<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sun, Jun</style></author><author><style face="normal" font="default" size="100%">Sayyar, Bahareh</style></author><author><style face="normal" font="default" size="100%">Butler, Jessica E</style></author><author><style face="normal" font="default" size="100%">Pharkya, Priti</style></author><author><style face="normal" font="default" size="100%">Fahland, Tom R</style></author><author><style face="normal" font="default" size="100%">Famili, Iman</style></author><author><style face="normal" font="default" size="100%">Schilling, Christophe H</style></author><author><style face="normal" font="default" size="100%">Lovley, Derek R</style></author><author><style face="normal" font="default" size="100%">Mahadevan, Radhakrishnan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-scale constraint-based modeling of Geobacter metallireducens.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Syst Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BMC Syst Biol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biodegradation, Environmental</style></keyword><keyword><style  face="normal" font="default" size="100%">Biomass</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecosystem</style></keyword><keyword><style  face="normal" font="default" size="100%">Electron Transport</style></keyword><keyword><style  face="normal" font="default" size="100%">Energy Metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Geobacter</style></keyword><keyword><style  face="normal" font="default" size="100%">Iron</style></keyword><keyword><style  face="normal" font="default" size="100%">Metabolic Networks and Pathways</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Species Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Systems Biology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">15</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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' 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.</style></abstract><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19175927?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yan, Bin</style></author><author><style face="normal" font="default" size="100%">Lovley, Derek R</style></author><author><style face="normal" font="default" size="100%">Krushkal, Julia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-wide similarity search for transcription factors and their binding sites in a metal-reducing prokaryote Geobacter sulfurreducens.</style></title><secondary-title><style face="normal" font="default" size="100%">Biosystems</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BioSystems</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bacterial Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Binding Sites</style></keyword><keyword><style  face="normal" font="default" size="100%">False Positive Reactions</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Geobacter</style></keyword><keyword><style  face="normal" font="default" size="100%">Metals</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Statistical</style></keyword><keyword><style  face="normal" font="default" size="100%">Operon</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword><keyword><style  face="normal" font="default" size="100%">Sigma Factor</style></keyword><keyword><style  face="normal" font="default" size="100%">Systems Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription, Genetic</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2007 Sep-Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">90</style></volume><pages><style face="normal" font="default" size="100%">421-41</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The knowledge obtained from understanding individual elements involved in gene regulation is important for reconstructing gene regulatory networks, a key for understanding cellular behavior. To study gene regulatory interactions in a model microorganism, Geobacter sulfurreducens, which participates in metal reduction and energy harvesting, we investigated the presence of 59 known Escherichia coli transcription factors and predicted transcription regulatory sites in its genome. The supplementary material, available at http://www.geobacter.org/research/genomescan/, provides the results of similarity comparisons that identified regulatory proteins of G. sulfurreducens and the genome locations of the predicted regulatory sites, including the list of putative regulatory elements in the upstream regions of every predicted operon and singleton open reading frame. Regulatory sequence elements, predicted using genome similarity searches to matrices of established transcription regulatory elements from E. coli, provide an initial insight into regulation of genes and operons in G. sulfurreducens. The predicted regulatory elements were predominantly located in the upstream regions of operons and singleton open reading frames. The validity of the predictions was examined using a permutation approach. Sequence similarity searches indicate that E. coli transcription factors ArgR, CytR, DeoR, FlhCD (both FlhC and FlhD subunits), FruR, GalR, GlpR, H-NS, LacI, MetJ, PurR, TrpR, and Tus are likely missing from G. sulfurreducens. Phylogenetic analysis suggests that one HU subunit is present in G. sulfurreducens as compared to two subunits in E. coli, while each of the two E. coli IHF subunits, HimA and HimD, have two homologs in G. sulfurreducens. The closest homolog of E. coli RpoE in G. sulfurreducens may be more similar to FecI than to RpoE. These findings represent the first step in the understanding of the regulatory relationships in G. sulfurreducens on the genome scale.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/17184904?dopt=Abstract</style></custom1></record></records></xml>