Systems Biology Modeling of Fathead Minnow Response to Endocrine DisruptorsEPA Grant Number: R831848
Title: Systems Biology Modeling of Fathead Minnow Response to Endocrine Disruptors
Investigators: Denslow, Nancy , Orlando, Edward F. , Watanabe, Karen , Sepulveda, Maria
Current Investigators: Denslow, Nancy , Orlando, Edward F. , Sepúlveda, Maria (Marisol) S. , Watanabe, Karen
Institution: University of Florida , Oregon Health & Sciences University , Saint Mary College
Current Institution: University of Florida , Florida Atlantic University - Boca Raton , Oregon Health & Sciences University , Purdue University
EPA Project Officer: Klieforth, Barbara I
Project Period: August 1, 2004 through July 31, 2007
Project Amount: $722,851
RFA: Computational Toxicology and Endocrine Disruptors: Use of Systems Biology in Hazard Identification and Risk Assessment (2004) RFA Text | Recipients Lists
Research Category: Economics and Decision Sciences , Computational Toxicology , Endocrine Disruptors , Health Effects , Health , Safer Chemicals
The objective of this study is to develop a computational model to evaluate molecular and protein biomarkers in relation to reproductive dysfunction in fathead minnows exposed to environmental estrogens. The model will incorporate a number of biochemical endpoints along the entire hypothalamic-pituitary-gonadal axis, direct evaluation of physiological changes and reproductive endpoints and the pharmacodynamics and kinetic distribution of the contaminants. The hypothesis that we will test is that genomic and proteomics biomarkers will be diagnostic of the estrogenic effects of environmental estrogens and that they will provide a global understanding of mechanisms of action that will relate specifically to reproductive endpoints in FHM that are adversely affected by exposure to estrogenic compounds.
Fathead minnows will be exposed to three concentrations each of ethinylestradiol (EE2), and its antagonist ZM 189,154 and to combinations of the two compounds for 48 hrs or 21 days to measure a battery of biochemical, physiological and reproductive endpoints. Short exposures will be used for gene expression and proteomics studies while both short and long exposures will be used to measure the physiologic, biochemical and reproductive endpoints. These data will be brought together in a predictive computational model for the action of environmental estrogens. The model will then be tested with an exposure of fathead minnows to zearalenone (estrogen mimic and positive testor) and trenbolone (nonaromatizable androgen and negative testor), compounds that are used in the cattle industry.
We expect to develop a computational model and identify 10-15 molecular and protein biomarkers that are specific and predictive of adverse effects of exposure to estrogenic compounds in reproduction of fathead minnows. This quantitative model will help improve risk assessment of exposure of wildlife and, by extrapolation, of mammals to endocrine disrupting compounds.