Survival of bacterial indicators and the functional diversity of native microbial communities in the Floridan aquifer system, south Florida

The Upper Floridan aquifer in the southern region of Florida is a multi-use, regional scale aquifer that is used as a potable water source and as a repository for passively recharged untreated surface waters, and injected treated surface water and wastewater, industrial wastes, including those which contain greenhouse gases (for example, carbon dioxide). The presence of confined zones within the Floridan aquifer that range in salinity from fresh to brackish allow regulatory agencies to permit the injection of these different types of product waters into specific zones without detrimental effects to humans and terrestrial and aquatic ecosystems. The type of recharge that has received the most regulatory attention in south Florida is aquifer storage and recovery (ASR). The treated water, prior to injection and during recovery, must meet primary and secondary drinking water standards. The primary microbiology drinking water standard is total coliforms, which have been shown to be difficult to inactivate below the regulatory standard during the treatment process at some ASR facilities. The inefficient inactivation of this group of indicator bacteria permits their direct injection into the storage zones of the Floridan aquifer. Prior to this study, the inactivation rates for any member of the total coliform group during exposure to native geochemical conditions in groundwater from any zone of the Floridan aquifer had not been derived.

Aboveground flow through mesocosms and diffusion chambers were used to quantify the inactivation rates of two bacterial indicators, Escherichia coli and Pseudomonas aeruginosa, during exposure to groundwater from six wells. These wells collect water from two ASR storage zones: the Upper Floridan aquifer (UFA) and Avon Park Permeable Zone (APPZ). Both bacterial strains followed a biphasic inactivation model. The E. coli populations had slower inactivation rates in the UFA (range: 0.217–0.628 per hour (h^-1)) during the first phase of the model than when exposed to groundwater from the APPZ (range: 0.540–0.684 h^-1). The inactivation rates for the first phase of the models for P. aeruginosa were not significantly different between the UFA (range: 0.144–0.770 h^-1) and APPZ (range: 0.159–0.772 h^-1) aquifer zones. The inactivation rates for the second phase of the model for this P. aeruginosa were also similar between UFA (range: 0.003–0.008 h^-1) and APPZ (0.004–0.005 h^-1) zones, although significantly slower than the model’s first phase rates for this bacterial species.

Geochemical data were used to determine which dissimilatory biogeochemical reactions were most likely to occur under the native conditions in the UFA and APPZ zones using thermodynamics principles to calculate free energy yields and other cell-related energetics data. The biogeochemical processes of acetotrophic and hydrogenotrophic sulfate reduction, methanogenesis and anaerobic oxidation of methane dominated in all six groundwater sites.

A high throughput DNA microarray sequencing technology was used to characterize the diversity in the native aquifer bacterial communities (bacteria and archaea) and assign putative physiological capabilities to the members of those communities. The bacterial communities in both zones of the aquifer were shown to possess the capabilities for primary and secondary fermentation, acetogenesis, methanogenesis, anaerobic methane oxidation, syntrophy with methanogens, ammonification, and sulfate reduction.

The data from this study provide the first determination of bacterial indicator survival during exposure to native geochemical conditions of the Floridan aquifer in south Florida. Additionally, the energetics and functional bacterial diversity characterizations are the first descriptions of native bacterial communities in this region of the Floridan aquifer and reveal how these communities persist under such extreme conditions. Collectively, these types of data can be used to develop and refine groundwater models.