A Comparison of Two Macroinvertebrate Multi-Plate Sampling Methods to Inform Great Lakes Monitoring and Remediation Efforts.

Hester-Dendy (HD) multi-plate samplers have been widely used by state and federal government agencies for bioassessment of water quality through use of macroinvertebrate community data. To help guide remediation and restoration efforts at the Niagara River Great Lakes Area of Concern site, a multi-agency study was conducted in 2014 to assess the contribution of seven major urban tributaries on the US side of the river toward the impairment of the Niagara River. As part of this study, macroinvertebrate communities were sampled using two co-located versions of HD samplers: one version used by the New York State Department of Environmental Conservation (NYSDEC) and another by the US Environmental Protection Agency Office of Research and Development. Samplers were deployed in tributaries in highly developed watersheds with high percent impervious surface. The two sampling methods varied in terms of number and size of plates, between-plate spacing, and deployment method. Comparison of the similarity/grouping of communities with multivariate ordination techniques, Nonmetric Multidimensional Scaling and Multi-Response Permutation Procedure, showed that both methods were able to detect differences in communities at stations, despite some grouping by month and method. The indices and metrics derived from the two HD methods were found to give comparable but not identical assessments of water quality. Despite their differences, the methods were robust with respect to water quality categories derived from indices used nationally (HBI) and by NY state (BAP). For the common richness metrics, total taxa and EPT richness, there was no statistical difference between means from 3 samplings. Some metrics, especially percent tolerant collector-gatherer individuals, did show significant differences at certain stations. Indicator Species Analysis showed some taxa associated with each method. The observed community differences were thought mostly due to the difference in sampler deployment position.

Characterization of vitellogenin concentration in male fathead minnow mucus compared to plasma, and liver mRNA.

The objective of this study was to characterize vitellogenin (VTG) protein in male fathead minnow (Pimephales promelas) mucus compared with more conventional measures in plasma and mRNA isolated from liver. To assess the intensity and duration of changes in mucus VTG concentrations, male fathead minnows were exposed to 17α-ethinylestradiol (EE2) for 7 days with a subsequent depuration period of 14 days. The experiment was conducted in a flow-through system to maintain a consistent concentration of EE2 at a nominal EC50 concentration of 2.5 ng/L and high concentration of 10 ng/L as a positive control. Mucus, plasma and liver were sampled at regular intervals throughout the study. Relative abundance of vtg mRNA increased after 2 days of exposure and returned to control levels after 4 days of depuration. VTG protein concentration displayed similar induction kinetics in both mucus and plasma, however, it was found to be significantly increased after 2 days of exposure using the mucus-based assays and 7 days with the plasma-based assay. Significantly elevated levels of VTG were detected by both assays throughout the 14-day depuration period. The elimination of the laborious plasma collection step in the mucus-based workflow allowed sampling of smaller organisms where blood volume is limiting. It also resulted in significant gains in workflow efficiency, decreasing sampling time without loss of performance.

Multigene Biomarkers of Pyrethroid Exposure: Exploratory Experiments.

We describe initial development of microarray-based assays for detecting 4 pyrethroid pesticides (bifenthrin, cypermethrin, esfenvalerate, and permethrin) in water. To facilitate comparison of transcriptional responses with gross apical responses, we estimated concentration-mortality curves for these pyrethroids using flow-through exposures of newly hatched Daphnia magna, Pimephales promelas adults, and 24 h posthatch P. promelas. Median lethal concentration (LC50) estimates were below most reported values, perhaps attributable to the use of flow-through exposures or of measured rather than nominal concentrations. Microarray analysis of whole P. promelas larvae and brains from exposed P. promelas adults showed that assays using either tissue type can detect these pyrethroids at concentrations below LC50 values reported for between 72 and 96% of aquatic species, depending on the pesticide. These estimates are conservative because they correspond to the lowest concentrations tested. This suggests that the simpler and less expensive whole-larval assay provides adequate sensitivity for screening contexts where acute aquatic lethality is observed, but the responsible agent is not known. Gene set analysis (GSA) highlighted several Gene Ontology (GO) terms consistent with known pyrethroid action, but the implications of other GO terms are less clear. Exploration of the sensitivity of results to changes in data processing suggests robustness of the detection assay results, but GSA results were sensitive to methodological variations. Environ Toxicol Chem 2019;38:2436-2446. Published 2019 Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work, and as such, is in the public domain in the United States of America.

Presence of pharmaceuticals in fish collected from urban rivers in the U.S. EPA 2008-2009 National Rivers and Streams Assessment.

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-1, 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.

Initial development of a multigene 'omics-based exposure biomarker for pyrethroid pesticides.

Omics technologies have long since promised to address a number of long standing issues related to environmental regulation. Despite considerable resource investment, there are few examples where these tools have been adopted by the regulatory community, which is in part due to a focus of most studies on discovery rather than assay development. The current work describes the initial development of an omics based assay using 48h Pimephales promelas (FHM) larvae for identifying aquatic exposures to pyrethroid pesticides. Larval FHM were exposed to seven concentrations of each of four pyrethroids (permethrin, cypermethrin, esfenvalerate and bifenthrin) in order to establish dose response curves. Then, in three separate identical experiments, FHM were exposed to a single equitoxic concentration of each pyrethroid, corresponding to 33% of the calculated LC50. All exposures were separated by weeks and all materials were either cleaned or replaced between runs in an attempt to maintain independence among exposure experiments. Gene expression classifiers were developed using the random forest algorithm for each exposure and evaluated first by cross-validation using hold out organisms from the same exposure experiment and then against test sets of each pyrethroid from separate exposure experiments. Bifenthrin exposed organisms generated the highest quality classifier, demonstrating an empirical Area Under the Curve (eAUC) of 0.97 when tested against bifenthrin exposed organisms from other exposure experiments and 0.91 against organisms exposed to any of the pyrethroids. An eAUC of 1.0 represents perfect classification with no false positives or negatives. Additionally, the bifenthrin classifier was able to successfully classify organisms from all other pyrethroid exposures at multiple concentrations, suggesting a potential utility for detecting cumulative exposures. Considerable run-to-run variability was observed both in exposure concentrations and molecular responses of exposed fish across exposure experiments. The application of a calibration step in analysis successfully corrected this, resulting in a significantly improved classifier. Classifier evaluation suggested the importance of considering a number of aspects of experimental design when developing an expression based tool for general use in ecological monitoring and risk assessment, such as the inclusion of multiple experimental runs and high replicate numbers.

An integrated assessment of sediment remediation in a midwestern U.S. stream using sediment chemistry, water quality, bioassessment, and fish biomarkers.

A comprehensive biological, sediment, and water quality study of the lower Little Scioto River near Marion, Ohio, USA, was undertaken to evaluate the changes or improvements in biotic measurements following the removal of creosote-contaminated sediment. The study area covered 7.5 river miles (RMs), including a remediated section between RMs 6.0 and 6.8. Fish and macroinvertebrate assemblages, fish biomarkers (i.e., polycyclic aromatic hydrocarbon [PAH] metabolite levels in white sucker [Castostomus commersoni] and common carp [Cyprinus carpio] bile and DNA damage), sediment chemistry, and water quality were assessed at five locations relative to the primary source of historical PAH contamination-upstream (RM 9.2), adjacent (RM 6.5), and downstream (RMs 5.7, 4.4, and 2.7). Overall, the biomarker results were consistent with the sediment PAH results, showing a pattern of low levels of PAH bile metabolites and DNA damage at the upstream (reference or background location), as well as the remediated section, high levels at the two immediate downstream sites, and somewhat lower levels at the furthest downstream site. Results show that remediation was effective in reducing sediment contaminant concentrations and exposure of fish to PAHs and in improving fish assemblages (60% increase in index of biotic integrity scores) in remediated river sections. Additional remedial investigation and potentially further remediation is needed to improve the downstream benthic fish community, which is still heavily exposed to PAH contaminants.

Discovery and validation of gene classifiers for endocrine-disrupting chemicals in zebrafish (danio rerio).

BACKGROUND: Development and application of transcriptomics-based gene classifiers for ecotoxicological applications lag far behind those of biomedical sciences. Many such classifiers discovered thus far lack vigorous statistical and experimental validations. A combination of genetic algorithm/support vector machines and genetic algorithm/K nearest neighbors was used in this study to search for classifiers of endocrine-disrupting chemicals (EDCs) in zebrafish. Searches were conducted on both tissue-specific and tissue-combined datasets, either across the entire transcriptome or within individual transcription factor (TF) networks previously linked to EDC effects. Candidate classifiers were evaluated by gene set enrichment analysis (GSEA) on both the original training data and a dedicated validation dataset. RESULTS: Multi-tissue dataset yielded no classifiers. Among the 19 chemical-tissue conditions evaluated, the transcriptome-wide searches yielded classifiers for six of them, each having approximately 20 to 30 gene features unique to a condition. Searches within individual TF networks produced classifiers for 15 chemical-tissue conditions, each containing 100 or fewer top-ranked gene features pooled from those of multiple TF networks and also unique to each condition. For the training dataset, 10 out of 11 classifiers successfully identified the gene expression profiles (GEPs) of their targeted chemical-tissue conditions by GSEA. For the validation dataset, classifiers for prochloraz-ovary and flutamide-ovary also correctly identified the GEPs of corresponding conditions while no classifier could predict the GEP from prochloraz-brain. CONCLUSIONS: The discrepancies in the performance of these classifiers were attributed in part to varying data complexity among the conditions, as measured to some degree by Fisher's discriminant ratio statistic. This variation in data complexity could likely be compensated by adjusting sample size for individual chemical-tissue conditions, thus suggesting a need for a preliminary survey of transcriptomic responses before launching a full scale classifier discovery effort. Classifier discovery based on individual TF networks could yield more mechanistically-oriented biomarkers. GSEA proved to be a flexible and effective tool for application of gene classifiers but a similar and more refined algorithm, connectivity mapping, should also be explored. The distribution characteristics of classifiers across tissues, chemicals, and TF networks suggested a differential biological impact among the EDCs on zebrafish transcriptome involving some basic cellular functions.

Transcriptional regulatory dynamics of the hypothalamic-pituitary-gonadal axis and its peripheral pathways as impacted by the 3-beta HSD inhibitor trilostane in zebrafish (Danio rerio).

To study mechanisms underlying generalized effects of 3ß hydroxysteroid dehydrogenase (HSD3B) inhibition, reproductively mature zebrafish (Danio rerio) were exposed to trilostane at two dosages for 24, 48, or 96 h and their gonadal RNA samples profiled with Agilent zebrafish microarrays. Trilostane had substantial impact on the transcriptional dynamics of zebrafish, as reflected by a number of differentially expressed genes (DEGs) including transcription factors (TFs), altered TF networks, signaling pathways, and Gene Ontology (GO) biological processes. Changes in gene expression between a treatment and its control were mostly moderate, ranging from 1.3 to 2.0 fold. Expression of genes coding for HSD3B and many of its transcriptional regulators remained unchanged, suggesting transcriptional up-regulation is not a primary compensatory mechanism for HSD3B enzyme inhibition. While some trilostane-responsive TFs appear to share cellular functions linked to endocrine disruption, there are also many other DEGs not directly linked to steroidogenesis. Of the 65 significant TF networks, little similarity, and therefore little cross-talk, existed between them and the hypothalamic-pituitary-gonadal (HPG) axis. The most enriched GO biological processes are regulations of transcription, phosphorylation, and protein kinase activity. Most of the impacted TFs and TF networks are involved in cellular proliferation, differentiation, migration, and apoptosis. While these functions are fairly broad, their underlying TF networks may be useful to development of generalized toxicological screening methods. These findings suggest that trilostane-induced effects on fish endocrine functions are not confined to the HPG-axis alone. Its impact on corticosteroid synthesis could also have contributed to some system wide transcriptional changes in zebrafish observed in this study.

Gene expression profiling of the androgen receptor antagonists flutamide and vinclozolin in zebrafish (Danio rerio) gonads.

The studies presented in this manuscript focus on characterization of transcriptomic responses to anti-androgens in zebrafish (Danio rerio). Research on the effects of anti-androgens in fish has been characterized by a heavy reliance on apical endpoints, and molecular mechanisms of action (MOA) of anti-androgens remain poorly elucidated. In the present study, we examined effects of a short term exposure (24-96h) to the androgen receptor antagonists flutamide (FLU) and vinclozolin (VZ) on gene expression in gonads of sexually mature zebrafish, using commercially available zebrafish oligonucleotide microarrays (4×44K platform). We found that VZ and FLU potentially impact reproductive processes via multiple pathways related to steroidogenesis, spermatogenesis, and fertilization. Observed changes in gene expression often were shared by VZ and FLU, as demonstrated by overlap in differentially-expressed genes and enrichment of several common key pathways including: (1) integrin and actin signaling, (2) nuclear receptor 5A1 signaling, (3) fibroblast growth factor receptor signaling, (4) polyamine synthesis, and (5) androgen synthesis. This information should prove useful to elucidating specific mechanisms of reproductive effects of anti-androgens in fish, as well as developing biomarkers for this important class of endocrine-active chemicals.

A transcriptomics-based biological framework for studying mechanisms of endocrine disruption in small fish species.

This study sought to construct a transcriptomics-based framework of signal transduction pathways, transcriptional regulatory networks, and the hypothalamic-pituitary gonadal (HPG) axis in zebrafish (Danio rerio) to facilitate formulation of specific, testable hypotheses regarding the mechanisms of endocrine disruption in fish. For the analyses involved, we used data from a total of more than 300 microarrays representing 58 conditions, which encompassed 4 tissue types from zebrafish of both genders exposed for 1 of 3 durations to 10 different test chemicals (17alpha-ethynyl estradiol, fadrozole, 17beta-trenbolone, fipronil, prochloraz, flutamide, muscimol, ketoconazole, trilostane, and vinclozolin). Differentially expressed genes were identified by one class t-tests for each condition, and those with false discovery rates of less than 40% and treatment/control ratios > or =1.3-fold were mapped to orthologous human, mouse, and rat pathways by Ingenuity Pathway Analysis to look for overrepresentation of known biological pathways. To complement the analysis of known biological pathways, the genes regulated by approximately 1800 transcription factors were inferred using the ARACNE mutual information-based algorithm. The resulting gene sets for all transcriptional factors, along with a group of compiled HPG-axis genes and approximately 130 publicly available biological pathways, were analyzed for their responses to the 58 treatment conditions by Gene Set Enrichment Analysis (GSEA) and its variant, Extended-GSEA. The biological pathways and transcription factors associated with multiple distinct treatments showed substantial interactions among the HPG-axis, TGF-beta, p53, and several of their cross-talking partners. These candidate networks/pathways have a variety of profound impacts on such cellular functions as stress response, cell cycle, and apoptosis.

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.

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.

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.

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.