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Identifying Signals of Septic Contamination in Groundwater Microbial Communities of the Grand Traverse Bay Watershed Maria Berry, 3rd year |
Abstract
Microbial communities in groundwater adapt to their local physical and chemical environment. When this environment contains contaminants, it may be reflected in the genetic content of resident microbial communities. This project explores the utilization of environmental DNA to record the influence of septic fields and other potential contaminants in the Grand Traverse Bay watershed by linking microbiological, geochemical, and hydrological approaches.
A total of 13 wells were sampled and analyzed for microbial cell counts, taxonomic diversity using the 16S rRNA gene, and genetic content using metagenomics. These data were explored for correlations with physical-chemical indicators of septic contamination (e.g. Br:Cl, Boron, xenobiotic compounds, antibiotic resistance genes, and human fecal microflora). Populations within the orders Betaproteobacteria and Chloroflexi were prevalent within the wells. Metagenomic data was used to construct metagenome assembled genomes from these clades that were then examined for the presence of functional and physiological adaptations to septic contamination. These included comparison to databases of antibiotic resistance genes, and searches for metabolic pathways involved in biogeochemical cycling and organic matter degradation. Knowledge about the composition of groundwater microbial communities, their relationship to potential contaminants and to hydrology is critical to the potential use of eDNA as an environmental tracer. In Michigan, there are approximately 1.3 million septic systems, and at least 10 percent of those systems are failing. Developing a unique ″fingerprint″ for septic contamination can inform mitigation and management strategies that can protect important water resources in the state, including the Grand Traverse Bay Watershed.