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Systems Toxicology Approach for Testing Chemical Cardiotoxicity in Larval Zebrafish

: Li, Roman; Zupanic, Anze; Talikka, Marja; Belcastro, Vincenzo; Madan, Sumit; Dörpinghaus, Jens; Berg, Colette vom; Szostak, Justyna; Martin, Florian; Peitsch, Manuel C.; Hoeng, Julia


Chemical research in toxicology 33 (2020), Nr.10, S.2550-2564
ISSN: 0893-228X (Print)
ISSN: 1520-5010 (Online)
Fraunhofer SCAI ()
peptides and proteins; genetics; layer; electron correlation; zebrafish

Transcriptomic approaches can give insight into molecular mechanisms underlying chemical toxicity and are increasingly being used as part of toxicological assessments. To aid the interpretation of transcriptomic data, we have developed a systems toxicology method that relies on a computable biological network model. We created the first network model describing cardiotoxicity in zebrafish larvaea valuable emerging model species in testing cardiotoxicity associated with drugs and chemicals. The network is based on scientific literature and represents hierarchical molecular pathways that lead from receptor activation to cardiac pathologies. To test the ability of our approach to detect cardiotoxic outcomes from transcriptomic data, we have selected three publicly available data sets that reported chemically induced heart pathologies in zebrafish larvae for five different chemicals. Network-based analysis detected cardiac perturbations for four out of five chemicals tested, for two of them using transcriptomic data collected up to 3 days before the onset of a visible phenotype. Additionally, we identified distinct molecular pathways that were activated by the different chemicals. The results demonstrate that the proposed integrational method can be used for evaluating the effects of chemicals on the zebrafish cardiac function and, together with observed cardiac apical end points, can provide a comprehensive method for connecting molecular events to organ toxicity. The computable network model is freely available and may be used to generate mechanistic hypotheses and quantifiable perturbation values from any zebrafish transcriptomic data.