Gene Expression and Pathway Analysis in Rat Brain and Liver After Exposure to Royal Demolition Explosive (Hexahydro-1,3,5-Trinitro-1,3,5-Triazine).

The nitramine explosive, hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) is associated with acute and chronic toxicity in mammals and targets both the central nervous system and liver. After a single oral dose of RDX in male rats, the systemic distribution of RDX and the toxicodynamic response was measured using clinical chemistry and Affymetrix Rat Genome® 230 2.0 gene expression arrays, respectively. Nominal doses of 0, 9 and 36 mg/kg pure RDX were administered to animals followed by liver, cerebral cortex, and hippocampus gene expression analysis at 0, 3.5, 24, and 48 hours. RDX quickly entered the liver and brain, increasing up to 24 hours. For the 36 mg/kg dose, RDX was still measurable in liver and brain at 48 hours, but was non-detectible for the 9 mg/kg dose. At 3.5 hours, the time within which most convulsions reportedly occur after RDX ingestion, the hippocampus displayed the highest response for both gene expression and pathways, while the cortex was relatively non-responsive. The top 2 impacted pathways, primarily involved in neurotransmission, were the GABAergic and glutamatergic pathways. High numbers of genes also responded to RDX in the liver with P450 metabolism pathways significantly involved. Compared to the liver, the hippocampus displayed more consistent biological effects across dose and time with neurotransmission pathways predominating. Overall, based on gene expression data, RDX responses were high in both the hippocampus and liver, but were minimal in the cerebral cortex. These results identify the hippocampus as an important target for RDX based on gene expression.

Current ecotoxicity testing needs among selected U.S. federal agencies.

U.S. regulatory and research agencies use ecotoxicity test data to assess the hazards associated with substances that may be released into the environment, including but not limited to industrial chemicals, pharmaceuticals, pesticides, food additives, and color additives. These data are used to conduct hazard assessments and evaluate potential risks to aquatic life (e.g., invertebrates, fish), birds, wildlife species, or the environment. To identify opportunities for regulatory uses of non-animal replacements for ecotoxicity tests, the needs and uses for data from tests utilizing animals must first be clarified. Accordingly, the objective of this review was to identify the ecotoxicity test data relied upon by U.S. federal agencies. The standards, test guidelines, guidance documents, and/or endpoints that are used to address each of the agencies' regulatory and research needs regarding ecotoxicity testing are described in the context of their application to decision-making. Testing and information use, needs, and/or requirements relevant to the regulatory or programmatic mandates of the agencies taking part in the Interagency Coordinating Committee on the Validation of Alternative Methods Ecotoxicology Workgroup are captured. This information will be useful for coordinating efforts to develop and implement alternative test methods to reduce, refine, or replace animal use in chemical safety evaluations.

Keanu: a novel visualization tool to explore biodiversity in metagenomes.

BACKGROUND: One of the main challenges when analyzing complex metagenomics data is the fact that large amounts of information need to be presented in a comprehensive and easy-to-navigate way. In the process of analyzing FASTQ sequencing data, visualizing which organisms are present in the data can be useful, especially with metagenomics data or data suspected to be contaminated. Here, we describe the development and application of a command-line tool, Keanu, for visualizing and exploring sample content in metagenomics data. We developed Keanu as an interactive tool to make viewing complex data easier. RESULTS: Keanu, a tool for exploring sequence content, helps a user to understand the presence and abundance of organisms in a sample by analyzing alignments against a database that contains taxonomy data and displaying them in an interactive web page. The content of a sample can be presented either as a collapsible tree, with node size indicating abundance, or as a bilevel partition graph, with arc size indicating abundance. Here, we illustrate how Keanu works by exploring shotgun metagenomics data from a sample collected from a bluff that contained paleosols and a krotovina in an alpine site in Ft. Greely, Alaska. CONCLUSIONS: Keanu provides a simple means by which researchers can explore and visualize species present in sequence data generated from complex communities and environments. Keanu is written in Python and is freely available at https://github.com/IGBB/keanu .

Multiple environmental stressors induce complex transcriptomic responses indicative of phenotypic outcomes in Western fence lizard.

BACKGROUND: The health and resilience of species in natural environments is increasingly challenged by complex anthropogenic stressor combinations including climate change, habitat encroachment, and chemical contamination. To better understand impacts of these stressors we examined the individual- and combined-stressor impacts of malaria infection, food limitation, and 2,4,6-trinitrotoluene (TNT) exposures on gene expression in livers of Western fence lizards (WFL, Sceloporus occidentalis) using custom WFL transcriptome-based microarrays. RESULTS: Computational analysis including annotation enrichment and correlation analysis identified putative functional mechanisms linking transcript expression and toxicological phenotypes. TNT exposure increased transcript expression for genes involved in erythropoiesis, potentially in response to TNT-induced anemia and/or methemoglobinemia and caused dose-specific effects on genes involved in lipid and overall energy metabolism consistent with a hormesis response of growth stimulation at low doses and adverse decreases in lizard growth at high doses. Functional enrichment results were indicative of inhibited potential for lipid mobilization and catabolism in TNT exposures which corresponded with increased inguinal fat weights and was suggestive of a decreased overall energy budget. Malaria infection elicited enriched expression of multiple immune-related functions likely corresponding to increased white blood cell (WBC) counts. Food limitation alone enriched functions related to cellular energy production and decreased expression of immune responses consistent with a decrease in WBC levels. CONCLUSIONS: Despite these findings, the lizards demonstrated immune resilience to malaria infection under food limitation with transcriptional results indicating a fully competent immune response to malaria, even under bio-energetic constraints. Interestingly, both TNT and malaria individually increased transcriptional expression of immune-related genes and increased overall WBC concentrations in blood; responses that were retained in the TNT x malaria combined exposure. The results demonstrate complex and sometimes unexpected responses to multiple stressors where the lizards displayed remarkable resiliency to the stressor combinations investigated.

Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology.

A quantitative adverse outcome pathway (qAOP) consists of one or more biologically based, computational models describing key event relationships linking a molecular initiating event (MIE) to an adverse outcome. A qAOP provides quantitative, dose-response, and time-course predictions that can support regulatory decision-making. Herein we describe several facets of qAOPs, including (a) motivation for development, (b) technical considerations, (c) evaluation of confidence, and (d) potential applications. The qAOP used as an illustrative example for these points describes the linkage between inhibition of cytochrome P450 19A aromatase (the MIE) and population-level decreases in the fathead minnow (FHM; Pimephales promelas). The qAOP consists of three linked computational models for the following: (a) the hypothalamic-pitutitary-gonadal axis in female FHMs, where aromatase inhibition decreases the conversion of testosterone to 17ß-estradiol (E2), thereby reducing E2-dependent vitellogenin (VTG; egg yolk protein precursor) synthesis, (b) VTG-dependent egg development and spawning (fecundity), and (c) fecundity-dependent population trajectory. While development of the example qAOP was based on experiments with FHMs exposed to the aromatase inhibitor fadrozole, we also show how a toxic equivalence (TEQ) calculation allows use of the qAOP to predict effects of another, untested aromatase inhibitor, iprodione. While qAOP development can be resource-intensive, the quantitative predictions obtained, and TEQ-based application to multiple chemicals, may be sufficient to justify the cost for some applications in regulatory decision-making.

Prioritization of Contaminants of Emerging Concern in Wastewater Treatment Plant Discharges Using Chemical:Gene Interactions in Caged Fish.

We examined whether contaminants present in surface waters could be prioritized for further assessment by linking the presence of specific chemicals to gene expression changes in exposed fish. Fathead minnows were deployed in cages for 2, 4, or 8 days at three locations near two different wastewater treatment plant discharge sites in the Saint Louis Bay, Duluth, MN and one upstream reference site. The biological impact of 51 chemicals detected in the surface water of 133 targeted chemicals was determined using biochemical endpoints, exposure activity ratios for biological and estrogenic responses, known chemical:gene interactions from biological pathways and knowledge bases, and analysis of the covariance of ovary gene expression with surface water chemistry. Thirty-two chemicals were significantly linked by covariance with expressed genes. No estrogenic impact on biochemical endpoints was observed in male or female minnows. However, bisphenol A (BPA) was identified by chemical:gene covariation as the most impactful estrogenic chemical across all exposure sites. This was consistent with identification of estrogenic effects on gene expression, high BPA exposure activity ratios across all test sites, and historical analysis of the study area. Gene expression analysis also indicated the presence of nontargeted chemicals including chemotherapeutics consistent with a local hospital waste stream. Overall impacts on gene expression appeared to be related to changes in treatment plant function during rain events. This approach appears useful in examining the impacts of complex mixtures on fish and offers a potential route in linking chemical exposure to adverse outcomes that may reduce population sustainability.

Rapid effects of the aromatase inhibitor fadrozole on steroid production and gene expression in the ovary of female fathead minnows (Pimephales promelas).

Cytochrome P450 aromatase catalyzes conversion of C19 androgens to C18 estrogens and is critical for normal reproduction in female vertebrates. Fadrozole is a model aromatase inhibitor that has been shown to suppress estrogen production in the ovaries of fish. However, little is known about the early impacts of aromatase inhibition on steroid production and gene expression in fish. Adult female fathead minnows (Pimephales promelas) were exposed via water to 0, 5, or 50µg fadrozole/L for a time-course of 0.5, 1, 2, 4, and 6h, or 0 or 50µg fadrozole/L for a time-course of 6, 12, and 24h. We examined ex vivo ovarian 17ß-estradiol (E2) and testosterone (T) production, and plasma E2 concentrations from each study. Expression profiles of genes known or hypothesized to be impacted by fadrozole including aromatase (cytochrome P450 [cyp] 19a1a), steriodogenic acute regulatory protein (star), cytochrome P450 side-chain cleavage (cyp11a), cytochrome P450 17 alpha hydroxylase/17,20 lyase (cyp17), and follicle stimulating hormone receptor (fshr) were measured in the ovaries by quantitative real-time polymerase chain reaction (QPCR). In addition, broader ovarian gene expression was examined using a 15k fathead minnow microarray. The 5µg/L exposure significantly reduced ex vivo E2 production by 6h. In the 50µg/L treatment, ex vivo E2 production was significantly reduced after just 2h of exposure and remained depressed at all time-points examined through 24h. Plasma E2 concentrations were significantly reduced as early as 4h after initiation of exposure to either 5 or 50µg fadrozole/L and remained depressed throughout 24h in the 50µg/L exposure. Ex vivo T concentrations remained unchanged throughout the time-course. Expression of transcripts involved in steroidogenesis increased within the first 24h suggesting rapid induction of a mechanism to compensate for fadrozole inhibition of aromatase. Microarray results also showed fadrozole exposure caused concentration- and time-dependent changes in gene expression profiles in many HPG-axis pathways as early as 4h. This study provides insights into the very rapid effects of aromatase inhibition on steroidogenic processes in fish.

Predicting chemical bioavailability using microarray gene expression data and regression modeling: A tale of three explosive compounds.

BACKGROUND: Chemical bioavailability is an important dose metric in environmental risk assessment. Although many approaches have been used to evaluate bioavailability, not a single approach is free from limitations. Previously, we developed a new genomics-based approach that integrated microarray technology and regression modeling for predicting bioavailability (tissue residue) of explosives compounds in exposed earthworms. In the present study, we further compared 18 different regression models and performed variable selection simultaneously with parameter estimation. RESULTS: This refined approach was applied to both previously collected and newly acquired earthworm microarray gene expression datasets for three explosive compounds. Our results demonstrate that a prediction accuracy of R(2) = 0.71-0.82 was achievable at a relatively low model complexity with as few as 3-10 predictor genes per model. These results are much more encouraging than our previous ones. CONCLUSION: This study has demonstrated that our approach is promising for bioavailability measurement, which warrants further studies of mixed contamination scenarios in field settings.

Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles.

BACKGROUND: A very large and rapidly growing collection of transcriptomic profiles in public repositories is potentially of great value to developing data-driven bioinformatics applications for toxicology/ecotoxicology. Modeled on human connectivity mapping (Cmap) in biomedical research, this study was undertaken to investigate the utility of an analogous Cmap approach in ecotoxicology. Over 3500 zebrafish (Danio rerio) and fathead minnow (Pimephales promelas) transcriptomic profiles, each associated with one of several dozen chemical treatment conditions, were compiled into three distinct collections of rank-ordered gene lists (ROGLs) by species and microarray platforms. Individual query signatures, each consisting of multiple gene probes differentially expressed in a chemical condition, were used to interrogate the reference ROGLs. RESULTS: Informative connections were established at high success rates within species when, as defined by their mechanisms of action (MOAs), both query signatures and ROGLs were associated with the same or similar chemicals. Thus, a simple query signature functioned effectively as an exposure biomarker without need for a time-consuming process of development and validation. More importantly, a large reference database of ROGLs also enabled a query signature to cross-interrogate other chemical conditions with overlapping MOAs, leading to novel groupings and subgroupings of seemingly unrelated chemicals at a finer resolution. This approach confirmed the identities of several estrogenic chemicals, as well as a polycyclic aromatic hydrocarbon and a neuro-toxin, in the largely uncharacterized water samples near several waste water treatment plants, and thus demonstrates its future potential utility in real world applications. CONCLUSIONS: The power of Cmap should grow as chemical coverages of ROGLs increase, making it a framework easily scalable in the future. The feasibility of toxicity extrapolation across fish species using Cmap needs more study, however, as more gene expression profiles linked to chemical conditions common to multiple fish species are needed.

A weight of evidence assessment approach for adverse outcome pathways.

The adverse outcome pathway (AOP) is a framework to mechanistically link molecular initiating events to adverse biological outcomes. From a regulatory perspective, it is of crucial importance to determine the confidence for the AOP in question as well as the quality of data available in supporting this evaluation. A weight of evidence approach has been proposed for this task, but many of the existing frameworks for weight of evidence evaluation are qualitative and there is not clear guidance regarding how weight of evidence should be calculated for an AOP. In this paper we advocate the use of a subject matter expertise driven approach for weight of evidence evaluation based on criteria and metrics related to data quality and the strength of causal linkages between key events. As a demonstration, we notionally determine weight of evidence scores for two AOPs: Non-competitive ionotropic GABA receptor antagonism leading to epileptic seizures, and Antagonist-binding and stabilization of a co-repressor to the peroxisome proliferator-activated receptor α (PPARα) signaling complex ultimately causing starvation-like weight loss.

Daphnia magna's sense of competition: intra-specific interactions (ISI) alter life history strategies and increase metals toxicity.

This work investigates whether the scale-up to multi-animal exposures that is commonly applied in genomics studies provides equivalent toxicity outcomes to single-animal experiments of standard Daphnia magna toxicity assays. Specifically, we tested the null hypothesis that intraspecific interactions (ISI) among D. magna have neither effect on the life history strategies of this species, nor impact toxicological outcomes in exposure experiments with Cu and Pb. The results show that ISI significantly increased mortality of D. magna in both Cu and Pb exposure experiments, decreasing 14 day LC50 s and 95 % confidence intervals from 14.5 (10.9-148.3) to 8.4 (8.2-8.7) µg Cu/L and from 232 (156-4810) to 68 (63-73) µg Pb/L. Additionally, ISI potentiated Pb impacts on reproduction eliciting a nearly 10-fold decrease in the no-observed effect concentration (from 236 to 25 µg/L). As an indication of environmental relevance, the effects of ISI on both mortality and reproduction in Pb exposures were sustained at both high and low food rations. Furthermore, even with a single pair of Daphnia, ISI significantly increased (p < 0.05) neonate production in control conditions, demonstrating that ISI can affect life history strategy. Given these results we reject the null hypothesis and conclude that results from scale-up assays cannot be directly applied to observations from single-animal assessments in D. magna. We postulate that D. magna senses chemical signatures of conspecifics which elicits changes in life history strategies that ultimately increase susceptibility to metal toxicity.

Systems toxicology identifies mechanistic impacts of 2-amino-4,6-dinitrotoluene (2A-DNT) exposure in Northern Bobwhite.

BACKGROUND: A systems toxicology investigation comparing and integrating transcriptomic and proteomic results was conducted to develop holistic effects characterizations for the wildlife bird model, Northern bobwhite (Colinus virginianus) dosed with the explosives degradation product 2-amino-4,6-dinitrotoluene (2A-DNT). A subchronic 60 d toxicology bioassay was leveraged where both sexes were dosed via daily gavage with 0, 3, 14, or 30 mg/kg-d 2A-DNT. Effects on global transcript expression were investigated in liver and kidney tissue using custom microarrays for C. virginianus in both sexes at all doses, while effects on proteome expression were investigated in liver for both sexes and kidney in males, at 30 mg/kg-d. RESULTS: As expected, transcript expression was not directly indicative of protein expression in response to 2A-DNT. However, a high degree of correspondence was observed among gene and protein expression when investigating higher-order functional responses including statistically enriched gene networks and canonical pathways, especially when connected to toxicological outcomes of 2A-DNT exposure. Analysis of networks statistically enriched for both transcripts and proteins demonstrated common responses including inhibition of programmed cell death and arrest of cell cycle in liver tissues at 2A-DNT doses that caused liver necrosis and death in females. Additionally, both transcript and protein expression in liver tissue was indicative of induced phase I and II xenobiotic metabolism potentially as a mechanism to detoxify and excrete 2A-DNT. Nuclear signaling assays, transcript expression and protein expression each implicated peroxisome proliferator-activated receptor (PPAR) nuclear signaling as a primary molecular target in the 2A-DNT exposure with significant downstream enrichment of PPAR-regulated pathways including lipid metabolic pathways and gluconeogenesis suggesting impaired bioenergetic potential. CONCLUSION: Although the differential expression of transcripts and proteins was largely unique, the consensus of functional pathways and gene networks enriched among transcriptomic and proteomic datasets provided the identification of many critical metabolic functions underlying 2A-DNT toxicity as well as impaired PPAR signaling, a key molecular initiating event known to be affected in di- and trinitrotoluene exposures.

Relating suborganismal processes to ecotoxicological and population level endpoints using a bioenergetic model.

Ecological effects of environmental stressors are commonly evaluated using organismal or suborganismal data, such as standardized toxicity tests that characterize responses of individuals (e.g., mortality and reproduction) and a rapidly growing body of "omics" data. A key challenge for environmental risk assessment is relating such information to population dynamics. One approach uses dynamic energy budget (DEB) models that relate growth and reproduction of individuals to underlying flows of energy and elemental matter. We hypothesize that suborganismal information identifies DEB parameters that are most likely impacted by a particular stressor and that the DEB model can then project suborganismal effects on life history and population endpoints. We formulate and parameterize a model of growth and reproduction for the water flea Daphnia magna. Our model resembles previous generic bioenergetic models, but has explicit representation of discrete molts, an important feature of Daphnia life history. We test its ability to predict six endpoints commonly used in chronic toxicity studies in specified food environments. With just one adjustable parameter, the model successfully predicts growth and reproduction of individuals from a wide array of experiments performed in multiple laboratories using different clones of D. magna raised on different food sources. Fecundity is the most sensitive endpoint, and there is broad correlation between the sensitivities of fecundity and long-run growth rate, as is desirable for the default metric used in chronic toxicity tests. Under some assumptions, we can combine our DEB model with the Euler-Lotka equation to estimate longrun population growth rates at different food levels. A review of Daphnia gene-expression experiments on the effects of contaminant exposure reveals several connections to model parameters, in particular a general trend of increased transcript expression of genes involved in energy assimilation and utilization at concentrations affecting growth and reproduction. The sensitivity of fecundity to many model parameters was consistent with frequent generalized observations of decreased expression of genes involved in reproductive physiology, but interpretation of these observations requires further mechanistic modeling. We thus propose an approach based on generic DEB models incorporating few essential species-specific features for rapid extrapolation of ecotoxicogenomic assays for Daphnia-based population risk assessment.

Identification of biomarkers that distinguish chemical contaminants based on gene expression profiles.

BACKGROUND: High throughput transcriptomics profiles such as those generated using microarrays have been useful in identifying biomarkers for different classification and toxicity prediction purposes. Here, we investigated the use of microarrays to predict chemical toxicants and their possible mechanisms of action. RESULTS: In this study, in vitro cultures of primary rat hepatocytes were exposed to 105 chemicals and vehicle controls, representing 14 compound classes. We comprehensively compared various normalization of gene expression profiles, feature selection and classification algorithms for the classification of these 105 chemicals into14 compound classes. We found that normalization had little effect on the averaged classification accuracy. Two support vector machine (SVM) methods, LibSVM and sequential minimal optimization, had better classification performance than other methods. SVM recursive feature selection (SVM-RFE) had the highest overfitting rate when an independent dataset was used for a prediction. Therefore, we developed a new feature selection algorithm called gradient method that had a relatively high training classification as well as prediction accuracy with the lowest overfitting rate of the methods tested. Analysis of biomarkers that distinguished the 14 classes of compounds identified a group of genes principally involved in cell cycle function that were significantly downregulated by metal and inflammatory compounds, but were induced by anti-microbial, cancer related drugs, pesticides, and PXR mediators. CONCLUSIONS: Our results indicate that using microarrays and a supervised machine learning approach to predict chemical toxicants, their potential toxicity and mechanisms of action is practical and efficient. Choosing the right feature and classification algorithms for this multiple category classification and prediction is critical.

MicroRNA and messenger RNA profiling reveals new biomarkers and mechanisms for RDX induced neurotoxicity.

BACKGROUND: RDX is a well-known pollutant to induce neurotoxicity. MicroRNAs (miRNA) and messenger RNA (mRNA) profiles are useful tools for toxicogenomics studies. It is worthy to integrate MiRNA and mRNA expression data to understand RDX-induced neurotoxicity. RESULTS: Rats were treated with or without RDX for 48 h. Both miRNA and mRNA profiles were conducted using brain tissues. Nine miRNAs were significantly regulated by RDX. Of these, 6 and 3 miRNAs were up- and down-regulated respectively. The putative target genes of RDX-regulated miRNAs were highly nervous system function genes and pathways enriched. Fifteen differentially genes altered by RDX from mRNA profiles were the putative targets of regulated miRNAs. The induction of miR-71, miR-27ab, miR-98, and miR-135a expression by RDX, could reduce the expression of the genes POLE4, C5ORF13, SULF1 and ROCK2, and eventually induce neurotoxicity. Over-expression of miR-27ab, or reduction of the expression of unknown miRNAs by RDX, could up-regulate HMGCR expression and contribute to neurotoxicity. RDX regulated immune and inflammation response miRNAs and genes could contribute to RDX- induced neurotoxicity and other toxicities as well as animal defending reaction response to RDX exposure. CONCLUSIONS: Our results demonstrate that integrating miRNA and mRNA profiles is valuable to indentify novel biomarkers and molecular mechanisms for RDX-induced neurological disorder and neurotoxicity.

Coral-zooxanthellae meta-transcriptomics reveals integrated response to pollutant stress.

BACKGROUND: Corals represent symbiotic meta-organisms that require harmonization among the coral animal, photosynthetic zooxanthellae and associated microbes to survive environmental stresses. We investigated integrated-responses among coral and zooxanthellae in the scleractinian coral Acropora formosa in response to an emerging marine pollutant, the munitions constituent, 1,3,5-trinitro-1,3,5 triazine (RDX; 5 day exposures to 0 (control), 0.5, 0.9, 1.8, 3.7, and 7.2 mg/L, measured in seawater). RESULTS: RDX accumulated readily in coral soft tissues with bioconcentration factors ranging from 1.1 to 1.5. Next-generation sequencing of a normalized meta-transcriptomic library developed for the eukaryotic components of the A. formosa coral holobiont was leveraged to conduct microarray-based global transcript expression analysis of integrated coral/zooxanthellae responses to the RDX exposure. Total differentially expressed transcripts (DET) increased with increasing RDX exposure concentrations as did the proportion of zooxanthellae DET relative to the coral animal. Transcriptional responses in the coral demonstrated higher sensitivity to RDX compared to zooxanthellae where increased expression of gene transcripts coding xenobiotic detoxification mechanisms (i.e. cytochrome P450 and UDP glucuronosyltransferase 2 family) were initiated at the lowest exposure concentration. Increased expression of these detoxification mechanisms was sustained at higher RDX concentrations as well as production of a physical barrier to exposure through a 40% increase in mucocyte density at the maximum RDX exposure. At and above the 1.8 mg/L exposure concentration, DET coding for genes involved in central energy metabolism, including photosynthesis, glycolysis and electron-transport functions, were decreased in zooxanthellae although preliminary data indicated that zooxanthellae densities were not affected. In contrast, significantly increased transcript expression for genes involved in cellular energy production including glycolysis and electron-transport pathways was observed in the coral animal. CONCLUSIONS: Transcriptional network analysis for central energy metabolism demonstrated highly correlated responses to RDX among the coral animal and zooxanthellae indicative of potential compensatory responses to lost photosynthetic potential within the holobiont. These observations underscore the potential for complex integrated responses to RDX exposure among species comprising the coral holobiont and highlight the need to understand holobiont-species interactions to accurately assess pollutant impacts.

Using transcriptomic tools to evaluate biological effects across effluent gradients at a diverse set of study sites in Minnesota, USA.

The aim of this study was to explore the utility of "omics" approaches in monitoring aquatic environments where complex, often unknown stressors make chemical-specific risk assessment untenable. We examined changes in the fathead minnow (Pimephales promelas) ovarian transcriptome following 4-day exposures conducted at three sites in Minnesota (MN, USA). Within each site, fish were exposed to water from three locations along a spatial gradient relative to a wastewater treatment plant (WWTP) discharge. After exposure, site-specific impacts on gene expression in ovaries were assessed. Using an intragradient point of comparison, biological responses specifically associated with the WWTP effluent were identified using functional enrichment analyses. Fish exposed to water from locations downstream of the effluent discharges exhibited many transcriptomic responses in common with those exposed to the effluent, indicating that effects of the discharge do not fully dissipate downstream. Functional analyses showed a range of biological pathways impacted through effluent exposure at all three sites. Several of those impacted pathways at each site could be linked to potential adverse reproductive outcomes associated with the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows, specifically signaling pathways associated with oocyte meiosis, TGF-beta signaling, gonadotropin-releasing hormone (GnRH) and epidermal growth factor receptor family (ErbB), and gene sets associated with cyclin B-1 and metalloproteinase. The utility of this approach comes from the ability to identify biological responses to pollutant exposure, particularly those that can be tied to adverse outcomes at the population level and those that identify molecular targets for future studies.

Differential effects and potential adverse outcomes of ionic silver and silver nanoparticles in vivo and in vitro.

Nanoparticles are of concern because of widespread use, but it is unclear if metal nanoparticles cause effects directly or indirectly. We explored whether polyvinylpyrrolidone-coated silver nanoparticles (PVP-AgNPs) cause effects through intact nanoparticles or dissolved silver. Females of the model species fathead minnow (Pimephales promelas) were exposed to either 4.8 µg/L of AgNO3 or 61.4 µg/L of PVP-AgNPs for 96h. Microarray analyses were used to identify impacted receptors and toxicity pathways in liver and brain tissues that were confirmed using in vitro mammalian assays. AgNO3 and PVP-AgNP exposed fish had common and distinct effects consistent with both intact nanoparticles and dissolved silver causing effects. PVP-AgNPs and AgNO3 both affected pathways involved in Na(+), K(+), and H(+) homeostasis and oxidative stress but different neurotoxicity pathways. In vivo effects were supported by PVP-AgNP activation of five in vitro nuclear receptor assays and inhibition of ligand binding to the dopamine receptor. AgNO3 inhibited ligand binding to adrenergic receptors α1 and α2 and cannabinoid receptor CB1, but had no effect in nuclear receptor assays. PVP-AgNPs have the potential to cause effects both through intact nanoparticles and metal ions, each interacting with different initiating events. Since the in vitro and in vivo assays examined here are commonly used in human and ecological hazard screening, this work suggests that environmental health assessments should consider effects of intact nanoparticles in addition to dissolved metals.

Endocrinology: advances through omics and related technologies.

The rapid development of new omics technologies to measure changes at genetic, transcriptomic, proteomic, and metabolomics levels together with the evolution of methods to analyze and integrate the data at a systems level are revolutionizing the study of biological processes. Here we discuss how new approaches using omics technologies have expanded our knowledge especially in nontraditional models. Our increasing knowledge of these interactions and evolutionary pathway conservation facilitates the use of nontraditional species, both invertebrate and vertebrate, as new model species for biological and endocrinology research. The increasing availability of technology to create organisms overexpressing key genes in endocrine function allows manipulation of complex regulatory networks such as growth hormone (GH) in transgenic fish where disregulation of GH production to produce larger fish has also permitted exploration of the role that GH plays in testis development, suggesting that it does so through interactions with insulin-like growth factors. The availability of omics tools to monitor changes at nearly any level in any organism, manipulate gene expression and behavior, and integrate data across biological levels, provides novel opportunities to explore endocrine function across many species and understand the complex roles that key genes play in different aspects of the endocrine function.

Integrated approach to explore the mechanisms of aromatase inhibition and recovery in fathead minnows (Pimephales promelas).

Aromatase, a member of the cytochrome P450 superfamily, is a key enzyme in estradiol synthesis that catalyzes the aromatization of androgens into estrogens in ovaries. Here, we used an integrated approach to assess the mechanistic basis of the direct effects of aromatase inhibition, as well as adaptation and recovery processes in fish. We exposed female fathead minnows (Pimephales promelas) via the water to 30 µg/L of a model aromatase inhibitor, fadrozole, during 8 days (exposure phase). Fish were then held in clean water for 8 more days (recovery phase). Samples were collected at 1, 2, 4, and 8 days of both the exposure and the recovery phases. Transcriptomics, metabolomics, and network inference were used to understand changes and infer connections at the transcript and metabolite level in the ovary. Apical endpoints directly indicative of endocrine function, such as plasma estradiol, testosterone, and vitellogenin levels were also measured. An integrated analysis of the data revealed changes in gene expression consistent with increased testosterone in fadrozole-exposed ovaries. Metabolites such as glycogen and taurine were strongly correlated with increased testosterone levels. Comparison of in vivo and ex vivo steroidogenesis data suggested the accumulation of steroidogenic enzymes, including aromatase, as a mechanism to compensate for aromatase inhibition.