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Linkage of exposure and effects using genomics, proteomics and metabolomics in small fish models (presentation)
Citation:
BENCIC, D. C., A. D. BIALES, R. WANG, J. M. LAZORCHAK, T. W. COLLETTE, D. L. VILLENEUVE, G. T. ANKLEY, AND D. L. LATTIER. Linkage of exposure and effects using genomics, proteomics and metabolomics in small fish models (presentation). Presented at 10th Brazilian Congress of Ecotoxicology, Porto Alegre, BRAZIL, April 30 - May 03, 2008.
Impact/Purpose:
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.
Description:
This research project combines the use of whole organism endpoints, genomic, proteomic and metabolomic approaches, and computational modeling in a systems biology approach to 1) identify molecular indicators of exposure and biomarkers of effect to EDCs representing several modes/mechanisms of action (MOA), and 2) link these indicators/biomarkers to effects that are relevant for both diagnostic and predictive risk assessment susing two small fish models. The two fish species used in this project are fathead minnows (Pimephales promelas; FHMs) and zebrafish (Danio rerio; ZF). The research has been organized into three phases, with phase 1 comprising 21-day reproduction studies with FHMs and phase 2 consisting of 1-4 day studies with the same chemicals to identify MOA-specific alterations in the transcriptome, proteome, and metabolome of ZF. Microarrays followed by real-time quantitative polymerase chain reaction (QPCR) verification and two-dimensional gel polyacrylamide gel electrophoresis (2-D PAGE) followed by mass spectrometry identification have been used to detect specific transcriptional and protein patterns, respectively, resulting from exposure to EDCs. Detection of anomalies at a molelcular level enables screening methods of shorter duration to identify effects, soon after exposure, before they are manifested at the tissue-, organ-, individual-, or population-level. Phase 3 involves translating ZF results back to FHMs and linking these molecular level changes to higher order changes form phase 1. The ability to determine the changes at each step of the molecular cascade allows for more relaible interpretation of key biological processes that result in phenotypic effects and supports the development of informative and predictive indicators. Incorporation of the results into conceptual systems (HPG axis-based) and population models will help integrate all aspects of the three phases of data collection.