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Using pathway-based biological effects monitoring and the adverse outcome pathway framework to link chemical exposure with ecological hazards
Citation:
Villeneuve, Dan, S. Corsi, AND B. Blackwell. Using pathway-based biological effects monitoring and the adverse outcome pathway framework to link chemical exposure with ecological hazards. National Monitoring Conference, Denver, CO, March 25 - 29, 2019.
Impact/Purpose:
Data from new approach methodologies (NAMs) such as quantitative structure activity relationships, high throughput in vitro assays, etc. are increasingly being used to characterize chemical toxicity. However, practical interpretation of those data are challenged by the fact that the endpoints measured predominantly relate to molecular and biochemical responses like gene expression, transcription factor activation, enzyme inhibition, receptor binding, changes in hormone concentrations, etc. The adverse outcome pathway (AOP)-Wiki (aopwiki.org) was recently developed as a means to capture, organize and present knowledge regarding the role each of those biomolecules play in a complex physiological system, and the conditions under which their perturbation can lead to adverse effects in wildlife or humans. This presentation provides examples of how AOPs and the AOP-Wiki can be used to better understand ecological hazards that may be associated with exposure to complex mixtures of contaminants present in surface waters.
Description:
The adverse outcome pathway (AOP)-Wiki was developed to capture and disseminate knowledge that can help resource managers and risk assessors better understand what molecular, biochemical, and/or cellular-level effects of chemicals may mean in terms of potential or probable physiological or population-level outcomes. This presentation introduces the AOP-wiki and provides several case studies that demonstrate how it can be used, along with environmental monitoring data, to better understand the potential ecological impacts of complex mixtures of contaminants present in the environment. As analytical methods for detecting chemicals in the environment improve, an increasing number and diversity of contaminants can be detected in surface waters, sediment, or biota. Unfortunately, for many of these contaminants, traditional toxicity benchmarks, expressed as a concentration of the chemical that elicits adverse effects on survival, growth, or reproduction in wildlife, are unavailable. Recognizing the dearth of traditional toxicity data for most chemicals in commerce, a new vision for toxicity testing that relies on in vitro assays, in silico predictions based on structure-activity relationships, and other high throughput approaches has been proposed. Based on this vision, thousands of chemicals have already been screened as part of several pioneering high throughput screening programs. This provides a novel source of concentration-dependent bioactivity data that can be used to help contextualize chemical monitoring data. However, practical interpretation of those bioactivity data are challenged by the fact that the endpoints measured in high throughput testing programs are predominantly related to molecular and biochemical responses like gene expression, transcription factor activation, enzyme inhibition, receptor binding, changes in hormone concentrations, etc. Consequently, the potential significance and implications of exposure to chemicals that elicit such biological effects is not easy to interpret without highly specialized knowledge regarding the role each of those biomolecules play in a complex physiological system, and the conditions under which their perturbation can lead to adverse effects in wildlife or humans. The adverse outcome pathway (AOP) wiki (aopwiki.org) was recently developed as a means to capture, organize and present this kind of specialized knowledge in a systematic, transparent, and accessible manner. The current presentation will introduce the AOP framework and the AOP-wiki and provide examples of how these epistemic tools can be practically applied in the context of environmental monitoring. Specific examples will focus on how AOPs have been employed to infer potential ecological hazards associated with exposures to complex mixtures of organic contaminants in surface waters from Great Lakes tributaries as well as arid western streams.