Identification and Characterization of Androgen-Responsive Genes in Zebrafish Embryos.

Responsive genes for fish embryos have been identified so far for some endocrine pathways but not for androgens. Using transcriptome analysis and multiple concentration-response modeling, we identified putative androgen-responsive genes in zebrafish embryos exposed to 0.05-5000 nM 11-ketotestosterone for 24 h. Four selected genes with sigmoidal concentration-dependent expression profiles (EC50 = 6.5-30.0 nM) were characterized in detail. The expression of cyp2k22 and slco1f4 was demonstrated in the pronephros; lipca was detected in the liver, and sult2st3 was found in the olfactory organs and choroid plexus. Their expression domains, the function of human orthologs, and a pathway analysis suggested a role of these genes in the metabolism of hormones. Hence, it was hypothesized that they were induced to compensate for elevated hormone levels. The induction of sult2st3 and cyp2k22 by 11-ketotestosterone was repressed by co-exposure to the androgen receptor antagonist nilutamide supporting a potential androgen receptor mediated regulation. Sensitivity (expressed as EC50 values) of sult2st3 and cyp2k22 gene expression induction after exposure to other steroidal hormones (11-ketotestosterone ∼ testosterone > progesterone > cortisol > ethinylestradiol) correlated with their known binding affinities to zebrafish androgen receptor. Hence, these genes might represent potential markers for screening of androgenic compounds in the zebrafish embryo.

A data-derived reference mixture representative of European wastewater treatment plant effluents to complement mixture assessment.

Aquatic environments are polluted with a multitude of organic micropollutants, which challenges risk assessment due the complexity and diversity of pollutant mixtures. The recognition that certain source-specific background pollution occurs ubiquitously in the aquatic environment might be one way forward to approach mixture risk assessment. To investigate this hypothesis, we prepared one typical and representative WWTP effluent mixture of organic micropollutants (EWERBmix) comprised of 81 compounds selected according to their high frequency of occurrence and toxic potential. Toxicological relevant effects of this reference mixture were measured in eight organism- and cell-based bioassays and compared with predicted mixture effects, which were calculated based on effect data of single chemicals retrieved from literature or different databases, and via quantitative structure-activity relationships (QSARs). The results show that the EWERBmix supports the identification of substances which should be considered in future monitoring efforts. It provides measures to estimate wastewater background concentrations in rivers under consideration of respective dilution factors, and to assess the extent of mixture risks to be expected from European WWTP effluents. The EWERBmix presents a reasonable proxy for regulatory authorities to develop and implement assessment approaches and regulatory measures to address mixture risks. The highlighted data gaps should be considered for prioritization of effect testing of most prevalent and relevant individual organic micropollutants of WWTP effluent background pollution. The here provided approach and EWERBmix are available for authorities and scientists for further investigations. The approach presented can furthermore serve as a roadmap guiding the development of archetypic background mixtures for other sources, geographical settings and chemical compounds, e.g. inorganic pollutants.

Towards a qAOP framework for predictive toxicology - Linking data to decisions.

The adverse outcome pathway (AOP) is a conceptual construct that facilitates organisation and interpretation of mechanistic data representing multiple biological levels and deriving from a range of methodological approaches including in silico, in vitro and in vivo assays. AOPs are playing an increasingly important role in the chemical safety assessment paradigm and quantification of AOPs is an important step towards a more reliable prediction of chemically induced adverse effects. Modelling methodologies require the identification, extraction and use of reliable data and information to support the inclusion of quantitative considerations in AOP development. An extensive and growing range of digital resources are available to support the modelling of quantitative AOPs, providing a wide range of information, but also requiring guidance for their practical application. A framework for qAOP development is proposed based on feedback from a group of experts and three qAOP case studies. The proposed framework provides a harmonised approach for both regulators and scientists working in this area.

A Self-Organizing Map of the Fathead Minnow Liver Transcriptome to Identify Consistent Toxicogenomic Patterns across Chemical Fingerprints.

Lack of consistent findings in different experimental settings remains a major challenge in toxicogenomics. The present study investigated whether consistency between findings of different microarray experiments can be improved when the analysis is based on a common reference frame ("toxicogenomic universe"), which can be generated using the machine learning algorithm of the self-organizing map (SOM). This algorithm arranges and clusters genes on a 2-dimensional grid according to their similarity in expression across all considered data. In the present study, 19 data sets, comprising of 54 different adult fathead minnow liver exposure experiments, were retrieved from Gene Expression Omnibus and used to train a SOM. The resulting toxicogenomic universe aggregates 58 872 probes to 2500 nodes and was used to project, visualize, and compare the fingerprints of these 54 different experiments. For example, we could identify a common pattern, with 14% of significantly regulated nodes in common, in the data sets of an interlaboratory study of ethinylestradiol exposures. Consistency could be improved compared with the 5% total overlap in regulated genes reported before. Furthermore, we could determine a specific and consistent estrogen-related pattern of differentially expressed nodes and clusters in the toxicogenomic universe by applying additional clustering steps and comparing all obtained fingerprints. Our study shows that the SOM-based approach is useful for generating comparable toxicogenomic fingerprints and improving consistency between results of different experiments. Environ Toxicol Chem 2020;39:526-537. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Map and model-moving from observation to prediction in toxicogenomics.

BACKGROUND: Chemicals induce compound-specific changes in the transcriptome of an organism (toxicogenomic fingerprints). This provides potential insights about the cellular or physiological responses to chemical exposure and adverse effects, which is needed in assessment of chemical-related hazards or environmental health. In this regard, comparison or connection of different experiments becomes important when interpreting toxicogenomic experiments. Owing to lack of capturing response dynamics, comparability is often limited. In this study, we aim to overcome these constraints. RESULTS: We developed an experimental design and bioinformatic analysis strategy to infer time- and concentration-resolved toxicogenomic fingerprints. We projected the fingerprints to a universal coordinate system (toxicogenomic universe) based on a self-organizing map of toxicogenomic data retrieved from public databases. Genes clustering together in regions of the map indicate functional relation due to co-expression under chemical exposure. To allow for quantitative description and extrapolation of the gene expression responses we developed a time- and concentration-dependent regression model. We applied the analysis strategy in a microarray case study exposing zebrafish embryos to 3 selected model compounds including 2 cyclooxygenase inhibitors. After identification of key responses in the transcriptome we could compare and characterize their association to developmental, toxicokinetic, and toxicodynamic processes using the parameter estimates for affected gene clusters. Furthermore, we discuss an association of toxicogenomic effects with measured internal concentrations. CONCLUSIONS: The design and analysis pipeline described here could serve as a blueprint for creating comparable toxicogenomic fingerprints of chemicals. It integrates, aggregates, and models time- and concentration-resolved toxicogenomic data.

The Transcriptome of the Zebrafish Embryo After Chemical Exposure: A Meta-Analysis.

Numerous studies have been published in the past years investigating the transcriptome of the zebrafish embryo (ZFE) upon being subjected to chemical stress. Aiming at a more mechanistic understanding of the results of such studies, knowledge about commonalities of transcript regulation in response to chemical stress is needed. Thus, our goal in this study was to identify and interpret genes and gene sets constituting a general response to chemical exposure. Therefore, we aggregated and reanalyzed published toxicogenomics data obtained with the ZFE. We found that overlap of differentially transcribed genes in response to chemical stress across independent studies is generally low and the most commonly differentially transcribed genes appear in less than 50% of all treatments across studies. However, effect size analysis revealed several genes showing a common trend of differential expression, among which genes related to calcium homeostasis emerged as key, especially in exposure settings up to 24 h post-fertilization. Additionally, we found that these and other downregulated genes are often linked to anatomical regions developing during the respective exposure period. Genes showing a trend of increased expression were, among others, linked to signaling pathways (e.g., Wnt, Fgf) as well as lysosomal structures and apoptosis. The findings of this study help to increase the understanding of chemical stress responses in the developing zebrafish embryo and provide a starting point to improve experimental designs for this model system. In future, improved time- and concentration-resolved experiments should offer better understanding of stress response patterns and access to mechanistic information.