@article {466,
	title = {Genome-scale constraint-based modeling of Geobacter metallireducens.},
	journal = {BMC Syst Biol},
	volume = {3},
	year = {2009},
	month = {2009},
	pages = {15},
	abstract = {BACKGROUND: Geobacter metallireducens was the first organism that can be grown in pure culture to completely oxidize organic compounds with Fe(III) oxide serving as electron acceptor. Geobacter species, including G. sulfurreducens and G. metallireducens, are used for bioremediation and electricity generation from waste organic matter and renewable biomass. The constraint-based modeling approach enables the development of genome-scale in silico models that can predict the behavior of complex biological systems and their responses to the environments. Such a modeling approach was applied to provide physiological and ecological insights on the metabolism of G. metallireducens.

RESULTS: The genome-scale metabolic model of G. metallireducens was constructed to include 747 genes and 697 reactions. Compared to the G. sulfurreducens model, the G. metallireducens metabolic model contains 118 unique reactions that reflect many of G. metallireducens{\textquoteright} specific metabolic capabilities. Detailed examination of the G. metallireducens model suggests that its central metabolism contains several energy-inefficient reactions that are not present in the G. sulfurreducens model. Experimental biomass yield of G. metallireducens growing on pyruvate was lower than the predicted optimal biomass yield. Microarray data of G. metallireducens growing with benzoate and acetate indicated that genes encoding these energy-inefficient reactions were up-regulated by benzoate. These results suggested that the energy-inefficient reactions were likely turned off during G. metallireducens growth with acetate for optimal biomass yield, but were up-regulated during growth with complex electron donors such as benzoate for rapid energy generation. Furthermore, several computational modeling approaches were applied to accelerate G. metallireducens research. For example, growth of G. metallireducens with different electron donors and electron acceptors were studied using the genome-scale metabolic model, which provided a fast and cost-effective way to understand the metabolism of G. metallireducens.

CONCLUSION: We have developed a genome-scale metabolic model for G. metallireducens that features both metabolic similarities and differences to the published model for its close relative, G. sulfurreducens. Together these metabolic models provide an important resource for improving strategies on bioremediation and bioenergy generation.},
	keywords = {Biodegradation, Environmental, Biomass, Computer Simulation, Ecosystem, Electron Transport, Energy Metabolism, Genome, Bacterial, Geobacter, Iron, Metabolic Networks and Pathways, Models, Biological, Models, Genetic, Mutation, Phenotype, Species Specificity, Systems Biology},
	issn = {1752-0509},
	doi = {10.1186/1752-0509-3-15},
	author = {Sun, Jun and Sayyar, Bahareh and Butler, Jessica E and Pharkya, Priti and Fahland, Tom R and Famili, Iman and Schilling, Christophe H and Lovley, Derek R and Mahadevan, Radhakrishnan}
}
@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}
}
