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.