay/Fox River and Milwaukee Estuary areas of concern. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 579: 825-837, (2017).

Prioritization of chemicals was performed on two Areas of Concerns in the Great Lakes An integrated risk surveillance and monitoring approach was applied Bio-effect prediction methodologies were used to identify additional biological pathways. Environmental assessment of complex mixtures typically requires integration of chemical and biological measurements. This study demonstrates the use of a combination of instrumental chemical analyses, effects-based monitoring, and bio-effects prediction approaches to help identify potential hazards and priority contaminants in two Great Lakes Areas of Concern (AOCs), the Lower Green Bay/Fox River located near Green Bay, WI, USA and the Milwaukee Estuary, located near Milwaukee, WI, USA. Fathead minnows were caged at four sites within each AOC (eight sites total). Following 4 d of in situ exposure, tissues and biofluids were sampled and used for targeted biological effects analyses. Additionally, 4 d composite water samples were collected concurrently at each caged fish site and analyzed for 132 analytes as well as evaluated for total estrogenic and androgenic activity using cell-based bioassays. Of the analytes examined, 75 were detected in composite samples from at least one site. Based on multiple analyses, one site in the East River and another site near a paper mill discharge in the Lower Green Bay/Fox River AOC, were prioritized due to their estrogenic and androgenic activity, respectively. The water samples from other sites generally did not exhibit significant estrogenic or androgenic activity, nor was there evidence for endocrine disruption in the fish exposed at these sites as indicated by the lack of alterations in ex vivo steroid production, circulating steroid concentrations, or vitellogenin mRNA expression in males. Induction of hepatic cyp1a mRNA expression was detected at several sites, suggesting the presence of chemicals that activate the Ah receptor. To expand the scope beyond targeted investigation of endpoints selected a priori, several bio-effects prediction approaches were employed to identify other potentially disturbed biological pathways and related chemical constituents that may warrant future monitoring at these sites. For example, several chemicals such as diethylphthalate and naphthalene , and genes and related pathways, such as cholinergic receptor muscarinic 3 (CHRM3), estrogen receptor alpha1 (esr1), chemokine ligand 10 protein (CXCL10), tumor protein p53 (p53), and monoamine oxidase B (Maob), were identified as candidates for future assessments at these AOCs. Overall, this study demonstrates that a better prioritization of contaminants and associated hazards can be achieved through integrated evaluation of multiple lines of evidence. Such prioritization can guide more comprehensive follow-up risk assessment efforts. This dataset is associated with the following publication: Li, S., D. Villeneuve, J. Berninger, B. Blackwell, J. Cavallin, M. Hughes, K. Jensen, Z. Jorgenson, M. Kahl, A. Schroeder, K. Stevens, L. Thomas, M. Weberg, and G. Ankley. An integrated approach for identifying priority contaminant in the Great Lakes Basin -Investigations in the Lower Green Bay/Fox River and Milwaukee Estuary areas of concern. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 579: 825-837, (2017).

Concentrations of 127 organic chemicals measured in water samples collected from five locations in proximity to two municipal wastewater treatment plants in the St. Croix River basin, MN and WI, USA are included. Additionally, gene expression in the livers of fathead minnows exposed in situ to the site water for 12 d is included. Gene expression was analyzed by oligonucleotide microarray and raw data are accessible through the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), accession number GSE81263. Additional analyses performed on those data, including construction of knowledge assembly models from comparison of the detected chemicals data with associated genes from the comparative toxicogenomics database, pathway and gene ontology enrichment analyses performed on the gene expression data, and richness and concordance statistics from a Reverse Causal Reasoning-based statistical approach are included. This dataset is associated with the following publication: Schroeder , A., D. Martinović-Weigelt, G. Ankley , K. Lee, N. Garcia-Reyero, E. Perkins, H. Schoenfuss, and D. Villeneuve. Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix river basin, MN, WI, USA.. ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 221: 427-436, (2017).

Concentrations of 127 organic chemicals measured in water samples collected from five locations in proximity to two municipal wastewater treatment plants in the St. Croix River basin, MN and WI, USA are included. Additionally, gene expression in the livers of fathead minnows exposed in situ to the site water for 12 d is included. Gene expression was analyzed by oligonucleotide microarray and raw data are accessible through the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), accession number GSE81263. Additional analyses performed on those data, including construction of knowledge assembly models from comparison of the detected chemicals data with associated genes from the comparative toxicogenomics database, pathway and gene ontology enrichment analyses performed on the gene expression data, and richness and concordance statistics from a Reverse Causal Reasoning-based statistical approach are included. This dataset is associated with the following publication: Schroeder , A., D. Martinović-Weigelt, G. Ankley , K. Lee, N. Garcia-Reyero, E. Perkins, H. Schoenfuss, and D. Villeneuve. Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix river basin, MN, WI, USA.. ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 221: 427-436, (2017).