Bioinformatics Analysis of Microbial Abundance and Diversity in Acid Mine Drainage from the Solomon Mine Near Creede, Colorado

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Miller, Ryan K.
Kirkham, Robert M.
Kleinschmit, Adam J.
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Acid mine drainage
Microbial ecology
16S rRna marker gene survey
High throughput sequencing
Environmental microbiota
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This study focused on characterizing the phylotypic composition of acid mine drainage (AMD) communities associated with the Solomon Mine near Creede, Colorado, and its relative diversity compared to microbial communities found in the East Willow Creek (EWC) watershed. AMD from the Solomon Mine adit flows into an existing passive bioremediation wetland system located next to the Solomon Mine adit that currently is ineffective and is under consideration for renovation. We are interested in gaining an understanding of the baseline microbial communities present in AMD/EWC and to monitor them during future wetland renovation. Prokaryotic community profiling was approached using SSU 16S rRNA marker gene amplification coupled with next generation sequencing. Bioinformatics analysis included raw read preprocessing, data visualization, and statistical testing using a combination of USEARCH and QIIME-based scripts. A pH and conductivity gradient were observed for water moving through the currently inefficient wetland system at the Solomon Mine. The EWC microbiomes had statistically significant higher alpha diversity compared to the AMD microbiomes. Beta diversity analysis parsed the sample locations into statistically significant groups including core AMD microbiomes, the wetland Cell 3 microbiome, and EWC microbiomes using multidimensional scaling. Taxa driving beta diversity included the phylum Proteobacteria for the core AMD microbiomes, the phyla Firmicutes and Chloroflexi for the constructed wetland Cell 3, and the phyla Bacteroidetes and Verrucomicrobia for EWC. Our data suggests that the microbial community in constructed wetland Cell 3 is likely where limited sulfate reduction activity is operating at low capacity, which will be further investigated via shotgun metagenomic analysis.