@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}
}
@article {700,
	title = {Characterizing regulation of metabolism in Geobacter sulfurreducens through genome-wide expression data and sequence analysis.},
	journal = {OMICS},
	volume = {12},
	year = {2008},
	month = {2008 Mar},
	pages = {33-59},
	abstract = {Geobacteraceae are a family of metal reducing bacteria with important applications in bioremediation and electricity generation. G. sulfurreducens is a representative of Geobacteraceae that has been extensively studied with the goal of extending the understanding of this family of organisms for optimizing their practical applications. Here, we have analyzed gene expression data from 10 experiments involving environmental and genetic perturbations and have identified putative transcription factor binding sites (TFBS) involved in regulating key aspects of metabolism. Specifically, we considered data from both a subset of 10 microarray experiments (7 of 10) and all 10 experiments. The expression data from these two sets were independently clustered, and the upstream regions of genes and operons from the clusters in both sets were used to identify TFBS using the AlignACE program. This analysis resulted in the identification of motifs upstream of several genes involved in central metabolism, sulfate assimilation, and energy metabolism, as well as genes potentially encoding acetate permease. Further, similar TFBS were identified from the analysis of both sets, suggesting that these TFBS are significant in the regulation of metabolism in G. sulfurreducens. In addition, we have utilized microarray data to derive condition specific constraints on the capacity of key enzymes in central metabolism. We have incorporated these constraints into the metabolic model of G. sulfurreducens and simulated Fe(II)-limited growth. The resulting prediction was consistent with data, suggesting that regulatory constraints are important for simulating growth phenotypes in nonoptimal environments.},
	keywords = {Gene Expression Regulation, Bacterial, Genome, Bacterial, Geobacter, Models, Genetic, Oligonucleotide Array Sequence Analysis, Sequence Analysis, DNA, Transcription, Genetic},
	issn = {1536-2310},
	doi = {10.1089/omi.2007.0043},
	author = {Mahadevan, Radhakrishnan and Yan, Bin and Postier, Brad and Nevin, Kelly P and Woodard, Trevor L and O{\textquoteright}Neil, Regina and Coppi, Maddalena V and Meth{\'e}, Barbara A and Krushkal, Julia}
}
@article {489,
	title = {Computational and experimental analysis of redundancy in the central metabolism of Geobacter sulfurreducens.},
	journal = {PLoS Comput Biol},
	volume = {4},
	year = {2008},
	month = {2008 Feb},
	pages = {e36},
	abstract = {Previous model-based analysis of the metabolic network of Geobacter sulfurreducens suggested the existence of several redundant pathways. Here, we identified eight sets of redundant pathways that included redundancy for the assimilation of acetate, and for the conversion of pyruvate into acetyl-CoA. These equivalent pathways and two other sub-optimal pathways were studied using 5 single-gene deletion mutants in those pathways for the evaluation of the predictive capacity of the model. The growth phenotypes of these mutants were studied under 12 different conditions of electron donor and acceptor availability. The comparison of the model predictions with the resulting experimental phenotypes indicated that pyruvate ferredoxin oxidoreductase is the only activity able to convert pyruvate into acetyl-CoA. However, the results and the modeling showed that the two acetate activation pathways present are not only active, but needed due to the additional role of the acetyl-CoA transferase in the TCA cycle, probably reflecting the adaptation of these bacteria to acetate utilization. In other cases, the data reconciliation suggested additional capacity constraints that were confirmed with biochemical assays. The results demonstrate the need to experimentally verify the activity of key enzymes when developing in silico models of microbial physiology based on sequence-based reconstruction of metabolic networks.},
	keywords = {Bacterial Proteins, Base Sequence, Computer Simulation, Gene Expression Regulation, Bacterial, Geobacter, Models, Biological, Molecular Sequence Data, Multienzyme Complexes, Signal Transduction},
	issn = {1553-7358},
	doi = {10.1371/journal.pcbi.0040036},
	author = {Segura, Daniel and Mahadevan, Radhakrishnan and Ju{\'a}rez, Katy and Lovley, Derek R}
}
