Data from study assessing the utility of knowledgebase-leveraging of comprehensive environmental-contaminant-exposure datasets by comparing biological effects predicted on the basis of target chemical analyses with measured biological effects in corresponding split water samples.

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).

Previous work identified a ‘cytotoxic burst’ (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared to the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). This dataset is associated with the following publication: Fay, K., J. Swintek, D. Villeneuve, S. Edwards, M. Nelms, B. Blackwell, and G. Ankley. Differentiating pathway-specific from non-specific effects in high-throughput toxicity data: A foundation for prioritizing adverse outcome pathway development. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 163(2): 500-515, (2018).

Previous work identified a ‘cytotoxic burst’ (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared to the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). This dataset is associated with the following publication: Fay, K., J. Swintek, D. Villeneuve, S. Edwards, M. Nelms, B. Blackwell, and G. Ankley. Differentiating pathway-specific from non-specific effects in high-throughput toxicity data: A foundation for prioritizing adverse outcome pathway development. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 163(2): 500-515, (2018).

Human-use pharmaceutical compounds were analyzed at the U.S. Geological Survey, National Water Quality Laboratory, Denver, Colorado, in wadeable streams in 4 Regional Stream Quality Assessments: Northeast (NESQA), Southeast (SESQA), Pacific Northwest (PNSQA) and California (CSQA). Multiple (with few exceptions) samplings occurred at each site, during base flow, between 2014 and 2017. Sites were located in the headwaters of perennial, wadeable streams in urban and agricultural watersheds. Site selection and methodology for each assessment can be found in Van Meter and others (2015), Sheibley and others (2015), Van Meter and others (2017), Coles and others (2016), Van Meter and others (2016), Journey and others (2015), and Van Meter and others (2014).

Human-use pharmaceutical compounds were analyzed at the U.S. Geological Survey, National Water Quality Laboratory, Denver, Colorado, in wadeable streams in 4 Regional Stream Quality Assessments: Northeast (NESQA), Southeast (SESQA), Pacific Northwest (PNSQA) and California (CSQA). Multiple (with few exceptions) samplings occurred at each site, during base flow, between 2014 and 2017. Sites were located in the headwaters of perennial, wadeable streams in urban and agricultural watersheds. Site selection and methodology for each assessment can be found in Van Meter and others (2015), Sheibley and others (2015), Van Meter and others (2017), Coles and others (2016), Van Meter and others (2016), Journey and others (2015), and Van Meter and others (2014).

This data release includes concentrations of contaminants of emerging concern (CEC), by chemical class, for sites sampled within 25 river basins in the U.S. portion of the Great Lakes basin and associated watershed characteristics. The CEC data include concentrations in surface water and sediment samples that were collected during 2010-2014. During the first 3 years, sample sites near mostly urban areas were chosen. The last two years of study focused on other point sources and few nominal reference sites. Water and sediment samples were analyzed for a diverse suite of CECs including, but not limited to, pharmaceuticals, industrial chemicals, flame retardants, pesticides, fragrances, and plasticizers. Statistical models were developed to define the relationships between watershed characteristics within a river basin and the occurrence of specific CEC classes using boosted regression tree models.

This data release includes concentrations of contaminants of emerging concern (CEC), by chemical class, for sites sampled within 25 river basins in the U.S. portion of the Great Lakes basin and associated watershed characteristics. The CEC data include concentrations in surface water and sediment samples that were collected during 2010-2014. During the first 3 years, sample sites near mostly urban areas were chosen. The last two years of study focused on other point sources and few nominal reference sites. Water and sediment samples were analyzed for a diverse suite of CECs including, but not limited to, pharmaceuticals, industrial chemicals, flame retardants, pesticides, fragrances, and plasticizers. Statistical models were developed to define the relationships between watershed characteristics within a river basin and the occurrence of specific CEC classes using boosted regression tree models.

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).