David L. Lattier

Quantification and associated variability of induced vitellogenin gene transcripts in fathead minnow (Pimephales promelas) by quantitative real‐time polymerase chain reaction assay

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.

Temporal and spatial variability in the estrogenicity of a municipal wastewater effluent.

The estrogenicity of a municipal wastewater effluent was monitored using the vitellogenin biomarker in adult male fathead minnows (Pimephales promelas). The variability in the expression of vitellogenin was evident among the monitoring periods. Significant (alpha< or =0.05) increases in plasma vitellogenin concentrations were detected in March and December, but not in August or June. Additionally, the magnitude of expression was variable. Variability in the spatial scale was also evident during the March and June exposure months. Concurrent exposures in both the creek receiving the effluent from a wastewater treatment plant and an experimental wetland showed estrogenicity to be different with distance from the respective effluent inflow sites. March exposures showed estrogenicity to be somewhat persistent in the receiving creek (>600 m), but to decrease rapidly within the experimental wetland (<40 m). Results are discussed relative to the monitoring season, to the spatial distribution of the response in both receiving systems, and to possible causative factors contributing to the effluent estrogenicity.

DNA Microarray‐based ecotoxicological biomarker discovery in a small fish model 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 path from molecular indicators of exposure to describing dynamic biological systems in an aquatic organism: microarrays and the fathead minnow.

The extent to which humans and wildlife are exposed to toxicants is an important focus of environmental research. This work has been directed toward the development of molecular indicators diagnostic for exposure to various stressors in freshwater fish. Research includes the discovery of genes, indicative of environmental exposure, in the Agencys long-established aquatic toxicological organism, the fathead minnow (Pimephales promelas). Novel cDNAs and coding sequences will be used in DNA microarray analyses for pattern identification of stressor-specific, differentially up- and down-regulated genes. The methods currently used to discover genes in this organism, for which few annotated nucleic acid sequences exist, are cDNA subtraction libraries, differential display, exploiting PCR primers for known genes of other members of the family Cyprinidae and use of degenerate PCR primers designed from regions of moderate protein homology. Single or multiple genes noted as being differentially expressed in microarray analyses will then be used in separate studies to measure bioavailable stressors in the laboratory and field. These analyses will be accomplished by quantitative RT-PCR. Moving from analysis of single gene exposures to the global state of the transcriptome offers possibilities that those genes identified by DNA microarray analyses might be critical components of dynamic biological systems and networks, wherein chemical stressors exert toxic effects through various modes of action. Additionally, the ability to discriminate bioavailability of stressors in complex environmental mixtures, and correlation with adverse effects downstream from these early molecular events, presents challenging new ground to be broken in the area of risk assessment.

Responses of molecular indicators of exposure in mesocosms: common carp (cyprinus carpio) exposed to the herbicides alachlor and atrazine

Common carp (Cyprinus carpio) were treated in aquatic mesocosms with a single pulse of the herbicides atrazine or alachlor to study the bioavailability and biological activity of these herbicides using molecular indicators: Liver vitellogenin gene expression in male fish for estrogenic activity, liver cytochrome P4501A1 gene expression, and DNA damage in blood cells using the single-cell gel electrophoresis method. Both alachlor and atrazine showed dose-related increases in DNA strand breaks at environmentally relevant concentrations (<100 ppb). Gene expression indicators showed that neither herbicide had estrogenic activity in the carp, whereas atrazine at concentrations as low as 7 ppb induced cytochrome P4501A1. These results support the study of molecular indicators for exposure in surrogate ecosystems to gauge relevant environmental changes following herbicide treatments.

A quantitative real‐time polymerase chain reaction method for the analysis of vitellogenin transcripts in model and nonmodel fish species

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.

DNA microarray application in ecotoxicology: experimental design, microarray scanning, and factors affecting transcriptional profiles in a small fish species.

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.

Proteomic analysis of a model fish species exposed to individual pesticides and a binary mixture

Pesticides are nearly ubiquitous in surface waters of the United States, where they often are found as mixtures. The molecular mechanisms underlying the toxic effects of sub-lethal exposure to pesticides as both individual and mixtures are unclear. The current work aims to identify and compare differentially expressed proteins in brains of male fathead minnows (Pimephales promelas) exposed for 72 h to permethrin (7.5 μg/L), terbufos (57.5 μg/L) and a binary mixture of both. Twenty-four proteins were found to be differentially expressed among all three treatments relative to the control using an ANOVA followed by a Dunnetts post hoc test (p ≤0.05). One protein was found to be differentially expressed among all treatment groups and one protein was in common between the terbufos and the mixture group. Fifteen spots were successfully sequenced using LC-MS/MS sequencing. Proteins associated with the ubiquitin-proteasome system, glycolysis, the cytoskeleton and hypoxia were enriched. As a second objective, we attempted to establish protein expression signatures (PES) for individual permethrin and terbufos exposures. We were unable to generate a useable PES for terbufos; however, the permethrin PES was able to distinguish between control and permethrin-exposed individuals in an independent experiment with an accuracy of 87.5%. This PES also accurately classified permethrin exposed individuals when the exposure occurred as part of a mixture. The identification of proteins differentially expressed as a result of pesticide exposure represent a step forward in the understanding of mechanisms of toxicity of permethrin and terbufos. They also allow a comparison of molecular responses of the binary mixture to single exposures. The permethrin PES is the first step in establishing a method to determine exposures in real-world scenarios.

Proteomic analysis of zebrafish brain tissue following exposure to the pesticide prochloraz

The hypothalamus-pituitary-gonadal (HPG) axis plays a central role in the maintenance of homeostasis and disruptions in its function can have important implications for reproduction and other critical biological processes. A number of compounds found in aquatic environments are known to affect the HPG axis. In the present study, we used two-dimensional electrophoresis to investigate the proteome of female and male zebrafish brain after 96 h exposure to the fungicide prochloraz. Prochloraz has known effects on a number of key HPG molecules, including antagonism of Cyp17 and Cyp19 (aromatase). Twenty-eight proteins were shown to be differentially expressed in the brains of females and 22 in males. Proteins were identified using LC-MS/MS and identities were examined relative to brain function in the context of changing steroid hormone levels. There was little overlap between sexes in proteins exhibiting differential expression. Proteins with known roles in metabolism, learning, neuroprotection, and calcium regulation were determined to be differentially regulated. Relationships between identified proteins were also examined using Ingenuity Pathway Analysis, and females were shown to exhibit enrichment of several metabolic pathways. We used differentially expressed proteins to establish a putative classifier consisting of three proteins that was able to discriminate prochloraz-exposed from control females. Putatively impacted brain functions and specific protein changes that were observed have the potential to be generalized to other that similarly impact steroid hormone levels.

Genomics: Applications, Challenges, and Opportunities for the U.S. Environmental Protection Agency

ABSTRACT Genomics information has great potential to enhance assessment of risks to human health and the environment. Although understanding genomic responses with respect to adverse ecological and human health outcomes is not, as yet, established, it is important to consider the likely future impacts of genomics technologies on risk assessment and decision-making. Four areas are identified as those likely to be influenced by the generation of genomics information within, and the submission of such information to, the U.S. Environmental Protection Agency (USEPA): risk assessment, prioritization of contaminants and contaminated sites, monitoring, and reporting provisions. For each of these risk assessment and regulatory applications, representative activities are presented to illustrate the application. Three major challenges for the USEPA associated with genomics are also identified in the areas of research, technical development, and capacity. The USEPAs initial activities to address these challenges are discussed. The Agency recognizes it must be prepared to use genomics information, and that many scientific, policy, ethical, and legal concerns will need to be addressed. The USEPA also recognizes it is essential to continue to collaborate with other federal agencies, academia, the regulated community, and other stakeholders in order to benefit from ongoing advances in genomics in the wider scientific and regulatory communities.