Adverse outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment.

Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences may be able to generate mechanistic information that could help in meeting these challenges. However, to use mechanistic data to support chemical assessments, there is a need for effective translation of this information into endpoints meaningful to ecological risk-effects on survival, development, and reproduction in individual organisms and, by extension, impacts on populations. Here we discuss a framework designed for this purpose, the adverse outcome pathway (AOP). An AOP is a conceptual construct that portrays existing knowledge concerning the linkage between a direct molecular initiating event and an adverse outcome at a biological level of organization relevant to risk assessment. The practical utility of AOPs for ecological risk assessment of chemicals is illustrated using five case examples. The examples demonstrate how the AOP concept can focus toxicity testing in terms of species and endpoint selection, enhance across-chemical extrapolation, and support prediction of mixture effects. The examples also show how AOPs facilitate use of molecular or biochemical endpoints (sometimes referred to as biomarkers) for forecasting chemical impacts on individuals and populations. In the concluding sections of the paper, we discuss how AOPs can help to guide research that supports chemical risk assessments and advocate for the incorporation of this approach into a broader systems biology framework.

Use of trout liver slices to enhance mechanistic interpretation of estrogen receptor binding for cost-effective prioritization of chemicals within large inventories.

The cost of testing chemicals as reproductive toxicants precludes the possibility of evaluating large chemical inventories without a robust strategyfor prioritizing chemicals to test. The use of quantitative structure-activity relationships in early hazard identification is a cost-effective prioritization tool, but in the absence of systematic collection of interpretable test data upon which models are formulated, these techniques fall short of their intended use. An approach is presented for narrowing the focus of candidate ED chemicals using two in vitro assays: one optimized to measure the potential of chemicals to bind rainbow trout estrogen receptors (rtER), and a second to enhance interpretation of receptor binding data in a relevant biological system (i.e., fish liver tissue). Results of rtER competitive binding assays for 16 chemicals yielded calculable relative binding affinities (RBA) from 179 to 0.0006% for 13 chemicals and partial or no binding for an additional 3 chemicals. Eleven lower to no affinity chemicals (RBA < 0.1%) were further tested in trout liver slices to measure induction of rtER-dependent vitellogenin (VTG) mRNA in the presence of chemical passive partitioning (from media to multiple hepatocyte layers in the slice) and liver xenobiotic metabolism. VTG induction in slices was observed in a concentration-dependent manner for eight chemicals tested that had produced complete displacement curves in binding assays, including the lowest affinity binder with an RBA of 0.0006%. Two chemicals with only partial binding curves up to their solubility limit did not induce VTG. The monohydroxy metabolite of methoxychlor was the only chemical tested that apparently bound rtER but did not induce VTG mRNA. Data are presented illustrating the utility of the two assays in combination for interpreting the role of metabolism in VTG induction, as well as the sensitivity of the assays for measuring enantiomer selective binding and ER-mediated induction. The combined approach appears particularly useful in interpreting the potential relevance of extremely low affinity chemical binding to fish receptors (RBA = 0.01-0.0001%) within a defined toxicity pathway as a basis for prioritizing within large chemical inventories of environmental concern.