Toxicogenomic differentiation of functional responses to fipronil and imidacloprid in Daphnia magna

Active substances of pesticides, biocides or pharmaceuticals can induce adverse side effects in the aquatic ecosystem, necessitating environmental hazard and risk assessment prior to substance registration. The freshwater crustacean Daphnia magna is a model organism for acute and chronic toxicity assessment representing aquatic invertebrates. However, standardized tests involving daphnia are restricted to the endpoints immobility and reproduction and thus provide only limited insights into the underlying modes-of-action. Here, we applied transcriptome profiling to a modified D. magna Acute Immobilization test to analyze and compare gene expression profiles induced by the GABA-gated chloride channel blocker fipronil and the nicotinic acetylcholine receptor (nAChR) agonist imidacloprid. Daphnids were expose to two low effect concentrations of each substance followed by RNA sequencing and functional classification of affected gene ontologies and pathways. For both insecticides, we observed a concentration-dependent increase in the number of differentially expressed genes, whose expression changes were highly significantly positively correlated when comparing both test concentrations. These gene expression fingerprints showed virtually no overlap between the test substances and they related well to previous data of diazepam and carbaryl, two substances targeting similar molecular key events. While, based on our results, fipronil predominantly interfered with molecular functions involved in ATPasecoupled transmembrane transport and transcription regulation, imidacloprid primarily affected oxidase and oxidoreductase activity. These findings provide evidence that systems biology approaches can be utilized to identify and differentiate modes-of-action of chemical stressors in D. magna as an invertebrate aquatic non-target organism. The mechanistic knowledge extracted from such data will in future contribute to the development of Adverse Outcome Pathways (AOPs) for read-across and prediction of population effects.