Aquatic Bacterial Community Responses to Aquatic Contaminants Revealed by 16S rRNA Metabarcoding in Field-Based Microcosms.

Abstract

In this study we used environmental DNA metabarcoding and field-based microcosms to assess three classes of aquatic contaminants (metals (copper), pesticides (diuron), and pharmaceuticals (venlafaxine)) and their impact on the structure of freshwater wetland sedimentary bacterial communities. Our results showed that copper had the most influence on bacterial community structure, followed by venlafaxine, then diuron. We also saw that the addition of copper facilitated the release of other sediment-bound metals (barium, zinc, and vanadium), also having significant impacts on community structure. The bacterial communities were mostly dominated by Proteobacteria, Cyanobacteria, Bacteroidota, and Verrucomicrobiota, which were key drivers of variation among treatments, along with Actinobacteriota. Our findings indicate that the ideal taxonomic level for the assessment and identification of bacterial bioindicators is family, with constraints at lower taxonomic levels. We identified five phyla, 13 families, and three species which show strong potential to be either diagnostic bioindicators of one or more of the chemicals assessed or broad bioindicators of common urban contaminants, eight of which are novel bioindicators. Our study highlights the effectiveness of eDNA metabarcoding to efficiently characterise sedimentary bacterial community assemblages and emphasises its value in aquatic ecosystem assessments, particularly for the prediction of contaminants driving ecosystem change.