Abstract
In environmental risk assessment of substances, the 14-day growth inhibition test following OECD test guideline 239 is employed to assess toxicity in the macrophyte Myriophyllum spicatum. Currently, this test evaluates physiological parameters and does not allow the identification of the mode of action (MoA) by which adverse effects are induced. However, for an improved ecotoxicity assessment of substances, knowledge about their ecotoxic MoA in non-target organisms is required. It has previously been suggested that the identification of gene expression changes can contribute to MoA identification. Therefore, we developed a shortened three-day assay for M. spicatum including the transcriptomic assessment of global gene expression changes and applied this assay to two model substances, the herbicide and photosynthesis inhibitor bentazone and the pharmaceutical and HMG-CoA reductase inhibitor atorvastatin. Due to the lack of a reference genome for M. spicatum we performed a de novo transcriptome assembly followed by a functional annotation to use the toxicogenomic results for MoA discrimination. The gene expression changes induced by low effect concentrations of these substances were used to identify differentially expressed genes (DEGs) and impaired biological functions for the respective MoA. We observed both concentration-dependent numbers and differentiated patterns of DEGs for both substances. While bentazone impaired genes involved in the response to reactive oxygen species as well as light response, and also genes involved in developmental processes, atorvastatin exposure led to a differential regulation of genes related to brassinosteroid response as well as potential metabolic shifts between the mevalonate and methyl erythritol 4-phosphate pathway. Based on these responses, we identified biomarker candidates for the assessment of MoA in M. spicatum. Utilizing the shortened assay developed in this study, the investigation of the identified biomarker candidates may contribute to the development of future MoA-specific screening approaches in the ecotoxicological hazard prediction using aquatic non-standard model organisms.
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