@article {3154,
	title = {Characterization and transcription of arsenic respiration and resistance genes during in situ uranium bioremediation.},
	journal = {ISME J},
	volume = {7},
	year = {2013},
	month = {2013 Feb},
	pages = {370-83},
	abstract = {<p>The possibility of arsenic release and the potential role of Geobacter in arsenic biogeochemistry during in situ uranium bioremediation was investigated because increased availability of organic matter has been associated with substantial releases of arsenic in other subsurface environments. In a field experiment conducted at the Rifle, CO study site, groundwater arsenic concentrations increased when acetate was added. The number of transcripts from arrA, which codes for the α-subunit of dissimilatory As(V) reductase, and acr3, which codes for the arsenic pump protein Acr3, were determined with quantitative reverse transcription-PCR. Most of the arrA (>60\%) and acr3-1 (>90\%) sequences that were recovered were most similar to Geobacter species, while the majority of acr3-2 (>50\%) sequences were most closely related to Rhodoferax ferrireducens. Analysis of transcript abundance demonstrated that transcription of acr3-1 by the subsurface Geobacter community was correlated with arsenic concentrations in the groundwater. In contrast, Geobacter arrA transcript numbers lagged behind the major arsenic release and remained high even after arsenic concentrations declined. This suggested that factors other than As(V) availability regulated the transcription of arrA in situ, even though the presence of As(V) increased the transcription of arrA in cultures of Geobacter lovleyi, which was capable of As(V) reduction. These results demonstrate that subsurface Geobacter species can tightly regulate their physiological response to changes in groundwater arsenic concentrations. The transcriptomic approach developed here should be useful for the study of a diversity of other environments in which Geobacter species are considered to have an important influence on arsenic biogeochemistry.</p>},
	keywords = {Acetates, Arsenate Reductases, Arsenic, Biodegradation, Environmental, Colorado, Gene Expression Regulation, Bacterial, Genes, Bacterial, Geobacter, Groundwater, Transcriptome, Uranium},
	issn = {1751-7370},
	doi = {10.1038/ismej.2012.109},
	author = {Giloteaux, Ludovic and Holmes, Dawn E and Williams, Kenneth H and Wrighton, Kelly C and Wilkins, Michael J and Montgomery, Alison P and Smith, Jessica A and Orellana, Roberto and Thompson, Courtney A and Roper, Thomas J and Long, Philip E and Lovley, Derek R}
}
@article {464,
	title = {Coupling a genome-scale metabolic model with a reactive transport model to describe in situ uranium bioremediation.},
	journal = {Microb Biotechnol},
	volume = {2},
	year = {2009},
	month = {2009 Mar},
	pages = {274-86},
	abstract = {The increasing availability of the genome sequences of microorganisms involved in important bioremediation processes makes it feasible to consider developing genome-scale models that can aid in predicting the likely outcome of potential subsurface bioremediation strategies. Previous studies of the in situ bioremediation of uranium-contaminated groundwater have demonstrated that Geobacter species are often the dominant members of the groundwater community during active bioremediation and the primary organisms catalysing U(VI) reduction. Therefore, a genome-scale, constraint-based model of the metabolism of Geobacter sulfurreducens was coupled with the reactive transport model HYDROGEOCHEM in an attempt to model in situ uranium bioremediation. In order to simplify the modelling, the influence of only three growth factors was considered: acetate, the electron donor added to stimulate U(VI) reduction; Fe(III), the electron acceptor primarily supporting growth of Geobacter; and ammonium, a key nutrient. The constraint-based model predicted that growth yields of Geobacter varied significantly based on the availability of these three growth factors and that there are minimum thresholds of acetate and Fe(III) below which growth and activity are not possible. This contrasts with typical, empirical microbial models that assume fixed growth yields and the possibility for complete metabolism of the substrates. The coupled genome-scale and reactive transport model predicted acetate concentrations and U(VI) reduction rates in a field trial of in situ uranium bioremediation that were comparable to the predictions of a calibrated conventional model, but without the need for empirical calibration, other than specifying the initial biomass of Geobacter. These results suggest that coupling genome-scale metabolic models with reactive transport models may be a good approach to developing models that can be truly predictive, without empirical calibration, for evaluating the probable response of subsurface microorganisms to possible bioremediation approaches prior to implementation.},
	keywords = {Acetates, Biodegradation, Environmental, Biological Transport, Genome, Bacterial, Geobacter, Iron, Models, Biological, Uranium},
	issn = {1751-7915},
	doi = {10.1111/j.1751-7915.2009.00087.x},
	author = {Scheibe, Timothy D and Mahadevan, Radhakrishnan and Fang, Yilin and Garg, Srinath and Long, Philip E and Lovley, Derek R}
}
