Metabolic Effect Level Index Links Multivariate Metabolic Fingerprints to Ecotoxicological Effect Assessment

A major goal of ecotoxicology is the prediction of adverse outcomes for populations from sensitive and early physiological responses. A snapshot of the physiological state of an organism can be provided by metabolic fingerprints. However, to inform chemical risk assessment, multivariate metabolic fingerprints need to be converted to readable end points suitable for effect estimation and comparison. The concentration- and time-dependent responsiveness of metabolic fingerprints to the PS-II inhibitor isoproturon was investigated by use of a Myriophyllum spicatum bioassay. Hydrophilic and lipophilic leaf extracts were analyzed with gas chromatography mass spectrometry (GC-MS) and prepro cessed with XCMS. Metabolic changes were aggregated in the quantitative metabolic effect level index (MELT), allowing effect estimation from Hill-based concentration response models. Hereby, the most sensitive response on the concentration scale was revealed by the hydrophilic MELT, followed by photosynthetic efficiency and, 1 order of magnitude higher, by the lipophilic MELI and shoot length change. In the hydrophilic MELT, 50% change compares to 30% inhibition of photosynthetic efficiency and 10% inhibition of dry weight change, indicating effect development on different response levels. In conclusion, aggregated metabolic fingerprints provide quantitative estimates and span a broad response spectrum, potentially valuable for establishing adverse outcome pathways of chemicals in environmental risk assessment.