Project description:Monitoring microbial communities can aid in understanding the state of these habitats. Environmental DNA (eDNA) techniques provide efficient and comprehensive monitoring by capturing broader diversity. Besides structural profiling, eDNA methods allow the study of functional profiles, encompassing the genes within the microbial community. In this study, three methodologies were compared for functional profiling of microbial communities in estuarine and coastal sites in the Bay of Biscay. The methodologies included inference from 16S metabarcoding data using Tax4Fun, GeoChip microarrays, and shotgun metagenomics.
Project description:Many biomonitoring tools/approaches have been proposed to assess presence of endocrine active chemicals (EACs) and their biological effects in the field. Although these tools have provided valuable information, they are often limited by their specificity for certain groups of EACs and they may not account for interactions between EACs. This study aims to evaluate utility of transcriptomic and metabolomic technologies for effects monitoring in the field, and to advance integration of omic and environmental chemistry data sets. The objective was to utilize transcriptomic biomonitoring to determine the relative contribution of wastewater treatment plant effluents to biological effects observed in fish exposed to ambient waters receiving the effluents. Adult male fathead minnow were exposed to treated wastewater effluent or stream water up or downstream the plant in three different watersheds for 4 days. After exposure, the liver of 5-7 fish per treatment per site (i.e 19-21 fish from each watershed) were analyzed by microarrays. The transcriptomic profiles were compared to control fish exposed to Lake Superior filtered water.
Project description:Many biomonitoring tools/approaches have been proposed to assess presence of endocrine active chemicals (EACs) and their biological effects in the field. Although these tools have provided valuable information, they are often limited by their specificity for certain groups of EACs and they may not account for interactions between EACs. This study aims to evaluate utility of transcriptomic and metabolomic technologies for effects monitoring in the field, and to advance integration of omic and environmental chemistry data sets. The objective was to utilize transcriptomic biomonitoring to determine the relative contribution of wastewater treatment plant effluents to biological effects observed in fish exposed to ambient waters receiving the effluents.
