Project description:Prochloraz is a fungicide known to cause endocrine disruption through effects on the hypothalamic-pituitary-gonadal (HPG) axis. To determine the short-term impacts of prochloraz on gene expression and steroid production, adult female fathead minnows (Pimephales promelas) were exposed to the chemical (0 or 300 M-NM-<g/L) for a time-course of 6, 12 and 24 h. Consistent with inhibition of cytochrome P450 17M-NM-1-hydroxylase/17,20-lyase (CYP17) and aromatase (CYP19), known molecular targets of prochloraz, plasma 17M-NM-2-estradiol (E2) was reduced within 6 hours. Ex vivo E2 production was significantly reduced at all time-points, while ex vivo testosterone (T) production remained unchanged. Consistent with the decrease in E2 levels, plasma concentrations of the estrogen-responsive protein vitellogenin were significantly reduced at 24 h. Genes coding for CYP19, CYP17, and steroidogenic acute regulatory protein were up-regulated in a compensatory manner in ovaries of the prochloraz-treated fish. In addition to targeted quantitative real-time polymerase chain reaction analyses, a 15k feature fathead minnow microarray was used to determine gene expression profiles in ovaries. From time-point to time-point, the microarray results showed a relatively rapid change in the differentially expressed gene (DEG) profiles associated with the chemical exposure. Functional analysis of the DEGs indicated changes in expression of genes associated with cofactor and coenzyme binding (GO: 0048037 and 0050662), fatty acid binding (GO:0005504) and organelle organization and biogenesis (GO: 0006996). Overall, the results from this study are consistent with compensation of the fish HPG axis to inhibition of steroidogenesis by prochloraz, and provide further insights into relatively rapid, system-wide, effects of a model chemical stressor on fish. RNA samples for each treatment/time point combination were used for microarray analysis (total of 23 arrays). For the microarray work, total RNA was isolated from ovary samples using RNeasy kits (Qiagen, Valencia, CA, USA). The RNA quality was assessed with an Agilent 2100 Bioanalyzer (Agilent, Wilmington, DE, USA) and quantity was determined using a NanodropM-BM-. ND-1000 spectrophotometer. Total RNA was stored at -80oC until analyzed with oligonucleotide microarrays. Microarray analysis was conducted at the US Army Engineer Research and Development Center (Vicksburg, MS, USA) using a 15k feature fathead minnow microarray (GEO: http://www.ncbi.nlm.nih.gov/geo/; Accession platform number GPL9248) designed by Dr. Nancy Denslow (University of Florida, Gainesville, FL, USA) and manufactured by Agilent Technologies (Palo Alto, CA, USA). The Agilent one-color microarray hybridization protocol (One-Color Microarray-Based Gene Expression Analysis, version 5.7, Agilent Technologies) was used for microarray hybridizations. One M-BM-5g of total RNA was used for all hybridizations. The cDNA synthesis, cRNA labeling, amplification and hybridization were performed following the manufacturerM-bM-^@M-^Ys kits and protocols (Quick Amp Labeling kit; Agilent Technologies). An Axon GenePixM-BM-. 4000B Microarray Scanner (Molecular Devices Inc., Sunnyvale, CA, USA) was used to scan microarray images at 5 M-NM-<m resolution. Data were resolved from microarray images using Agilent Feature Extraction software (Agilent Technologies). Statistical analyses were conducted using Statistica 8 (StatSoft Inc., Tulsa, OK, USA) and GraphPad Instat v. 3.01 (GraphPad Software, San Diego, CA, USA). Data were tested for normality and homogeneity of variance. When data conformed to parametric assumptions, data were analyzed using a parametric one-way ANOVA with chemical treatment as the independent variable. When data did not conform to parametric assumptions, they were either transformed (log 10) or analyzed using a non-parametric KruskallM-bM-^@M-^SWallis test (pM-bM-^IM-$ 0.05). The data are presented as means with standard errors of the mean. Differences were considered significant at p M-bM-^IM-$ 0.05. Microarray data were imported into the Rosetta Resolver 7.2 system for gene expression analysis (Rosetta Biosoftware, Kirkland, WA, USA). Data were normalized using the default, text loader, intensity profile builder settings in the Rosetta Resolver system. Significantly DEGs were identified using one-way ANOVA (p < 0.01) with no multiple testing correction
2011-02-03 | E-GEOD-26958 | biostudies-arrayexpress
