Citation:

BENCIC, D. C., A. L. MIRACLE, D. L. LATTIER, J. M. LAZORCHAK, N. D. DENSLOW, K. H. WATANABE, T. L. WHITEHEAD, T. W. COLLETTE, M. D. KAHL, AND G. T. ANKLEY. CHANGES IN GENE AND PROTEIN EXPRESSION IN ZEBRAFISH (DANIO RERIO) FOLLOWING EXPOSURE TO ENVIRONMENTALLY-RELEVANT ENDOCRINE DISRUPTING COMPOUNDS (EDCS). Presented at SETAC, Baltimore, MD, November 13 - 17, 2005.

Impact/Purpose:

The indeterminate condition of exposure indicator research stands to change markedly with the ability to connect molecular biological technologies with cellular or tissue effects and outcomes. Three focal areas of ecological research aim to develop a sequence of approaches where "the earliest recognizable signatures of exposure" (i.e., unique patterns of up- and down-regulated genes and proteins) are identified for numerous stressors, demonstrable in case studies and incorporated into Agency, State and Regional studies supported by EMAP and other programs.

Area 1, Computational Toxicology Research: Exposure assessment has historically been based on use of chemical analysis data to generate exposure models. While biological activity of chemicals has been recognized to be important for exposure risk assessments, measurement of such activity has been limited to whole organism toxicity tests. Use of molecular approaches will:

improve extrapolation between components of source-to-outcome continuum (source , exposure , dose , effect , outcome)

Using a systems modeling approach, gene and protein expression data, in small fish models (fathead minnow and zebrafish), will be integrated with metabolomic and histopathological data. This will assist in prediction of environmental transformation and chemical effects based on structural characteristics, and enhance quantitative risk assessments, including areas of uncertainty such as a basis for extrapolation of effects of endocrine disrupting chemicals, interspecies extrapolation, complex chemical mixtures and dose-response assessment.

Area 2, Ecological Research-Environmental Diagnostics: Development of molecular diagnostic indicators contributes to several of the GPRA Diagnostic Research Goals. Methods will employ DNA microarray technology and expression proteomics, focusing on species of relevance to aquatic ecosystem risk assessment. Significantly, these diagnostic indicators will open the door to understanding subcellular interactions resulting from exposure to complex chemical mixtures.

define relationship between genetic disposition of populations and degree/specificity of stressor-specific gene transcriptional response in aquatic organisms (fish and invertebrates)

identify of chemical mixture induced transcriptional "patterns" using microarrays and hyperspectral scanning - via collaboration with DOE Sandia National Labs

apply molecular indicators to watershed level stressor study, including pilot studies with targeted pesticides and toxins indicators

develop molecular indicators of exposure for invertebrates (Daphnia, Lumbriculus, Chironomus)

Area 3, Exposure Research in Endocrine Disruptors:

Subobjective 1: Develop exposure methods, measurement protocols, and models for assessment of risk management practices of endocrine disrupting compounds. As risk management approaches are identified and developed, there will be a need to identify, adapt and develop bioassay screening tools and other analytical methods to assess their efficacy. Measurements research will be performed to define management needs. This effort will entail cross-lab participation from NRMRL, NERL and NHEERL.

Subobjective 2: Determine extent of environmental and human exposures to EDCs, characterize sources and factors influencing these exposures, develop and evaluate risk management strategies to reduce exposures. In order to develop effective risk management strategies, it is important to understand the extent of exposures to endocrine disrupting compounds and factors influencing source-to-exposure-to-dose relationships.

apply molecular indicators of exposure to estrogenic compounds in selected wastewater treatment plants located in ten USEPA Regions

identify differential gene expression following exposure of fathead minnows to environmental androgens and androgen-like compounds

apply molecular indicators of exposu

Description:

Endocrine-disrupting chemicals (EDCs) are increasingly being reported in waterways worldwide and have been shown to affect fish species by disrupting numerous aspects of development, behavior, reproduction, and survival. Furthermore, new data have suggested that the reduced reproductive fitness resulting from EDC exposure may have a significant impact at biological levels beyond the individual, such as the population level. In this study, we examined the effects of the synthetic steroids 17�-ethinylestradiol (EE2) and 17�-trenbolone (trenbolone) on gene and protein expression in the liver and gonads of reproductively mature zebrafish (Danio rerio). These compounds are highly specific and potent agonists of estrogen and androgen receptors, respectively, and are used extensively in the U.S. as an active ingredient in many oral contraceptives (EE2) or a growth promoter in beef cattle (trenbolone). Both have been detected in aquatic environments and are therefore relevant as environmental contaminants. Fish were exposed to two concentrations of EE2 (30 or 100 ng/L) or trenbolone (0.3 or 3.0 �g/L) or control water for up to 96 hours in a flow-through system. Changes in the transcriptome and proteome were measured using microarrays followed by QPCR validation and two-dimensional gel electrophoresis followed by peptide analysis via mass spectroscopy, respectively. The differential expression profiles will provide molecular diagnostic and predictive biomarkers for risk assessment, and along with metabolite profiles and whole organism endpoints from ongoing projects, will further enhance source-to-outcome linkages and support computational modeling. Integration of these zebrafish gene and protein expression data sets with definitive tests in the fathead minnow (Pimephales promelas) will help establish toxicity pathways of environmentally-relevant responses in a systems- and population-modeling context.

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