NUCKS1 promotes the progression of colorectal cancer via activating PI3K/AKT/mTOR signaling pathway.

Nuclear ubiquitous casein and cyclin-dependent kinase substrate 1 (NUCKS1) is highly expressed in a variety of malignant tumors and functions as an oncogene; however, its role in colorectal cancer (CRC) remains unclear. We aimed to explore the function and regulatory mechanisms of NUCKS1 and potential therapeutic agents targeting NUCKS1 in CRC. We knocked down and overexpressed NUCKS1 in CRC cells and explored its effects in vitro and in vivo. Flow cytometry, CCK-8, Western blotting, colony formation, immunohistochemistry, in vivo tumorigenic, and transmission electron microscopy analyses were performed to determine the effects of NUCKS1 on CRC cell function. LY294002 was used to examine the mechanism of NUCKS1 expression in CRC cells. Potential therapeutic agents for NUCKS1-high CRC patients were analyzed using the CTRP and PRISM datasets, and the function of selected agents was determined by CCK-8 and Western blotting. We revealed that NUCKS1 was highly expressed in CRC tissues and clinically correlated with poor prognosis in CRC patients. NUCKS1 knockdown induces cell cycle arrest, inhibits CRC cell proliferation, and promotes apoptosis and autophagy. These results were reversed when NUCKS1 was overexpressed. Mechanistically, NUCKS1 exerts a cancer-promoting function by activating the PI3K/AKT/mTOR signaling pathway. This was reversed when LY294002 was used to inhibit the PI3K/AKT pathway. Furthermore, we determined that mitoxantrone exhibited high drug sensitivity in NUCKS1-overexpressing CRC cells. This work demonstrated NUCKS1 plays a crucial role in CRC progression via the PI3K/AKT/mTOR signaling pathway. Additionally, mitoxantrone may be a potential therapeutic agent for CRC treatment. Therefore, NUCKS1 represents a promising anti-tumor therapeutic target.

Semantic characterization of adverse outcome pathways.

This study was undertaken to systematically assess the utilities and performance of ontology-based semantic analysis in adverse outcome pathway (AOP) research. With an increasing number of AOPs developed by scientific domain experts to organize toxicity information and facilitate chemical risk assessment, there is a pressing need for objective approaches to evaluate the biological coherence and quality of these AOPs. Powered by ontologies covering a wide range of biological domains, abundant phenotypic data annotated ontologically, and some sophisticated knowledge computing tools, semantic analysis has great potential in this area of application. With the events in the AOP-Wiki first annotated into logical definitions and then grouped into phenotypic profiles by individual AOPs, the coherence and quality of AOPs were assessed at several levels: paired key event relationships (KER), all possible event pair combinations within AOPs, and the phenotypic profiles of AOPs, genes, biological pathways, human diseases, and selected chemicals. The semantic similarities were assessed at all these levels based on a unified cross-species vertebrate phenotype ontology encompassing the logical definitions of AOP events as well as many other domain ontologies. A substantial number of KERs and AOPs in the AOP-Wiki were found to be semantically coherent. These same coherent AOPs also mapped to many more genes, pathways, and diseases biologically aligned with the intended chain of events therein leading to their respective adverse outcomes. Significantly, these findings imply that semantic analysis should also have utilities in developing future AOPs by selecting candidate events from either the existing AOP-Wiki events or a broader collection of ontology terms semantically similar to the molecular initiating events or adverse outcomes of interest. In addition, semantic analysis enabled AOP networks to be constructed at the level of phenotypic profiles based on similarities, complementing those based on event sharing by bringing genes, pathways, diseases, and chemicals into the networks too-thus greatly expanding the biological scope and our understanding of AOPs.

Ontology-based semantic mapping of chemical toxicities.

This study was undertaken to evaluate the use of ontology-based semantic mapping (OS-Mapping) in chemical toxicity assessment. Nineteen chemical-species phenotypic profiles (CSPPs) were constructed by ontologically annotating the toxicity responses reported in more than seven hundred published studies of ten chemicals on six vertebrate species. The CSPPs were semantically compared to more than 29,000 publicly available phenotypic profiles of genes, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, and diseases based on a cross-species phenotype ontology. OS-Mapping was shown to differentiate chemical toxicities among themselves as well as within and across species. It also revealed cases of chemical by species interactions. In addition to confirming similar MOAs (mechanisms of action) for a few chemicals, OS-Mapping also generated novel insights into the MOAs underlying some seemingly different, yet phenotypically similar, classes of chemicals. The nature of a unified cross-species phenotype ontology and its representation of diverse knowledge domains allowed the construction of a complete phenotypic continuum for the 17α-ethynylestradiol_fathead minnow across the biological levels of organization, which complemented a similar one derived from the Comparative Toxicogenomics Database but based primarily on 17α-ethynylestradiol-induced molecular phenotypes. Overall, OS-Mapping has been demonstrated to offer a powerful approach to help bridge the gap between the molecular and non-molecular phenotypes of chemicals characterized by using high throughput or traditional omics methods and their apical endpoints of greater regulatory relevance, which are typically phenotypes found at the higher levels of biological organization. OS-Mapping also enables comparative toxicity assessment among chemicals, both within and across species. Furthermore, the semantic analysis of phenotypes can reveal additional novel MOAs for some well-known chemicals and discover candidate MOAs for chemicals that are less molecularly characterized. A full phenotypic continuum based on OS-Mapping will also be conducive to the future development of adverse outcome pathways. As phenomics continues to advance and the ontological annotation of literature becomes more automated, the power of OS-Mapping will be further enhanced.

Social hierarchy modulates responses of fish exposed to contaminants of emerging concern.

Many organisms, including the fathead minnow (Pimephales promelas), a toxicological model organism, establish social hierarchies. The social rank of each male in a population is under the control of the hypothalamic-pituitary-gonadal (HPG) axis mainly through regulation of circulating androgen concentrations, which in turn drive the expression of secondary sex characteristics (SSCs). As dominant and subordinate males in an exposure study are initially under different physiological conditions (i.e., differing plasma androgen concentrations), we proposed that they belong to different subpopulations in the context of exposure to compounds that may interact with the HPG axis. Using a meta-analysis of our data from several previously published studies, we corroborated the hypothesis that social status, as indicated by SSCs, results in distinct clusters (eigenvalues >0.8 explaining >80% of variability) with differential expression of plasma vitellogenin, a commonly used biomarker of exposure to contaminants of emerging concern (CEC). Furthermore, we confirmed our predictions that exposure to estrogenic CECs would homogenize plasma vitellogenin response (E1: cluster mean SSC values decreased to 4.33 and 4.86 relative to those of control; E2: decreased to 4.8 and 5.37) across the social hierarchy. In contrast, serotonin-specific reuptake inhibitors expand this response range (cluster mean SSC increased to 5.21 and 6.5 relative to those of control). Our results demonstrated that social hierarchies in male fathead minnows result in heterogeneous responses to chemical exposure. These results represent a cautionary note for the experimental design of single-sex exposure studies. We anticipate our study to be a starting point for the re-evaluation of toxicological data analyses in single sex exposure experiments.

How consistent are we? Interlaboratory comparison study in fathead minnows using the model estrogen 17α-ethinylestradiol to develop recommendations for environmental transcriptomics.

Fundamental questions remain about the application of omics in environmental risk assessments, such as the consistency of data across laboratories. The objective of the present study was to determine the congruence of transcript data across 6 independent laboratories. Male fathead minnows were exposed to a measured concentration of 15.8 ng/L 17α-ethinylestradiol (EE2) for 96 h. Livers were divided equally and sent to the participating laboratories for transcriptomic analysis using the same fathead minnow microarray. Each laboratory was free to apply bioinformatics pipelines of its choice. There were 12 491 transcripts that were identified by one or more of the laboratories as responsive to EE2. Of these, 587 transcripts (4.7%) were detected by all laboratories. Mean overlap for differentially expressed genes among laboratories was approximately 50%, which improved to approximately 59.0% using a standardized analysis pipeline. The dynamic range of fold change estimates was variable between laboratories, but ranking transcripts by their relative fold difference resulted in a positive relationship for comparisons between any 2 laboratories (mean R2 > 0.9, p < 0.001). Ten estrogen-responsive genes encompassing a fold change range from dramatic (>20-fold; e.g., vitellogenin) to subtle (∼2-fold; i.e., block of proliferation 1) were identified as differentially expressed, suggesting that laboratories can consistently identify transcripts that are known a priori to be perturbed by a chemical stressor. Thus, attention should turn toward identifying core transcriptional networks using focused arrays for specific chemicals. In addition, agreed-on bioinformatics pipelines and the ranking of genes based on fold change (as opposed to p value) should be considered in environmental risk assessment. These recommendations are expected to improve comparisons across laboratories and advance the use of omics in regulations. Environ Toxicol Chem 2017;36:2593-2601. © 2017 SETAC.

Creating a Structured AOP Knowledgebase via Ontology-Based Annotations.

INTRODUCTION: The Adverse Outcome Pathway framework is increasingly used to integrate data generated based on traditional and emerging toxicity testing paradigms. As the number of AOP descriptions has increased, so has the need to define the AOP in computable terms. MATERIALS AND METHODS: Herein, we present a comprehensive annotation of 172 AOPs housed in the AOP-Wiki as of December 4, 2016 using terms from existing biological ontologies. RESULTS: AOP Key Events (KEs) were assigned ontology terms using a concept called the Event Component, which consists of a Process, an Object, and an Action term, with each term originating from ontologies and other controlled vocabularies. Annotation of KEs with ontology classes from fourteen ontologies and controlled vocabularies resulted in a total of 685 KEs being annotated with a total of 809 Event Components. A set of seven conventions resulted, defining the annotation of KEs via Event Components. DISCUSSION: This expanded annotation of AOPs allows computational reasoners to aid in both AOP development and applications. In addition, the incorporation of explicit biological objects will reduce the time required for converting a qualitative AOP description into a conceptual model that can support computational modeling. As high throughput genomics becomes a more important part of the high throughput toxicity testing landscape, the new approaches described here for annotating key events will also promote the visualization and analysis of genomics data in an AOP context.

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.

Investigation of treatment methods in obstructive colorectal cancer.

PURPOSE: The aim of this study was to explore the treatment strategies for patients with obstructive colorectal cancer at different sites. METHODS: Treatment strategies were adopted according to the location of colorectal cancer and the condition of the patients when they were admitted to the hospital. Among a total of 134 patients, 29 patients were subjected to stent placement to relieve the obstruction before undergoing colorectal resection, 15 patients underwent per anum ileus catheterization to alleviate the symptoms of obstruction and waited for removal of the tumor within a limited time; 39 underwent intraoperative colonic lavage and colon resection with anastomosis and the remaining 51 patients were subjected to emergency surgery due to strangulation of the bowel, perforation, septic shock or other conditions before surgery. RESULTS: Stent placement was successfully performed on 23 patients, with a success rate of 79%. Ninety-five of 134 patients (71% had stage I anastomosis and only one case had anastomotic fistula. Infection of incision happened in 9 (7%) cases and 2 (1.5%) patients died of infection. CONCLUSIONS: Individualized treatment for patients with obstructive colorectal cancer can lead to tumor resection and stage I anastomosis, thereby avoiding the suffering of second-stage surgery or colostomy.

Systematic Omics Analysis Review (SOAR) tool to support risk assessment.

Environmental health risk assessors are challenged to understand and incorporate new data streams as the field of toxicology continues to adopt new molecular and systems biology technologies. Systematic screening reviews can help risk assessors and assessment teams determine which studies to consider for inclusion in a human health assessment. A tool for systematic reviews should be standardized and transparent in order to consistently determine which studies meet minimum quality criteria prior to performing in-depth analyses of the data. The Systematic Omics Analysis Review (SOAR) tool is focused on assisting risk assessment support teams in performing systematic reviews of transcriptomic studies. SOAR is a spreadsheet tool of 35 objective questions developed by domain experts, focused on transcriptomic microarray studies, and including four main topics: test system, test substance, experimental design, and microarray data. The tool will be used as a guide to identify studies that meet basic published quality criteria, such as those defined by the Minimum Information About a Microarray Experiment standard and the Toxicological Data Reliability Assessment Tool. Seven scientists were recruited to test the tool by using it to independently rate 15 published manuscripts that study chemical exposures with microarrays. Using their feedback, questions were weighted based on importance of the information and a suitability cutoff was set for each of the four topic sections. The final validation resulted in 100% agreement between the users on four separate manuscripts, showing that the SOAR tool may be used to facilitate the standardized and transparent screening of microarray literature for environmental human health risk assessment.

Natural Variation in Fish Transcriptomes: Comparative Analysis of the Fathead Minnow (Pimephales promelas) and Zebrafish (Danio rerio).

Fathead minnow and zebrafish are among the most intensively studied fish species in environmental toxicogenomics. To aid the assessment and interpretation of subtle transcriptomic effects from treatment conditions of interest, better characterization and understanding are needed for natural variation in gene expression among fish individuals from lab cultures. Leveraging the transcriptomics data from a number of our toxicogenomics studies conducted over the years, we conducted a meta-analysis of nearly 600 microarrays generated from the ovary tissue of untreated, reproductively mature fathead minnow and zebrafish samples. As expected, there was considerable batch-to-batch transcriptomic variation; this "batch-effect" appeared to differentially impact subsets of fish transcriptomes in a nonsystematic way. Temporally more closely spaced batches tended to share a greater transcriptomic similarity among one another. The overall level of within-batch variation was quite low in fish ovary tissue, making it a suitable system for studying chemical stressors with subtle biological effects. The observed differences in the within-batch variability of gene expression, at the levels of both individual genes and pathways, were probably both technical and biological. This suggests that biological interpretation and prioritization of genes and pathways targeted by experimental conditions should take into account both their intrinsic variability and the size of induced transcriptional changes. There was significant conservation of both the genomes and transcriptomes between fathead minnow and zebrafish. The high degree of conservation offers promising opportunities in not only studying fish molecular responses to environmental stressors by a comparative biology approach, but also effective sharing of a large amount of existing public transcriptomics data for developing toxicogenomics applications.

Anterior tibial artery perforator flap for reconstruction of intraoral defects.

PURPOSE: The present clinical study assessed the feasibility of using an anterior tibial artery perforator (ATAP) flap for the reconstruction of an intraoral defect after ablative surgery for oral cancer. PATIENTS AND METHODS: A cohort of consecutive patients with oral cancer requiring reconstruction of an intraoral defect using an ATAP flap were enrolled after ablative surgery for oral cancer and ipsilateral neck dissection. RESULTS: Twelve patients had primary oral squamous cell carcinoma (8 with tongue cancer and 4 with buccal cancer). All patients received intraoral defect repair using an ATAP flap from the lower left leg. The flap measured 7 × 4 to 8 × 6 cm(2). Flap thickness was approximately 4.8 mm (3 to 6 mm). Anastomosis of all ATAP flaps was straightforward because of the long and high-caliber vessel pedicle. All flaps survived and yielded excellent esthetic results for intraoral reconstruction. No major complications occurred in any patient. CONCLUSION: The main advantages of the ATAP flap included the thin and pliable tissue characteristics and a long and high-caliber pedicle. For small and medium-size intraoral defects, the ATAP flap is a reliable alternative to the radial forearm free flap.

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.

Altered gene expression in the brain and ovaries of zebrafish (Danio rerio) exposed to the aromatase inhibitor fadrozole: microarray analysis and hypothesis generation.

As part of a research effort examining system-wide responses of the hypothalamic-pituitary-gonadal (HPG) axis in fish to endocrine-active chemicals (EACs) with different modes of action, zebrafish (Danio rerio) were exposed to 25 or 100 microg/L of the aromatase inhibitor fadrozole for 24, 48, or 96 h. Global transcriptional response in brain and ovarian tissue of fish exposed to 25 microg/L of fadrozole was compared to that in control fish using a commercially available, 22,000-gene oligonucleotide microarray. Transcripts altered in brain were functionally linked to differentiation, development, DNA replication, and cell cycle. Additionally, multiple genes associated with the one-carbon pool by folate pathway (KEGG 00670) were significantly up-regulated. Transcripts altered in ovary were functionally linked to cell-cell adhesion, extracellular matrix, vasculogenesis, and development. Promoter motif analysis identified GATA-binding factor 2, Ikaros 2, alcohol dehydrogenase gene regulator 1, myoblast-determining factor, and several heat shock factors as being associated with coexpressed gene clusters that were differentially expressed following exposure to fadrozole. Based on the transcriptional changes observed, it was hypothesized that fadrozole elicits neurodegenerative stress in brain tissue and that fish cope with this stress through proliferation of radial glial cells. Additionally, it was hypothesized that changes of gene expression in the ovary of fadrozole-exposed zebrafish reflect disruption of oocyte maturation and ovulation because of impaired vitellogenesis. These hypotheses and others derived from the microarray results provide a foundation for future studies aimed at understanding responses of the HPG axis to EACs and other chemical stressors.

Endocrine disrupting chemicals in fish: developing exposure indicators and predictive models of effects based on mechanism of action.

Knowledge of possible toxic mechanisms (or modes) of action (MOA) of chemicals can provide valuable insights as to appropriate methods for assessing exposure and effects, thereby reducing uncertainties related to extrapolation across species, endpoints and chemical structure. However, MOA-based testing seldom has been used for assessing the ecological risk of chemicals. This is in part because past regulatory mandates have focused more on adverse effects of chemicals (reductions in survival, growth or reproduction) than the pathways through which these effects are elicited. A recent departure from this involves endocrine-disrupting chemicals (EDCs), where there is a need to understand both MOA and adverse outcomes. To achieve this understanding, advances in predictive approaches are required whereby mechanistic changes caused by chemicals at the molecular level can be translated into apical responses meaningful to ecological risk assessment. In this paper we provide an overview and illustrative results from a large, integrated project that assesses the effects of EDCs on two small fish models, the fathead minnow (Pimephales promelas) and zebrafish (Danio rerio). For this work a systems-based approach is being used to delineate toxicity pathways for 12 model EDCs with different known or hypothesized toxic MOA. The studies employ a combination of state-of-the-art genomic (transcriptomic, proteomic, metabolomic), bioinformatic and modeling approaches, in conjunction with whole animal testing, to develop response linkages across biological levels of organization. This understanding forms the basis for predictive approaches for species, endpoint and chemical extrapolation. Although our project is focused specifically on EDCs in fish, we believe that the basic conceptual approach has utility for systematically assessing exposure and effects of chemicals with other MOA across a variety of biological systems.

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.