<?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%">Izallalen, Mounir</style></author><author><style face="normal" font="default" size="100%">Mahadevan, Radhakrishnan</style></author><author><style face="normal" font="default" size="100%">Burgard, Anthony</style></author><author><style face="normal" font="default" size="100%">Postier, Bradley</style></author><author><style face="normal" font="default" size="100%">DiDonato, Raymond</style></author><author><style face="normal" font="default" size="100%">Sun, Jun</style></author><author><style face="normal" font="default" size="100%">Schilling, Christopher H</style></author><author><style face="normal" font="default" size="100%">Lovley, Derek R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Geobacter sulfurreducens strain engineered for increased rates of respiration.</style></title><secondary-title><style face="normal" font="default" size="100%">Metab Eng</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Metab. Eng.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adenosine Triphosphate</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacterial Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Biodegradation, Environmental</style></keyword><keyword><style  face="normal" font="default" size="100%">Citric Acid Cycle</style></keyword><keyword><style  face="normal" font="default" size="100%">Electron Transport</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%">NADH Dehydrogenase</style></keyword><keyword><style  face="normal" font="default" size="100%">NADP</style></keyword><keyword><style  face="normal" font="default" size="100%">Oxygen Consumption</style></keyword><keyword><style  face="normal" font="default" size="100%">Phosphates</style></keyword><keyword><style  face="normal" font="default" size="100%">Proton-Translocating ATPases</style></keyword><keyword><style  face="normal" font="default" size="100%">Radioactive Pollutants</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008 Sep</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">267-75</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Geobacter species are among the most effective microorganisms known for the bioremediation of radioactive and toxic metals in contaminated subsurface environments and for converting organic compounds to electricity in microbial fuel cells. However, faster rates of electron transfer could aid in optimizing these processes. Therefore, the Optknock strain design methodology was applied in an iterative manner to the constraint-based, in silico model of Geobacter sulfurreducens to identify gene deletions predicted to increase respiration rates. The common factor in the Optknock predictions was that each resulted in a predicted increase in the cellular ATP demand, either by creating ATP-consuming futile cycles or decreasing the availability of reducing equivalents and inorganic phosphate for ATP biosynthesis. The in silico model predicted that increasing the ATP demand would result in higher fluxes of acetate through the TCA cycle and higher rates of NADPH oxidation coupled with decreases in flux in reactions that funnel acetate toward biosynthetic pathways. A strain of G. sulfurreducens was constructed in which the hydrolytic, F(1) portion of the membrane-bound F(0)F(1) (H(+))-ATP synthase complex was expressed when IPTG was added to the medium. Induction of the ATP drain decreased the ATP content of the cell by more than half. The cells with the ATP drain had higher rates of respiration, slower growth rates, and a lower cell yield. Genome-wide analysis of gene transcript levels indicated that when the higher rate of respiration was induced transcript levels were higher for genes involved in energy metabolism, especially in those encoding TCA cycle enzymes, subunits of the NADH dehydrogenase, and proteins involved in electron acceptor reduction. This was accompanied by lower transcript levels for genes encoding proteins involved in amino acid biosynthesis, cell growth, and motility. Several changes in gene expression that involve processes not included in the in silico model were also detected, including increased expression of a number of redox-active proteins, such as c-type cytochromes and a putative multicopper outer-surface protein. The results demonstrate that it is possible to genetically engineer increased respiration rates in G. sulfurreducens in accordance with predictions from in silico metabolic modeling. To our knowledge, this is the first report of metabolic engineering to increase the respiratory rate of a microorganism.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/18644460?dopt=Abstract</style></custom1></record></records></xml>