Prioritizing chemicals of ecological concern in Great Lakes tributaries using high-throughput screening data and adverse outcome pathways

Abstract Chemical monitoring data were collected in surface waters from 57 Great Lakes tributaries from 2010 to 13 to identify chemicals of potential biological relevance and sites at which these chemicals occur. Traditional water-quality benchmarks for aquatic life based on in vivo toxicity data were available for 34 of 67 evaluated chemicals. To expand evaluation of potential biological effects, measured chemical concentrations were compared to chemical-specific biological activities determined in high-throughput (ToxCast) in vitro assays. Resulting exposure-activity ratios (EARs) were used to prioritize the chemicals of greatest potential concern: 4‑nonylphenol, bisphenol A, metolachlor, atrazine, DEET, caffeine, tris(2‑butoxyethyl) phosphate, tributyl phosphate, triphenyl phosphate, benzo(a)pyrene, fluoranthene, and benzophenone. Water-quality benchmarks were unavailable for five of these chemicals, but for the remaining seven, EAR-based prioritization was consistent with that based on toxicity quotients calculated from benchmarks. Water-quality benchmarks identified three additional PAHs (anthracene, phenanthrene, and pyrene) not prioritized using EARs. Through this analysis, an EAR of 10 −3 was identified as a reasonable threshold above which a chemical might be of potential concern. To better understand apical hazards potentially associated with biological activities captured in ToxCast assays, in vitro bioactivity data were matched with available adverse outcome pathway (AOP) information. The 49 ToxCast assays prioritized via EAR analysis aligned with 23 potentially-relevant AOPs present in the AOP-Wiki. Mixture effects at monitored sites were estimated by summation of EAR values for multiple chemicals by individual assay or individual AOP. Commonly predicted adverse outcomes included impacts on reproduction and mitochondrial function. The EAR approach provided a screening-level assessment for evidence-based prioritization of chemicals and sites with potential for adverse biological effects. The approach aids prioritization of future monitoring activities and provides testable hypotheses to help focus those efforts. This also expands the fraction of detected chemicals for which biologically-based benchmark concentrations are available to help contextualize chemical monitoring results.