You are here:
Chemical-gene interaction networks and causal reasoning for biological effects prediction and prioritization of contaminants for environmental monitoring and surveillance
Citation:
Schroeder, A., D. Martinovic-Weigelt, G. Ankley, K. Lee, N. Garcia-Reyero, E. Perkins, H. Schoenfuss, AND Dan Villeneuve. Chemical-gene interaction networks and causal reasoning for biological effects prediction and prioritization of contaminants for environmental monitoring and surveillance. SETAC North America, Salt Lake City, UT, November 01 - 05, 2015.
Impact/Purpose:
not applicable
Description:
Evaluating the potential human health and ecological risks associated with exposures to complex chemical mixtures in the environment is one of the main challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and biological effects data to evaluate risks associated with chemicals present in the environment. Here, we used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near the North Branch and Chisago wastewater treatment plants (WWTP) in the St. Croix River Basin, MN and WI. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data were also mapped to the assembly models to evaluate the likelihood of a chemical contributing to the observed biological responses using richness and concordance statistics. The prior knowledge approach was able predict the observed biological pathways impacted at one site but not the other. Atrazine was identified as a potential contributor to the observed gene expression responses at a location upstream of the North Branch WTTP. Four chemicals were identified as contributors to the observed biological responses at the effluent and downstream of the North Branch WWTP, with carbamazepine being a significant contributor at both locations. Four chemicals were identified as the greatest contributors to the observed biological responses in fish exposed to the effluent at the Chisago WWTP. Five chemicals were identified as contributors to the observed biological responses in fish exposed downstream of the Chisago WWTP, with 17-estradiol and estrone being two of the significant chemicals. Knowledge assembly models have strong potential for associating chemical occurrence with potential biological effects and providing a foundation for hypothesis generation to guide research and/or monitoring efforts related to the effects of contaminants in the environment.