Abteilung Umwelttoxikologie

Zebrafish (Danio rerio) early life stages offer a versatile model system to study the efficacy and safety of drugs or other chemicals with regard to human and environmental health. This is because, aside from the well-characterized genome of zebrafish and the availability of a broad range of experimental and computational research tools, they are exceptionally well suited for high-throughput approaches. Yet, one important pharmacokinetic aspect is thus far only poorly understood in zebrafish embryo and early larvae: their biotransformation capacity. Especially biotransformation of electrophilic compounds is a critical pathway because they easily react with nucleophile molecules, such as DNA or proteins, potentially inducing adverse health effects. To combat such adverse effects, conjugation reactions with glutathione and further processing within the mercapturic acid pathway have evolved. We here explore the functionality of this pathway in zebrafish early life stages using a reference substrate (1-chloro-2,4-dinitrobenzene, CDNB).

With this work we show that zebrafish embryos can biotransform CDNB to the respective glutathione conjugate as early as 4 hours post fertilization. At all examined life stages, the glutathione conjugate is further biotransformed to the last metabolite of the mercapturic acid pathway, the mercapturate, which is slowly excreted.

Being able to biotransform electrophiles within the mercapturic acid pathway shows that zebrafish early life stages possess the potential to process xenobiotic compounds through glutathione conjugation and the formation of mercapturates. The presence of this chemical biotransformation and clearance route in zebrafish early life stages supports the application of this model in toxicology and chemical hazard assessment.

1-Chloro-2,4-dinitrobenzene (CDNB) is widely used as a model substrate for measuring enzyme activity of glutathione S-transferases in toxicity studies and in studies focusing on the metabol-ic capacity of different test systems. To allow the quantification of CDNB at low, non-toxic concentra-tions, we developed a sensitive liquid chromatography-mass spectrometry (LC-MS) technique, which is based on electron capture ionization using atmospheric pressure chemical ionization (APCI) in negative ion mode. Gas phase reactions occurring under atmospheric pressure produce specific ions that allow direct CDNB quantification down to 17 ng/ml in water. Using the new technique, we were able to verify CDNB exposure concentrations applied in two typical toxicity studies with early life stages of the com-mon model organisms, zebrafish (Danio rerio) and a zebrafish embryonic cell line (Pac2).

Environmental risk assessment associated with aquatic and terrestrial contamination is mostly based on predicted or measured environmental concentrations of a limited list of chemicals in a restricted number of environmental compartments. High resolution mass spectrometry (HRMS) can provide a more comprehensive picture of exposure to harmful chemicals, particularly through the retrospective analysis of digitally stored HRMS data. Using this methodology, our study characterized the contamination of various environmental compartments including 154 surface water, 46 urban effluent, 67 sediment, 15 soil, 34 groundwater, 24 biofilm, 41 gammarid and 49 fish samples at 95 sites widely distributed over the Swiss Plateau. As a proof-of-concept, we focused our investigation on antifungal azoles, a class of chemicals of emerging concern due to their endocrine disrupting effects on aquatic organisms and humans. Our results demonstrated the occurrence of antifungal azoles and some of their (bio)transformation products in all the analyzed compartments (0.1-100 ng/L or ng/g d.w.). Comparison of actual and predicted concentrations showed the partial suitability of level 1 fugacity modelling in predicting the exposure to azoles. Risk quotient calculations additionally revealed risk of exposure especially if some of the investigated rivers and streams are used for drinking water production. The case study clearly shows that the retrospective analysis of HRMS/MS data can improve the current knowledge on exposure and the related risks to chemicals of emerging concern and can be effectively employed in the future for such purposes.

Adverse outcome pathway Bayesian networks (AOPBNs) are a promising avenue for developing predictive toxicology and risk assessment tools based on adverse outcome pathways (AOPs). Here, we describe a process for developing AOPBNs. AOPBNs use causal networks and Bayesian statistics to integrate evidence across key events. In this article, we use our AOPBN to predict the occurrence of steatosis under different chemical exposures. Since it is an expert‐driven model, we use external data (i.e., data not used for modeling) from the literature to validate predictions of the AOPBN model. The AOPBN accurately predicts steatosis for the chemicals from our external data. In addition, we demonstrate how end users can utilize the model to simulate the confidence (based on posterior probability) associated with predicting steatosis. We demonstrate how the network topology impacts predictions across the AOPBN, and how the AOPBN helps us identify the most informative key events that should be monitored for predicting steatosis. We close with a discussion of how the model can be used to predict potential effects of mixtures and how to model susceptible populations (e.g., where a mutation or stressor may change the conditional probability tables in the AOPBN). Using this approach for developing expert AOPBNs will facilitate the prediction of chemical toxicity, facilitate the identification of assay batteries, and greatly improve chemical hazard screening strategies.