Grantee Research Project Results

Development of a larval fish neurobehavior adverse outcome pathway to predict effects of contaminants at the ecosystem level and across multiple ecologically relevant taxa

EPA Grant Number: R835798
Title: Development of a larval fish neurobehavior adverse outcome pathway to predict effects of contaminants at the ecosystem level and across multiple ecologically relevant taxa
Investigators: Murphy, Cheryl A. , Carvan, Michael , Jones, Michael , Garcia-Reyero, Natàlia
Current Investigators: Murphy, Cheryl A. , Garcia-Reyero, Natàlia , Carvan, Michael , Jones, Michael
Institution: Michigan State University , Mississippi State University , University of Wisconsin - Milwaukee
Current Institution: Michigan State University , University of Wisconsin - Milwaukee , Mississippi State University
EPA Project Officer: Spatz, Kyle
Project Period: June 1, 2015 through May 31, 2018 (Extended to May 31, 2021)
Project Amount: $800,000
RFA: Systems-Based Research for Evaluating Ecological Impacts of Manufactured Chemicals (2014) RFA Text |  Recipients Lists
Research Category: Chemical Safety for Sustainability

Objective:

The overall objective of this project is to advance the adverse outcome pathway framework to predict effects of contaminants with different modes of action on the neurobehavior of larval fish from three different species and to determine what Adverse Outcome Pathways (AOPs) are common between species. The overall hypothesis is that two contaminants will affect the neurobehavior AOP of larval fish species and that common pathways will be found between species to allow for predictions on ecologically relevant species from typical laboratory model species to the ecosystem level.

Approach:

This approach integrates the classic toxicological paradigm with global analyses across multiple levels of biological organization, providing a more comprehensive systems level understanding of the problem. Critical genes and pathways predictive of adverse neurobehavior outcomes will be identified through network inference methods using RNAsequencing and metabolomics and physiological endpoints, including behavior and developmental abnormalities, from three different fish species exposed to PCB126 and methylmercury. Behavior of predictive genes and pathways will be compared across species. Finally, an individual-based model predictive of growth and survival will be developed. The model will incorporate behavioral data to predict larval cohort survival and stage duration and EC50s, which can be incorporated into population models modified to accommodate different community structures to predict long-term population impacts. We will quantify uncertainty in key stressor-demographic linkages and use error-propagation methods to frame simulation outputs in a risk assessment context

Expected Results:

The proposed work will demonstrate the effectiveness of systems toxicology and network inference approaches in determining adverse neurobehavior outcomes. We expect that monitoring chemical effects on critical genes and pathways on fish larvae will be indicative of adverse outcomes on fish/animal species at the population and community level and will improve risk management of populations of species that are impossible to test in the laboratory.

Publications and Presentations:

Publications have been submitted on this project: View all 23 publications for this project

Journal Articles:

Journal Articles have been submitted on this project: View all 6 journal articles for this project

Supplemental Keywords:

aquatic, scaling, ecological effects endocrine disruptors, neurotoxicity, computational toxicology, network inference, modeling, RNAseq

Progress and Final Reports:

2015 Progress Report

2016 Progress Report

2017 Progress Report

2018 Progress Report

2019 Progress Report

Final Report