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HIGH-THROUGHPUT CHEMICAL SCREENING USING PROTEIN PROFILING OF FISH PLASMA
Citation:
Hudson, R., M J. Hemmer, K. Salinas, J. Watts, J T. Winstead, P S. Harris, A. Kirkpatrick, C C. Walker, AND S S. Wilkinson. HIGH-THROUGHPUT CHEMICAL SCREENING USING PROTEIN PROFILING OF FISH PLASMA. Presented at 44th Annual Society of Toxicology Meeting, New Orleans, LA, March 06 - 10, 2005.
Impact/Purpose:
Conference abstract
Description:
Compounds that affect the hormone system, referred to as "endocrine-disrupting chemicals" (EDCs), cause human and animal health problems. It is necessary to test putative EDC chemicals for such deleterious effects, though current testing methodologies are time/animal intensive and costly. To screen the large EPA inventory of possible EDC chemicals, other methods must be developed for testing. Protein profiling methodology can be used for high-throughput identification of protein patterns or biomarker "fingerprints" indicative of a change in physiological or disease status. This "fingerprint" can then be used diagnostically to screen for chemical effects. Using Surface Enhanced Laser Desorption/Ionization Time-of-Flight Spectrometry (SELDI-TOF MS), we profiled plasma obtained from sheepshead minnows (Cyprinodon variegatus) for endocrine-related changes in protein patterns. Specifically, the fish were placed into flow-through aquaria consisting of duplicate tanks for treatment with each of the following: vehicle control (triethylene glycol, TEG), estrogen (17 ß-estradiol), EDC positive controls (methoxychlor and bisphenol) and EDC negative controls (endosulfan and chlorpyriphos). Test concentrations were maintained by intermittent seawater flow and injection of the chemical and carrier control treatments. After treatment, fish were sampled for their plasma. The plasma was then applied to ProteinChip® arrays and analyzed. No discriminatory pattern difference was found between protein profiles of seawater control and TEG-treated fish. A number of protein peaks, in the <20 kDa range, exhibited altered expression levels in response to estrogen exposure, with respect to the TEG controls. An estrogen-specific spectral fingerprint was identified using the pattern recognition software, Biomaker Patterns. Using this pattern to diagnostically determine estrogenicity, the two EDC positive controls were classified by the software as estrogenic. The two EDC negative controls were classified as nonestrogenic. This methodology represents a viable and rapid means for assaying chemicals for estrogenic effects. Also, this protocol should be readily transferable to other species and other mechanisms of interest.