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Nitrate contamination in water remains to be on the rise globally due to continuous anthropogenic activities, such as mining and farming, which utilize high amounts of ammonium nitrate explosives and chemical-NPK-fertilizers, respectively. This study presents insights into the development of a bioremediation strategy to remove nitrates (NO3−) using consortia enriched from wastewater collected from a diamond mine in Lesotho and a platinum mine in South Africa. A biogeochemical analysis was conducted on the water samples which aided in comparing and elucidating their unique physicochemical parameters. The chemical analysis uncovered that both wastewater samples contained over 120 mg/L of NO3− and over 250 mg/L of sulfates (SO42-), which were both beyond the acceptable limit of the environmental surface water standards of South Africa. The samples were atypical of mine wastewaters as they had low concentrations of dissolved heavy metals and a pH of over 5. A metagenomic analysis applied to study microbial diversities revealed that both samples were dominated by the phyla Proteobacteria and Bacteroidetes, which accounted for over 40% and 15%, respectively. Three consortia were enriched to target denitrifying bacteria using selective media and then subjected to complete denitrification experiments. Denitrification dynamics and denitrifying capacities of the consortia were determined by monitoring dissolved and gaseous nitrogen species over time. Denitrification optimization was carried out by changing environmental conditions, including supplementing the cultures with metal enzyme co-factors (iron and copper) that were observed to promote different stages of denitrification. Copper supplemented at 50 mg/L was observed to be promoting complete denitrification of over 500 mg/L of NO3−, evidenced by the emission of nitrogen gas (N2) that was more than nitrous oxide gas (N2O) emitted as the terminal by-product. Modification and manipulation of growth conditions based on the microbial diversity enriched proved that it is possible to optimize a bioremediation system that can reduce high concentrations of NO3−, while emitting an environmentally-friendly N2 instead of N2O, that is, a greenhouse gas. Data collected and discussed in this research study can be used to model an upscale NO3− bioremediation system aimed to remove nitrogenous and other contaminants without secondary contamination.

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