Influence of ammonium availability on expression of nifD and amtB genes during biostimulation of a U(VI) contaminated aquifer: implications for U(VI) removal and monitoring the metabolic state of Geobacteraceae
2009
Author(s): Mouser, Paula J.; N'Guessan, A. Lucie; Elifantz, Hila; Holmes, Dawn E.; Williams, Kenneth H; Wilkins, Michael J.; Long, Philip E.; Lovley, Derek R. | Abstract: The influence of ammonium availability on bacterial community structure and the physiological status of Geobacter species during in situ bioremediation of uranium-contaminated groundwater was evaluated. Ammonium concentrations varied by 2 orders of magnitude (l4 to 400 ?M) across the study site. Analysis of 16S rRNA sequences suggested that ammonium may have been one factor influencing the community composition prior to acetate amendment with Rhodoferax species predominating over Geobacter species with higher ammonium and Dechloromonas species dominating at the site with lowest ammonium. However, once acetate was added and dissimilatory metal reduction was stimulated, Geobacter species became the predominant organisms at all locations. Rates of U(VI) reduction appeared to be more related to acetate concentrations rather than ammonium levels. In situ mRNA transcript abundance of the nitrogen fixation gene, nifD, and the ammonium transporter gene, amtB, in Geobacter species indicated that ammonium was the primary source of nitrogen during uranium reduction. The abundance of amtB was inversely correlated to ammonium levels, whereas nifD transcript levels were similar across all sites examined. These results suggest that nifD and amtB expression are closely regulated in response to ammonium availability to ensure an adequate supply of nitrogen while conserving cell resources. Thus, quantifying nifD and amtB transcript expression appears to be a useful approach for monitoring the nitrogen-related physiological status of subsurface Geobacter species. This study also emphasizes the need for more detailed analysis of geochemical and physiological interactions at the field scale in order to adequately model subsurface microbial processes during bioremediation.
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