Ecological risk assessors have a growing need for sensitive and rapid indicators of environmental exposures in aquatic ecosystems resulting from natural and synthetic estrogen-like compounds. Investigators developing subcellular exposure markers in traditional sentinel organisms must be vigilant about inherent variability of analyses, especially regarding regulatory and policy statements. Here, we report a quantitative real-time polymerase chain reaction (QPCR) assay for the detection of vitellogenin transcripts environmentally triggered in fathead minnows (Pimephales promelas). We demonstrate that our QPCR assay exhibits little inter- or intra-assay variability (21.7 and 11.9%, respectively). This method appears to be robust in terms of variability stemming from extrinsic sources, indicating that it may be readily transferable to laboratories having the requisite equipment. Our primary focus in development of this method derived from the observation that transcriptional responses of the vitellogenin gene (vtg) in fathead minnows demonstrated high biological variability between identically treated individuals, even under controlled laboratory conditions (coefficient of variation, > 100%). This variability was not seen in other genes from the same RNA preparations that we examined, suggesting that it is specific to the vitellogenin response. Our data and those of others suggest that variability in vtg expression is common to a number of aquatic vertebrates, which is indicative of genetic causation. Despite a relatively high degree of variability in vtg transcription, this method is sensitive enough to detect exposures of 5.0 ng 17alpha-ethinylestradiol (EE2)/L within 24 h of exposure, and it has the ability to discriminate 10.0 and 5.0 ng EE2/L within 48 h. The vitellogenin QPCR assay is a highly sensitive, comparatively rapid, and inexpensive method for the detection and characterization of exposure to environmental estrogens and estrogen mimics.
Fish are good indicators of aquatic environment pollution because of their capability to uptake pollutants contained in water. Therefore, accumulation of pharmaceutical compounds in freshwater and marine fish and other aquatic organisms has been studied extensively in the last decade. In this context, the present study investigates the occurrence of pharmaceutical compounds in wild fish from 25 polluted river sites in the USA, downstream from wastewater treatment plants (WWTPs). Sample sites constitute a subset of urban rivers investigated in the U.S. EPA's 2008-2009 National Rivers and Streams Assessment. Thirteen pharmaceuticals (out of the twenty compounds analyzed) were quantified in fish fillets at concentrations commonly below 10ngg, in accordance with the findings from previous studies in the USA and Europe. The psychoactive drugs venlafaxine, carbamazepine and its metabolite 2-hydroxy carbamazepine were the most prevalent compounds (58%, 27% and 42%, respectively). This group of drugs is highly prescribed and rather resistant to degradation during conventional treatment in WWTPs as well as in natural aquatic environments. Salbutamol, a drug used to treat asthma, and the diuretic hydrochlorothiazide were also frequently detected (in >20% of the samples). Occurrence of six pharmaceutical families due to chronic exposure at environmental concentrations in water was detected in eight fish species.
As potential biomarkers, gene classifiers are gene expression signatures or patterns capable of distinguishing biological samples belonging to different classes or conditions. This is the second of two papers on profiling gene expression in zebrafish (Danio rerio) treated with endocrine-disrupting chemicals of different modes of action, with a focus on comparative analysis of microarray data for gene classifier discovery. Various combinations of gene feature selection/class prediction algorithms were evaluated, with the use of microarray data organized by a chemical stressor or tissue type, for their accuracy in determining the class memberships of independent test samples. Two-way clustering of gene classifiers and treatment conditions offered another alternative to assess the performance of these potential biomarkers. Both gene feature selection methods and class prediction algorithms were shown to be important in identifying successful gene classifiers. The genetic algorithm and support vector machine yielded classifiers with the best prediction accuracy, regardless of sample size, nature of class prediction, and data complexity. A chemical stressor significantly altering the expression of a greater number of genes tended to generate gene classifiers with better performance. All combinations of gene feature selection/class prediction algorithms performed similarly well with data of high signal to noise ratio. Gene classifier discovery and application on the basis of individual sampling and sample data pooling, respectively, were found to enhance class predictions. Gene expression profiles of the top gene classifiers, identified from both microarray and quantitative polymerase chain reaction assays, displayed greater similarity between fadrozole and 17beta-trenbolone than either one to 17alpha-ethinylestradiol. These gene classifiers could serve as potential biomarkers of exposure to specific classes of endocrine disruptors.
The measurement of vitellogenin (vtg) gene transcription has been shown to be a reliable indicator of exposure to estrogenic compounds. Unfortunately, the relatively poor molecular characterization of North American fish species has hindered its application to a larger number of ecologically important species. The current research aimed to demonstrate specific amplification of vtg gene transcripts in three model (zebrafish, rainbow trout, and medaka) and six nonmodel (emerald shiner, pearl dace, smallmouth bass, creek chub, white sucker, and golden redhorse) fish species. Quantitative polymerase chain reaction (QPCR) primers for model species were designed from publicly available vtg sequences. Successful amplification of vtg was demonstrated in fish exposed to 17alpha-ethinylestradiol (EE(2)) for all model species. Vitellogenin primers for selected nonmodel species were designed from published sequences of closely related species. Multiple primers were developed targeting different regions of the vtg gene. The successful amplification of vtg was confirmed through size and sequence analysis for all nonmodel species with the exception of the white sucker, in which amplifications failed. Furthermore, QPCR primers and conditions were quantitative over five orders of magnitude in at least one species (pearl dace) exposed to 5 ng/L of EE(2) for 24 h. The selected species are found in a wide array of ecological habitats that span the United States. Inclusion of vtg transcriptional analysis for wild, ecologically relevant fish in monitoring studies may aid in understanding the extent of estrogenic exposure in aquatic ecosystems across the United States.
The research presented here is part of a larger study of the molecular mode of action of endocrine-disrupting chemicals targeting the hypothalamic-pituitary-gonadal axis in zebrafish (Danio rerio). It addresses several issues critical to microarray application in aquatic ecotoxicology: experimental design, microarray scanning, gene expression intensity distribution, and the effect of experimental parameters on the zebrafish transcriptome. Expression profiles from various tissues of individual zebrafish exposed to 17alpha-ethinylestradiol (30 ng/L), fadrozole (25 micro.g/L), or 17beta-trenbolone (3.0 microg/L) for 48 or 96 h were examined with the Agilent Oligo Microarray (G2518A). As a flexible and efficient alternative to the designs commonly used in microarray studies, an unbalanced incomplete block design was found to be well suited for this work, as evidenced by high data reproducibility, low microarray-to-microarray variability, and little gene-specific dye bias. Random scanner noise had little effect on data reproducibility. A low-level, slightly variable Cyanine 3 (Cy3) contaminant was revealed by hyperspectral imaging, suggesting fluorescence contamination as a potential contributor to the large variance associated with weakly expressed genes. Expression intensities of zebrafish genes were skewed toward the lower end of their distribution range, and more weakly expressed genes tended to have larger variances. Tissue type, followed in descending order by gender, chemical treatment, and exposure duration, had the greatest effect on the overall gene expression profiles, a finding potentially critical to experimental design optimization. Overall, congruence was excellent between quantitative polymerase chain reaction results and microarray profiles of 13 genes examined across a subset of 20 pairs of ovarian samples. These findings will help to improve applications of microarrays in future ecotoxicological studies.
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