NCM 2021: Analysing regional and seasonal microbial community variation from a contaminated Montana river

Megan is part of the CREWS project – Consortium for Research on Environmental Water Systems. The research goal is to study Montana’s environmental water systems and specific quality issues. Megan’s research focusses on water quality impacts related to hard water mining in the Upper Clark Ford River, which is known as ‘The Richest Hill on Earth’ due to its copper. Unfortunately, extensive mining has left behind poor water quality due to mining waste. In 1908, a flood led to millions of tons of mine tailings contaminating the waterway. It’s currently designated as one of the largest sites contaminated by toxic waste. Millions of dollars have been given by the government to help and clean-up efforts have been going on for over a decade, but nobody has studied how the poor water quality affects the microbial community. The CREWS team are investigating 13 areas in this river; Megan has been involved in six of these and will discuss results from three areas. Megan has processed ‘16S sequence data to analyse phylogenetic relationships among organisms to understand the microbial communities’. Megan particularly wanted to look at 1) regional variation along the river, and 2) seasonal effects in microbial communities and algal blooms. Samples from the rocks in the river were collected and DNA was extracted for 16S amplification, library preparation and sequencing using MinION. Data analysis was performed using Guppy basecalling and EPI2ME Agent for taxonomic analysis. Megan analyzed the levels of ‘Bacteroidetes, Cyanobacteria, Firmicutes, Planctomycetes, Proteobacteria, and Other’ in spring and summer samples. Further analysis looked into the different Cyanobacteria species: Oscillatoriales, Nostocales, Synechococcales and Nostocaceae, because of the association with toxic algal blooms. Megan discusses her future goals and how she will connect her research findings with the environmental characteristics of the study sites.