The Variation in Groundwater Microbial Communities in an Unconfined Aquifer Contaminated by Multiple Nitrogen Contamination Sources

Abstract

Aquifers provide integral freshwater resources and host ecosystems of largely uncharacterized, truncated endemic microorganisms. In recent history, many aquifers have become increasingly contaminated from various anthropogenic sources. To better understand the impacts of nitrogen contamination on native groundwater ecosystems, 16S rRNA sequencing of the groundwater microbial communities was carried out. Samples were taken from an aquifer known to be contaminated with nitrogen from multiple sources, including fertilizers and wastewater treatment plant effluents. In total, two primary contaminants were identified: NH4+ (<0.1–3.7–26 mg L−1 NH4+ min-median-max), and NO3− (<0.01–18–150 mg L−1 NO3− min-median-max). These contaminants were found to be associated with a decrease/increase in microbial species richness within affected groundwater for NH4+/NO3−, respectively. Important phyla were identified, including Proteobacteria, which had the highest abundance within samples unaffected by NH4+ (36–81% NH4+ unaffected, 4–33% NH4+ affected), and Planctomycetes (0.05–10% NH4+ unaffected, 43–72% NH4+ affected), which had the highest abundance within the NH4+ affected samples, likely due to its ability to perform anaerobic ammonia oxidation (ANAMMOX). Planctomycetes were identified as a potential indicator for the presence of NH4+ contamination. The analysis and characterization of sequencing data alongside physicochemical data showed potential to increase the depth of our understanding of contaminant behavior and fate within a contaminated aquifer using this type of data and analysis.

From the Mountain to the Valley: Drivers of Groundwater Prokaryotic Communities along an Alpine River Corridor

“…In the RNA-derived fraction, there is an increasing presence of Proteobacteria, mainly composed of Gammaproteobacteria, comprising almost half of the reads of the active groundwater community. No matter the nucleic acid fraction, Proteobacteria comprise the most abundant phylum present, as has also been observed in other groundwater studies [ 95 , 96 , 97 ]. A more extensive picture into the groundwater microbiome could emerge if microbial communities attached to the aquifer matrices as well as microeukaryotes were also included in a future analysis, since they will contribute significantly to compositional aspects as well as functions [ 98 ].…”

Differentiation between Impacted and Unimpacted Microbial Communities of a Nitrogen Contaminated Aquifer

“…Other than the data analysis, the methods adopted here are the same as those outlined in Morrissy et al [16] (with some minor rewording), as this current paper is a further analysis of the data (towards the objectives outlined above) as a part of a larger research project.…”

“…All bores were not able to be sampled on every sampling campaign (hence 24 samples instead of 30); all samples were taken in triplicate (resulting in a total of 72 subsamples). The three sampling campaigns took place in August 2018, November 2018 and May 2019 (more detail on the bores sampled in each campaign can be found in Morrissy et al [16] Table 1). The locations of the sampled bores are shown in Figure 1.…”

“…The analysis of the data presented in Morrissy et al [16] allowed us to identify three 'contamination zones' which were defined by no known presence of contamination in the uncontaminated bores (UB's) (BS-002 and BS-004), the presence of NO 3 − contamination (NCBs) (bores DSE63273, RB23, RB10 and RB6/7) and the presence of NO 3 − and NH 4 + contamination (ANCBs) (bores RB12 and RB17/18). Using MANOVA analysis of the physicochemical data with the N variables as the dependent variables, we determined if there was any statistically significant difference between the contamination zones with regard to N contamination (Table 2).…”

“…Our previous work in Morrissy et al [16] identified that nitrogen pollution had an effect on the microbial communities at the Boneo site in Victoria, Australia; additionally, multiple papers have discussed the structure of microbial communities and how they change over different conditions [17][18][19]. The importance of this work lies in the novelty of utilising a relatively small dataset to show the effects of pollution on the major ecosystem functions of microbial communities in groundwater and how we can use this information to predict contaminant impact, fate, and behaviour in groundwater.…”