Deep Subsurface Microbial Biomass and Community Structure in Witwatersrand Basin Mines

The extreme environments of South Africa mines were investigated to determine microbial community structure and biomass in the deep subsurface. These community parameters were determined using phospholipid fatty acid (PLFA) technique. Air, water and rock samples were collected from several levels and shafts in eight different mines. Biomass estimates ranged over nine orders of magnitude. Biofilm samples exhibited the highest biomass with quantities ranging from 10 ³ to 10 ⁷ pmol PLFA g ^?1 . Rock samples had biomass ranging from 10 ³ to 10 ⁶ pmol PLFA g ^?1 . Mine service waters and rock fracture waters had biomass estimates ranging from 10 ⁰ to 10 ⁶ pmol PLFA L ^?1 . Air samples biomass values ranged from 10 ^?2 to 10 ⁰ pmol PLFA L ^?1 . The biomass estimates were similar to those estimates for other deep subsurface sites. Redundancy analysis of the PLFA profiles distinguished between the sample types, where signature lipid biomarkers for aerobic and anaerobic prokaryotes, sulfate-and metal-reducing bacteria were associated with biofilms. Rock samples were enriched in 18:1 ω 9 c , 18:2 ω 6, br17:1s and br18:1s, which are indicative of microeukaryotes and metal- reducing bacteria. Air samples were enriched with 22:0, 17:1, 18:1, and a polyunsaturated fatty acid. Service waters had monounsaturated fatty acids. Fracture waters contained i17:0 and 10Me18:0 which indicated gram-positive and other anaerobic bacteria. When the fracture and service water sample PLFA responses to changes in environmental parameters of temperature, pH, and anion concentrations were analyzed, service waters correlated with higher nitrate and sulfate concentrations and the PLFAs 18:1 ω 7 c and 16:1 ω 7 c . Dreifontein shaft 5 samples correlated with chloride concentrations and terminally branched saturated fatty acids and branched monounsaturated fatty acids. Kloof, Tau Tona, and Merriespruit fracture waters aligned with temperature and pH vectors and 18:0, 20:0 and 22:6 ω 3. The redundancy analysis provided a robust method to understand the PLFA responses to changes in environmental parameters.