First, the DRomics tool was developed in order to manage molecular responses obtained in a dose-response framework. As the microERA project necessitates dealing with this kind of data, we needed a reliable procedure able to manage the data obtained during the experiment. This tool 1/ detects responding data (e.g. genes, metabolites), 2/ finds out the best model to describe the response, 3/ builds dose-response curves even in the case of complex responses (e.g. biphasic), 4/ derives an effect concentration (here, benchmark dose) and 5/ builds a cumulative distribution of gene or metabolite sensitivity.
Second, in a proof-of principle study, the functionality of the tool was demonstrated for an existing dataset, describing the response of the chlorophyte Scenedesmus vacuolatus to the biocide triclosan (6 concentrations including control). Responses were observed at the molecular level (untargeted transcriptomics (microarrays) and metabolomics) and apical/classical endpoints (growth, photosynthesis). This step allowed to first reach our goals on a model organism with a lower biological complexity compared to communities and to identify potential limitations to be solved for consecutive experiments on periphytic communities. Using DRomics, we observed that apical endpoints were less sensitive than most of molecular endpoints and that the well-known sigmoid response was more the exception than the rule at the molecular level. An ESD was built on both transcriptomics and metabolomics responses and clearly highlighted importance of the consideration of omics responses in ERA and reinforced our initial assumptions.
Third, an experiment was performed to investigate the responses of stream periphytic communities to the herbicide diuron on different functional levels. Responses at the molecular level (transcriptomics=sequencing of RNA, metabolomics) were investigated after 1 hour of exposure. Moreover, the same experiment was performed in parallel on communities pre-exposed for one month to diuron in order to investigate potential tolerance acquisition mechanisms on functional responses. A strong effort was also put in the optimization of a protocol to extract RNA in a sufficient quality and quantity for the downstream analysis. Quality control of the extraction and the sequencing of RNA were satisfying. The annotation of the sequencing is still in treatment. An ESD build on community functional responses in the light of metabolic pathways annotation (e.g. KEGG pathways) is under development considering tolerance mechanisms.
