<?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%">Lovley, Derek R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Happy together: microbial communities that hook up to swap electrons.</style></title><secondary-title><style face="normal" font="default" size="100%">ISME J</style></secondary-title><alt-title><style face="normal" font="default" size="100%">ISME J</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Archaea</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacteria</style></keyword><keyword><style  face="normal" font="default" size="100%">Electron Transport</style></keyword><keyword><style  face="normal" font="default" size="100%">Methane</style></keyword><keyword><style  face="normal" font="default" size="100%">Microbial Consortia</style></keyword><keyword><style  face="normal" font="default" size="100%">Microbial Interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Oxidation-Reduction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">327-336</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The discovery of direct interspecies electron transfer (DIET) and cable bacteria has demonstrated that microbial cells can exchange electrons over long distances (μm-cm) through electrical connections. For example, in the presence of cable bacteria electrons are rapidly transported over centimeter distances, coupling the oxidation of reduced sulfur compounds in anoxic sediments to oxygen reduction in overlying surficial sediments. Bacteria and archaea wired for DIET are found in anaerobic methane-producing and methane-consuming communities. Electrical connections between gut microbes and host cells have also been proposed. Iterative environmental and defined culture studies on methanogenic communities revealed the importance of electrically conductive pili and c-type cytochromes in natural electrical grids, and demonstrated that conductive carbon materials and magnetite can substitute for these biological connectors to facilitate DIET. This understanding has led to strategies to enhance and stabilize anaerobic digestion. Key unknowns warranting further investigation include elucidation of the archaeal electrical connections facilitating DIET-based methane production and consumption; and the mechanisms for long-range electron transfer through cable bacteria. A better understanding of mechanisms for cell-to-cell electron transfer could facilitate the hunt for additional electrically connected microbial communities with omics approaches and could advance spin-off applications such as the development of sustainable bioelectronics materials and bioelectrochemical technologies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/27801905?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%">Feist, Adam M</style></author><author><style face="normal" font="default" size="100%">Nagarajan, Harish</style></author><author><style face="normal" font="default" size="100%">Rotaru, Amelia-Elena</style></author><author><style face="normal" font="default" size="100%">Tremblay, Pier-Luc</style></author><author><style face="normal" font="default" size="100%">Zhang, Tian</style></author><author><style face="normal" font="default" size="100%">Nevin, Kelly P</style></author><author><style face="normal" font="default" size="100%">Lovley, Derek R</style></author><author><style face="normal" font="default" size="100%">Zengler, Karsten</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Constraint-based modeling of carbon fixation and the energetics of electron transfer in Geobacter metallireducens.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Comput Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS Comput Biol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Carbon</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%">Models, Biological</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">e1003575</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Geobacter species are of great interest for environmental and biotechnology applications as they can carry out direct electron transfer to insoluble metals or other microorganisms and have the ability to assimilate inorganic carbon. Here, we report on the capability and key enabling metabolic machinery of Geobacter metallireducens GS-15 to carry out CO2 fixation and direct electron transfer to iron. An updated metabolic reconstruction was generated, growth screens on targeted conditions of interest were performed, and constraint-based analysis was utilized to characterize and evaluate critical pathways and reactions in G. metallireducens. The novel capability of G. metallireducens to grow autotrophically with formate and Fe(III) was predicted and subsequently validated in vivo. Additionally, the energetic cost of transferring electrons to an external electron acceptor was determined through analysis of growth experiments carried out using three different electron acceptors (Fe(III), nitrate, and fumarate) by systematically isolating and examining different parts of the electron transport chain. The updated reconstruction will serve as a knowledgebase for understanding and engineering Geobacter and similar species.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/24762737?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%">Meniche, Xavier</style></author><author><style face="normal" font="default" size="100%">Otten, Renee</style></author><author><style face="normal" font="default" size="100%">Siegrist, M Sloan</style></author><author><style face="normal" font="default" size="100%">Baer, Christina E</style></author><author><style face="normal" font="default" size="100%">Murphy, Kenan C</style></author><author><style face="normal" font="default" size="100%">Bertozzi, Carolyn R</style></author><author><style face="normal" font="default" size="100%">Sassetti, Christopher M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Subpolar addition of new cell wall is directed by DivIVA in mycobacteria.</style></title><secondary-title><style face="normal" font="default" size="100%">Proc Natl Acad Sci U S A</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Proc. Natl. Acad. Sci. U.S.A.</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%">Cell Cycle Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Membrane</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Polarity</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Wall</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Mycobacterium smegmatis</style></keyword><keyword><style  face="normal" font="default" size="100%">Mycolic Acids</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Binding</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Aug 5</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">111</style></volume><pages><style face="normal" font="default" size="100%">E3243-51</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Mycobacteria are surrounded by a complex multilayered envelope and elongate at the poles. The principles that organize the coordinated addition of chemically diverse cell wall layers during polar extension remain unclear. We show that enzymes mediating the terminal cytosolic steps of peptidoglycan, arabinogalactan, and mycolic acid synthesis colocalize at sites of cell growth or division. The tropomyosin-like protein, DivIVA, is targeted to the negative curvature of the pole, is enriched at the growing end, and determines cell shape from this site. In contrast, cell wall synthetic complexes are concentrated at a distinct subpolar location. When viewed at subdiffraction resolution, new peptidoglycan is deposited at this subpolar site, and inert cell wall covers the DivIVA-marked tip. The differentiation between polar tip and cell wall synthetic complexes is also apparent at the biochemical level. Enzymes that generate mycolate precursors interact with DivIVA, but the final condensation of mycolic acids occurs in a distinct protein complex at the site of nascent cell wall addition. We propose an ultrastructural model of mycobacterial polar growth where new cell wall is added in an annular zone below the cell tip. This model may be broadly applicable to other bacterial and fungal organisms that grow via polar extension.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">31</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/25049412?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%">Nagarajan, Harish</style></author><author><style face="normal" font="default" size="100%">Embree, Mallory</style></author><author><style face="normal" font="default" size="100%">Rotaru, Amelia-Elena</style></author><author><style face="normal" font="default" size="100%">Shrestha, Pravin M</style></author><author><style face="normal" font="default" size="100%">Feist, Adam M</style></author><author><style face="normal" font="default" size="100%">Palsson, Bernhard Ø</style></author><author><style face="normal" font="default" size="100%">Lovley, Derek R</style></author><author><style face="normal" font="default" size="100%">Zengler, Karsten</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterization and modelling of interspecies electron transfer mechanisms and microbial community dynamics of a syntrophic association.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adaptation, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Electron Transport</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%">Microbial Interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Symbiosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">2809</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Syntrophic associations are central to microbial communities and thus have a fundamental role in the global carbon cycle. Despite biochemical approaches describing the physiological activity of these communities, there has been a lack of a mechanistic understanding of the relationship between complex nutritional and energetic dependencies and their functioning. Here we apply a multi-omic modelling workflow that combines genomic, transcriptomic and physiological data with genome-scale models to investigate dynamics and electron flow mechanisms in the syntrophic association of Geobacter metallireducens and Geobacter sulfurreducens. Genome-scale modelling of direct interspecies electron transfer reveals insights into the energetics of electron transfer mechanisms. While G. sulfurreducens adapts to rapid syntrophic growth by changes at the genomic and transcriptomic level, G. metallireducens responds only at the transcriptomic level. This multi-omic approach enhances our understanding of adaptive responses and factors that shape the evolution of syntrophic communities.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/24264237?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%">Qiu, Yu</style></author><author><style face="normal" font="default" size="100%">Nagarajan, Harish</style></author><author><style face="normal" font="default" size="100%">Embree, Mallory</style></author><author><style face="normal" font="default" size="100%">Shieu, Wendy</style></author><author><style face="normal" font="default" size="100%">Abate, Elisa</style></author><author><style face="normal" font="default" size="100%">Juárez, Katy</style></author><author><style face="normal" font="default" size="100%">Cho, Byung-Kwan</style></author><author><style face="normal" font="default" size="100%">Elkins, James G</style></author><author><style face="normal" font="default" size="100%">Nevin, Kelly P</style></author><author><style face="normal" font="default" size="100%">Barrett, Christian L</style></author><author><style face="normal" font="default" size="100%">Lovley, Derek R</style></author><author><style face="normal" font="default" size="100%">Palsson, Bernhard O</style></author><author><style face="normal" font="default" size="100%">Zengler, Karsten</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterizing the interplay between multiple levels of organization within bacterial sigma factor regulatory networks.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Energy Metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Regulatory Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Geobacter</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Regulon</style></keyword><keyword><style  face="normal" font="default" size="100%">Sigma Factor</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">1755</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Bacteria contain multiple sigma factors, each targeting diverse, but often overlapping sets of promoters, thereby forming a complex network. The layout and deployment of such a sigma factor network directly impacts global transcriptional regulation and ultimately dictates the phenotype. Here we integrate multi-omic data sets to determine the topology, the operational, and functional states of the sigma factor network in Geobacter sulfurreducens, revealing a unique network topology of interacting sigma factors. Analysis of the operational state of the sigma factor network shows a highly modular structure with σ(N) being the major regulator of energy metabolism. Surprisingly, the functional state of the network during the two most divergent growth conditions is nearly static, with sigma factor binding profiles almost invariant to environmental stimuli. This first comprehensive elucidation of the interplay between different levels of the sigma factor network organization is fundamental to characterize transcriptional regulatory mechanisms in bacteria.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/23612296?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%">He, Ying</style></author><author><style face="normal" font="default" size="100%">Swaminathan, Aishwarya</style></author><author><style face="normal" font="default" size="100%">Lopes, John M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transcription regulation of the Saccharomyces cerevisiae PHO5 gene by the Ino2p and Ino4p basic helix-loop-helix proteins.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Microbiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol. Microbiol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Acid Phosphatase</style></keyword><keyword><style  face="normal" font="default" size="100%">Basic Helix-Loop-Helix Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromatin Immunoprecipitation</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA, Fungal</style></keyword><keyword><style  face="normal" font="default" size="100%">Enhancer Elements, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Fungal</style></keyword><keyword><style  face="normal" font="default" size="100%">Inositol</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Phospholipids</style></keyword><keyword><style  face="normal" font="default" size="100%">Promoter Regions, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Binding</style></keyword><keyword><style  face="normal" font="default" size="100%">Saccharomyces cerevisiae</style></keyword><keyword><style  face="normal" font="default" size="100%">Saccharomyces cerevisiae Proteins</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%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">83</style></volume><pages><style face="normal" font="default" size="100%">395-407</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The Saccharomyces cerevisiae PHO5 gene product accounts for a majority of the acid phosphatase activity. Its expression is induced by the basic helix-loop-helix (bHLH) protein, Pho4p, in response to phosphate depletion. Pho4p binds predominantly to two UAS elements (UASp1 at -356 and UASp2 at -247) in the PHO5 promoter. Previous studies from our lab have shown cross-regulation of different biological processes by bHLH proteins. This study tested the ability of all yeast bHLH proteins to regulate PHO5 expression and identified inositol-mediated regulation via the Ino2p/Ino4p bHLH proteins. Ino2p/Ino4p are known regulators of phospholipid biosynthetic genes. Genetic epistasis experiments showed that regulation by inositol required a third UAS site (UASp3 at -194). ChIP assays showed that Ino2p:Ino4p bind the PHO5 promoter and that this binding is dependent on Pho4p binding. These results demonstrate that phospholipid biosynthesis is co-ordinated with phosphate utilization via the bHLH proteins.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></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%">Fang, Yilin</style></author><author><style face="normal" font="default" size="100%">Scheibe, Timothy D</style></author><author><style face="normal" font="default" size="100%">Mahadevan, Radhakrishnan</style></author><author><style face="normal" font="default" size="100%">Garg, Srinath</style></author><author><style face="normal" font="default" size="100%">Long, Philip E</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%">Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model.</style></title><secondary-title><style face="normal" font="default" size="100%">J Contam Hydrol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Contam. Hydrol.</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%">Biological Transport</style></keyword><keyword><style  face="normal" font="default" size="100%">Colorado</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Simulation</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%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Uranium</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Mar 25</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">122</style></volume><pages><style face="normal" font="default" size="100%">96-103</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The modeling system is designed in such a way that constraint-based models targeting different microorganisms or competing organism communities can be easily plugged into the system. Constraint-based modeling is very costly given the size of a genome-scale reaction network. To save computation time, a binary tree is traversed to examine the concentration and solution pool generated during the simulation in order to decide whether the constraint-based model should be called. We also show preliminary results from the integrated model including a comparison of the direct and indirect coupling approaches and evaluated the ability of the approach to simulate field experiment.</style></abstract><issue><style face="normal" font="default" size="100%">1-4</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/21172725?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%">Zhuang, Kai</style></author><author><style face="normal" font="default" size="100%">Izallalen, Mounir</style></author><author><style face="normal" font="default" size="100%">Mouser, Paula</style></author><author><style face="normal" font="default" size="100%">Richter, Hanno</style></author><author><style face="normal" font="default" size="100%">Risso, Carla</style></author><author><style face="normal" font="default" size="100%">Mahadevan, Radhakrishnan</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%">Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments.</style></title><secondary-title><style face="normal" font="default" size="100%">ISME J</style></secondary-title><alt-title><style face="normal" font="default" size="100%">ISME J</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Acetates</style></keyword><keyword><style  face="normal" font="default" size="100%">Anaerobiosis</style></keyword><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%">Comamonadaceae</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome</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%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Nitrogen Fixation</style></keyword><keyword><style  face="normal" font="default" size="100%">Quaternary Ammonium Compounds</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Ribosomal, 16S</style></keyword><keyword><style  face="normal" font="default" size="100%">Uranium</style></keyword><keyword><style  face="normal" font="default" size="100%">Water Microbiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Water Pollutants, Radioactive</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">305-16</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The advent of rapid complete genome sequencing, and the potential to capture this information in genome-scale metabolic models, provide the possibility of comprehensively modeling microbial community interactions. For example, Rhodoferax and Geobacter species are acetate-oxidizing Fe(III)-reducers that compete in anoxic subsurface environments and this competition may have an influence on the in situ bioremediation of uranium-contaminated groundwater. Therefore, genome-scale models of Geobacter sulfurreducens and Rhodoferax ferrireducens were used to evaluate how Geobacter and Rhodoferax species might compete under diverse conditions found in a uranium-contaminated aquifer in Rifle, CO. The model predicted that at the low rates of acetate flux expected under natural conditions at the site, Rhodoferax will outcompete Geobacter as long as sufficient ammonium is available. The model also predicted that when high concentrations of acetate are added during in situ bioremediation, Geobacter species would predominate, consistent with field-scale observations. This can be attributed to the higher expected growth yields of Rhodoferax and the ability of Geobacter to fix nitrogen. The modeling predicted relative proportions of Geobacter and Rhodoferax in geochemically distinct zones of the Rifle site that were comparable to those that were previously documented with molecular techniques. The model also predicted that under nitrogen fixation, higher carbon and electron fluxes would be diverted toward respiration rather than biomass formation in Geobacter, providing a potential explanation for enhanced in situ U(VI) reduction in low-ammonium zones. These results show that genome-scale modeling can be a useful tool for predicting microbial interactions in subsurface environments and shows promise for designing bioremediation strategies.</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/20668487?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%">Mahadevan, Radhakrishnan</style></author><author><style face="normal" font="default" size="100%">Palsson, Bernhard Ø</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%">In situ to in silico and back: elucidating the physiology and ecology of Geobacter spp. using genome-scale modelling.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Rev Microbiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat. Rev. Microbiol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computer Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Environment</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%">Models, Biological</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">39-50</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">There is a wide diversity of unexplored metabolism encoded in the genomes of microorganisms that have an important environmental role. Genome-scale metabolic modelling enables the individual reactions that are encoded in annotated genomes to be organized into a coherent whole, which can then be used to predict metabolic fluxes that will optimize cell function under a range of conditions. In this Review, we summarize a series of studies in which genome-scale metabolic modelling of Geobacter spp. has resulted in an in-depth understanding of their central metabolism and ecology. A similar iterative modelling and experimental approach could accelerate elucidation of the physiology and ecology of other microorganisms inhabiting a diversity of environments, and could guide optimization of the practical applications of these species.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/21132020?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%">Morita, Yasu S</style></author><author><style face="normal" font="default" size="100%">Fukuda, Takeshi</style></author><author><style face="normal" font="default" size="100%">Sena, Chubert B C</style></author><author><style face="normal" font="default" size="100%">Yamaryo-Botte, Yoshiki</style></author><author><style face="normal" font="default" size="100%">McConville, Malcolm J</style></author><author><style face="normal" font="default" size="100%">Kinoshita, Taroh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Inositol lipid metabolism in mycobacteria: biosynthesis and regulatory mechanisms.</style></title><secondary-title><style face="normal" font="default" size="100%">Biochim Biophys Acta</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Biochim. Biophys. Acta</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Inositol</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipid Metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipids</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Mycobacterium</style></keyword><keyword><style  face="normal" font="default" size="100%">Phosphatidylinositols</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Jun</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">1810</style></volume><pages><style face="normal" font="default" size="100%">630-41</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: The genus Mycobacterium includes a number of medically important pathogens. The cell walls of these bacteria have many unique features, including the abundance of various inositol lipids, such as phosphatidylinositol mannosides (PIMs), lipomannan (LM), and lipoarabinomannan (LAM). The biosynthesis of these lipids is believed to be prime drug targets, and has been clarified in detail over the past several years.

SCOPE OF REVIEW: Here we summarize our current understanding of the inositol lipid metabolism in mycobacteria. We will highlight unsolved issues and future directions especially in the context of metabolic regulation.

MAJOR CONCLUSIONS: Inositol is a building block of phosphatidylinositol (PI), which is further elaborated to become PIMs, LM and LAM. d-myo-inositol 3-phosphate is an intermediate of the de novo inositol synthesis, but it is also the starting substrate for mycothiol synthesis. Controlling the level of d-myo-inositol 3-phosphate appears to be important for maintaining the steady state levels of mycothiol and inositol lipids. Several additional control mechanisms must exist to control the complex biosynthetic pathways of PI, PIMs, LM and LAM. These may include regulatory proteins such as a lipoprotein LpqW, and spatial separation of enzymes, such as the amphipathic PimA mannosyltransferase and later enzymes in the PIMs/LM biosynthetic pathway. Finally, we discuss mechanisms that underlie control of LM/LAM glycan polymer elongation.

GENERAL SIGNIFICANCE: Mycobacteria have evolved a complex network of inositol metabolism. Clarifying its metabolism will not only provide better understanding of bacterial pathogenesis, but also understanding of the evolution and general functions of inositol lipids in nature.</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/21477636?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%">Sun, Jun</style></author><author><style face="normal" font="default" size="100%">Haveman, Shelley A</style></author><author><style face="normal" font="default" size="100%">Bui, Olivia</style></author><author><style face="normal" font="default" size="100%">Fahland, Tom R</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%">Constraint-based modeling analysis of the metabolism of two Pelobacter species.</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%">Anaerobiosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Citric Acid Cycle</style></keyword><keyword><style  face="normal" font="default" size="100%">Desulfuromonas</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%">Gene Expression Regulation, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword><keyword><style  face="normal" font="default" size="100%">Sulfur</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">174</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Pelobacter species are commonly found in a number of subsurface environments, and are unique members of the Geobacteraceae family. They are phylogenetically intertwined with both Geobacter and Desulfuromonas species. Pelobacter species likely play important roles in the fermentative degradation of unusual organic matters and syntrophic metabolism in the natural environments, and are of interest for applications in bioremediation and microbial fuel cells.

RESULTS: In order to better understand the physiology of Pelobacter species, genome-scale metabolic models for Pelobacter carbinolicus and Pelobacter propionicus were developed. Model development was greatly aided by the availability of models of the closely related Geobacter sulfurreducens and G. metallireducens. The reconstructed P. carbinolicus model contains 741 genes and 708 reactions, whereas the reconstructed P. propionicus model contains 661 genes and 650 reactions. A total of 470 reactions are shared among the two Pelobacter models and the two Geobacter models. The different reactions between the Pelobacter and Geobacter models reflect some unique metabolic capabilities such as fermentative growth for both Pelobacter species. The reconstructed Pelobacter models were validated by simulating published growth conditions including fermentations, hydrogen production in syntrophic co-culture conditions, hydrogen utilization, and Fe(III) reduction. Simulation results matched well with experimental data and indicated the accuracy of the models.

CONCLUSIONS: We have developed genome-scale metabolic models of P. carbinolicus and P. propionicus. These models of Pelobacter metabolism can now be incorporated into the growing repertoire of genome scale models of the Geobacteraceae family to aid in describing the growth and activity of these organisms in anoxic environments and in the study of their roles and interactions in the subsurface microbial community.</style></abstract><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/21182788?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%">Zhao, Jiao</style></author><author><style face="normal" font="default" size="100%">Fang, Yilin</style></author><author><style face="normal" font="default" size="100%">Scheibe, Timothy D</style></author><author><style face="normal" font="default" size="100%">Lovley, Derek R</style></author><author><style face="normal" font="default" size="100%">Mahadevan, R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modeling and sensitivity analysis of electron capacitance for Geobacter in sedimentary environments.</style></title><secondary-title><style face="normal" font="default" size="100%">J Contam Hydrol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Contam. Hydrol.</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%">Electric Capacitance</style></keyword><keyword><style  face="normal" font="default" size="100%">Geobacter</style></keyword><keyword><style  face="normal" font="default" size="100%">Kinetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Uranium</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010 Mar 1</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">112</style></volume><pages><style face="normal" font="default" size="100%">30-44</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In situ stimulation of the metabolic activity of Geobacter species through acetate amendment has been shown to be a promising bioremediation strategy to reduce and immobilize hexavalent uranium [U(VI)] as insoluble U(IV). Although Geobacter species are reducing U(VI), they primarily grow via Fe(III) reduction. Unfortunately, the biogeochemistry and the physiology of simultaneous reduction of multiple metals are still poorly understood. A detailed model is therefore required to better understand the pathways leading to U(VI) and Fe(III) reduction by Geobacter species. Based on recent experimental evidence of temporary electron capacitors in Geobacter we propose a novel kinetic model that physically distinguishes planktonic cells into electron-loaded and -unloaded states. Incorporation of an electron load-unload cycle into the model provides insight into U(VI) reduction efficiency, and elucidates the relationship between U(VI)- and Fe(III)-reducing activity and further explains the correlation of high U(VI) removal with high fractions of planktonic cells in subsurface environments. Global sensitivity analysis was used to determine the level of importance of geochemical and microbial processes controlling Geobacter growth and U(VI) reduction, suggesting that the electron load-unload cycle and the resulting repartition of the microbes between aqueous and attached phases are critical for U(VI) reduction. As compared with conventional Monod modeling approaches without inclusion of the electron capacitance, the new model attempts to incorporate a novel cellular mechanism that has a significant impact on the outcome of in situ bioremediation.</style></abstract><issue><style face="normal" font="default" size="100%">1-4</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19892431?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%">Scheibe, Timothy D</style></author><author><style face="normal" font="default" size="100%">Mahadevan, Radhakrishnan</style></author><author><style face="normal" font="default" size="100%">Fang, Yilin</style></author><author><style face="normal" font="default" size="100%">Garg, Srinath</style></author><author><style face="normal" font="default" size="100%">Long, Philip E</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%">Coupling a genome-scale metabolic model with a reactive transport model to describe in situ uranium bioremediation.</style></title><secondary-title><style face="normal" font="default" size="100%">Microb Biotechnol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Microb Biotechnol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Acetates</style></keyword><keyword><style  face="normal" font="default" size="100%">Biodegradation, Environmental</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological Transport</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%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Uranium</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 Mar</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">274-86</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</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/21261921?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%">Risso, Carla</style></author><author><style face="normal" font="default" size="100%">Sun, Jun</style></author><author><style face="normal" font="default" size="100%">Zhuang, Kai</style></author><author><style face="normal" font="default" size="100%">Mahadevan, Radhakrishnan</style></author><author><style face="normal" font="default" size="100%">DeBoy, Robert</style></author><author><style face="normal" font="default" size="100%">Ismail, Wael</style></author><author><style face="normal" font="default" size="100%">Shrivastava, Susmita</style></author><author><style face="normal" font="default" size="100%">Huot, Heather</style></author><author><style face="normal" font="default" size="100%">Kothari, Sagar</style></author><author><style face="normal" font="default" size="100%">Daugherty, Sean</style></author><author><style face="normal" font="default" size="100%">Bui, Olivia</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%">Methé, Barbara A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III)-reducer Rhodoferax ferrireducens.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Genomics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BMC Genomics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Comamonadaceae</style></keyword><keyword><style  face="normal" font="default" size="100%">Comparative Genomic Hybridization</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Ferric Compounds</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Oxidation-Reduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</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%">10</style></volume><pages><style face="normal" font="default" size="100%">447</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Rhodoferax ferrireducens is a metabolically versatile, Fe(III)-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies.

RESULTS: The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress.

CONCLUSION: This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.</style></abstract><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19772637?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%">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%">Griffith, Kevin L</style></author><author><style face="normal" font="default" size="100%">Fitzpatrick, M Megan</style></author><author><style face="normal" font="default" size="100%">Keen, Edward F</style></author><author><style face="normal" font="default" size="100%">Wolf, Richard E</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Two functions of the C-terminal domain of Escherichia coli Rob: mediating &quot;sequestration-dispersal&quot; as a novel off-on switch for regulating Rob's activity as a transcription activator and preventing degradation of Rob by Lon protease.</style></title><secondary-title><style face="normal" font="default" size="100%">J Mol Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Mol. Biol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Decanoic Acids</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Escherichia coli</style></keyword><keyword><style  face="normal" font="default" size="100%">Escherichia coli Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Reporter</style></keyword><keyword><style  face="normal" font="default" size="100%">Microscopy, Fluorescence</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Protease La</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Structure, Tertiary</style></keyword><keyword><style  face="normal" font="default" size="100%">Pyridines</style></keyword><keyword><style  face="normal" font="default" size="100%">Recombinant Fusion Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Trans-Activators</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription, Genetic</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 May 8</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">388</style></volume><pages><style face="normal" font="default" size="100%">415-30</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In Escherichia coli, Rob activates transcription of the SoxRS/MarA/Rob regulon. Previous work revealed that Rob resides in three to four immunostainable foci, that dipyridyl and bile salts are inducers of its activity, and that inducers bind to Rob's C-terminal domain (CTD). We propose that sequestration inactivates Rob by blocking its access to the transcriptional machinery and that inducers activate Rob by mediating its dispersal, allowing interaction with RNA polymerase. To test &quot;sequestration-dispersal&quot; as a new mechanism for regulating the activity of transcriptional activators, we fused Rob's CTD to SoxS and used indirect immunofluorescence microscopy to determine the effect of inducers on SoxS-Rob's cellular localization. Unlike native SoxS, which is uniformly distributed throughout the cell, SoxS-Rob is sequestered without an inducer, but is rapidly dispersed when cells are treated with an inducer. In this manner, Rob's CTD serves as an anti-sigma factor in regulating the co-sigma-factor-like activity of SoxS when fused to it. Rob's CTD also protects its N-terminus from Lon protease, since Lon's normally rapid degradation of SoxS is blocked in the chimera. Accordingly, Rob's CTD has novel regulatory properties that can be bestowed on another E. coli protein.</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19289129?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%">Segura, Daniel</style></author><author><style face="normal" font="default" size="100%">Mahadevan, Radhakrishnan</style></author><author><style face="normal" font="default" size="100%">Juárez, Katy</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%">Computational and experimental analysis of redundancy in the central metabolism of Geobacter sulfurreducens.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Comput Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS Comput. Biol.</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%">Base Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Geobacter</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Multienzyme Complexes</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</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 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">e36</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</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/18266464?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%">Mahadevan, R</style></author><author><style face="normal" font="default" size="100%">Lovley, D R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The degree of redundancy in metabolic genes is linked to mode of metabolism.</style></title><secondary-title><style face="normal" font="default" size="100%">Biophys J</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Biophys. J.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bacterial Physiological Phenomena</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacterial Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Duplicate</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</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 Feb 15</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">94</style></volume><pages><style face="normal" font="default" size="100%">1216-20</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">An understanding of the factors favoring the maintenance of duplicate genes in microbial genomes is essential for developing models of microbial evolution. A genome-scale flux-balance analysis of the metabolic network of Saccharomyces cerevisiae has suggested that gene duplications primarily provide increased enzyme dosage to enhance metabolic flux because the incidence of gene duplications in essential genes is no higher than that in nonessential genes. Here, we used genome-scale metabolic models to analyze the extent of genetic and biochemical redundancy in prokaryotes that are either specialists, with one major mode of energy generation, or generalists, which have multiple metabolic strategies for conservation of energy. Surprisingly, the results suggest that generalists, such as Escherichia coli and Bacillus subtilis, are similar to the eukaryotic generalist, S. cerevisiae, in having a low percentage (&lt;10%) of essential genes and few duplications of these essential genes, whereas metabolic specialists, such as Geobacter sulfurreducens and Methanosarcina barkeri, have a high percentage (&gt;30%) of essential genes and a high degree of genetic redundancy in these genes compared to nonessential genes. Furthermore, the specialist organisms appear to rely more on gene duplications rather than alternative-but-equivalent metabolic pathways to provide resilience to gene loss. Generalists rely more on alternative pathways. Thus, the concept that the role of gene duplications is to boost enzymatic flux rather than provide metabolic resilience may not be universal. Rather, the degree of gene duplication in microorganisms may be linked to mode of metabolism and environmental niche.</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/17981891?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%">Long, Jarukit Edward</style></author><author><style face="normal" font="default" size="100%">Renzette, Nicholas</style></author><author><style face="normal" font="default" size="100%">Centore, Richard C</style></author><author><style face="normal" font="default" size="100%">Sandler, Steven J</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Differential requirements of two recA mutants for constitutive SOS expression in Escherichia coli K-12.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS One</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS ONE</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Escherichia coli K12</style></keyword><keyword><style  face="normal" font="default" size="100%">Escherichia coli Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Rec A Recombinases</style></keyword><keyword><style  face="normal" font="default" size="100%">SOS Response (Genetics)</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</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">e4100</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Repairing DNA damage begins with its detection and is often followed by elicitation of a cellular response. In E. coli, RecA polymerizes on ssDNA produced after DNA damage and induces the SOS Response. The RecA-DNA filament is an allosteric effector of LexA auto-proteolysis. LexA is the repressor of the SOS Response. Not all RecA-DNA filaments, however, lead to an SOS Response. Certain recA mutants express the SOS Response (recA(C)) in the absence of external DNA damage in log phase cells.

METHODOLOGY/PRINCIPAL FINDINGS: Genetic analysis of two recA(C) mutants was used to determine the mechanism of constitutive SOS (SOS(C)) expression in a population of log phase cells using fluorescence of single cells carrying an SOS reporter system (sulAp-gfp). SOS(C) expression in recA4142 mutants was dependent on its initial level of transcription, recBCD, recFOR, recX, dinI, xthA and the type of medium in which the cells were grown. SOS(C) expression in recA730 mutants was affected by none of the mutations or conditions tested above.

CONCLUSIONS/SIGNIFICANCE: It is concluded that not all recA(C) alleles cause SOS(C) expression by the same mechanism. It is hypothesized that RecA4142 is loaded on to a double-strand end of DNA and that the RecA filament is stabilized by the presence of DinI and destabilized by RecX. RecFOR regulate the activity of RecX to destabilize the RecA filament. RecA730 causes SOS(C) expression by binding to ssDNA in a mechanism yet to be determined.</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19116657?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%">Lovley, Derek R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Extracellular electron transfer: wires, capacitors, iron lungs, and more.</style></title><secondary-title><style face="normal" font="default" size="100%">Geobiology</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Geobiology</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cell Surface Extensions</style></keyword><keyword><style  face="normal" font="default" size="100%">Cytochromes</style></keyword><keyword><style  face="normal" font="default" size="100%">Electron Transport</style></keyword><keyword><style  face="normal" font="default" size="100%">Ferric Compounds</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Shewanella</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 Jun</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">225-31</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/18393985?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><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><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%">Lopper, Matthew</style></author><author><style face="normal" font="default" size="100%">Boonsombat, Ruethairat</style></author><author><style face="normal" font="default" size="100%">Sandler, Steven J</style></author><author><style face="normal" font="default" size="100%">Keck, James L</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A hand-off mechanism for primosome assembly in replication restart.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Cell</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol. Cell</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Binding Sites</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Helicases</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Replication</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA, Single-Stranded</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA-Directed DNA Polymerase</style></keyword><keyword><style  face="normal" font="default" size="100%">Escherichia coli</style></keyword><keyword><style  face="normal" font="default" size="100%">Escherichia coli Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Multienzyme Complexes</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Binding</style></keyword><keyword><style  face="normal" font="default" size="100%">Replication Origin</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 Jun 22</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">26</style></volume><pages><style face="normal" font="default" size="100%">781-93</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Collapsed DNA replication forks must be reactivated through origin-independent reloading of the replication machinery (replisome) to ensure complete duplication of cellular genomes. In E. coli, the PriA-dependent pathway is the major replication restart mechanism and requires primosome proteins PriA, PriB, and DnaT for replisome reloading. However, the molecular mechanisms that regulate origin-independent replisome loading are not fully understood. Here, we demonstrate that assembly of primosome protein complexes represents a key regulatory mechanism, as inherently weak PriA-PriB and PriB-DnaT interactions are strongly stimulated by single-stranded DNA. Furthermore, the binding site on PriB for single-stranded DNA partially overlaps the binding sites for PriA and DnaT, suggesting a dynamic primosome assembly process in which single-stranded DNA is handed off from one primosome protein to another as a repaired replication fork is reactivated. This model helps explain how origin-independent initiation of DNA replication is restricted to repaired replication forks, preventing overreplication of the genome.</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/17588514?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%">Chen, Meng</style></author><author><style face="normal" font="default" size="100%">Lopes, John M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multiple basic helix-loop-helix proteins regulate expression of the ENO1 gene of Saccharomyces cerevisiae.</style></title><secondary-title><style face="normal" font="default" size="100%">Eukaryot Cell</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Eukaryotic Cell</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Basic Helix-Loop-Helix Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">beta-Galactosidase</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromatin Immunoprecipitation</style></keyword><keyword><style  face="normal" font="default" size="100%">E-Box Elements</style></keyword><keyword><style  face="normal" font="default" size="100%">Epistasis, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolution, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Fungal</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Dominant</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Phosphopyruvate Hydratase</style></keyword><keyword><style  face="normal" font="default" size="100%">Promoter Regions, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Recombinant Fusion Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Saccharomyces cerevisiae</style></keyword><keyword><style  face="normal" font="default" size="100%">Saccharomyces cerevisiae Proteins</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 May</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">786-96</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The basic helix-loop-helix (bHLH) eukaryotic transcription factors have the ability to form multiple dimer combinations. This property, together with limited DNA-binding specificity for the E box (CANNTG), makes them ideally suited for combinatorial control of gene expression. We tested the ability of all nine Saccharomyces cerevisiae bHLH proteins to regulate the enolase-encoding gene ENO1. ENO1 was known to be activated by the bHLH protein Sgc1p. Here we show that expression of an ENO1-lacZ reporter was also regulated by the other eight bHLH proteins, namely, Ino2p, Ino4p, Cbf1p, Rtg1p, Rtg3p, Pho4p, Hms1p, and Ygr290wp. ENO1-lacZ expression was also repressed by growth in inositol-choline-containing medium. Epistatic analysis and chromatin immunoprecipitation experiments showed that regulation by Sgc1p, Ino2p, Ino4p, and Cbf1p and repression by inositol-choline required three distal E boxes, E1, E2, and E3. The pattern of bHLH binding to the three E boxes and experiments with two dominant-negative mutant alleles of INO4 and INO2 support the model that bHLH dimer selection affects ENO1-lacZ expression. These results support the general model that bHLH proteins can coordinate different biological pathways via multiple mechanisms.</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/17351075?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%">Mahadevan, R</style></author><author><style face="normal" font="default" size="100%">Bond, D R</style></author><author><style face="normal" font="default" size="100%">Butler, J E</style></author><author><style face="normal" font="default" size="100%">Esteve-Nuñez, A</style></author><author><style face="normal" font="default" size="100%">Coppi, M V</style></author><author><style face="normal" font="default" size="100%">Palsson, B O</style></author><author><style face="normal" font="default" size="100%">Schilling, C H</style></author><author><style face="normal" font="default" size="100%">Lovley, D R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterization of metabolism in the Fe(III)-reducing organism Geobacter sulfurreducens by constraint-based modeling.</style></title><secondary-title><style face="normal" font="default" size="100%">Appl Environ Microbiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Appl. Environ. Microbiol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acids</style></keyword><keyword><style  face="normal" font="default" size="100%">Electron Transport</style></keyword><keyword><style  face="normal" font="default" size="100%">Escherichia coli</style></keyword><keyword><style  face="normal" font="default" size="100%">Fumarates</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%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Oxidation-Reduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Protons</style></keyword><keyword><style  face="normal" font="default" size="100%">Quinones</style></keyword><keyword><style  face="normal" font="default" size="100%">Species Specificity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">72</style></volume><pages><style face="normal" font="default" size="100%">1558-68</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Geobacter sulfurreducens is a well-studied representative of the Geobacteraceae, which play a critical role in organic matter oxidation coupled to Fe(III) reduction, bioremediation of groundwater contaminated with organics or metals, and electricity production from waste organic matter. In order to investigate G. sulfurreducens central metabolism and electron transport, a metabolic model which integrated genome-based predictions with available genetic and physiological data was developed via the constraint-based modeling approach. Evaluation of the rates of proton production and consumption in the extracellular and cytoplasmic compartments revealed that energy conservation with extracellular electron acceptors, such as Fe(III), was limited relative to that associated with intracellular acceptors. This limitation was attributed to lack of cytoplasmic proton consumption during reduction of extracellular electron acceptors. Model-based analysis of the metabolic cost of producing an extracellular electron shuttle to promote electron transfer to insoluble Fe(III) oxides demonstrated why Geobacter species, which do not produce shuttles, have an energetic advantage over shuttle-producing Fe(III) reducers in subsurface environments. In silico analysis also revealed that the metabolic network of G. sulfurreducens could synthesize amino acids more efficiently than that of Escherichia coli due to the presence of a pyruvate-ferredoxin oxidoreductase, which catalyzes synthesis of pyruvate from acetate and carbon dioxide in a single step. In silico phenotypic analysis of deletion mutants demonstrated the capability of the model to explore the flexibility of G. sulfurreducens central metabolism and correctly predict mutant phenotypes. These results demonstrate that iterative modeling coupled with experimentation can accelerate the understanding of the physiology of poorly studied but environmentally relevant organisms and may help optimize their practical applications.</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/16461711?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%">Vriezen, J A C</style></author><author><style face="normal" font="default" size="100%">de Bruijn, F J</style></author><author><style face="normal" font="default" size="100%">Nüsslein, K</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Desiccation responses and survival of Sinorhizobium meliloti USDA 1021 in relation to growth phase, temperature, chloride and sulfate availability.</style></title><secondary-title><style face="normal" font="default" size="100%">Lett Appl Microbiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Lett. Appl. Microbiol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bacteriological Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Chlorides</style></keyword><keyword><style  face="normal" font="default" size="100%">Desiccation</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Sinorhizobium meliloti</style></keyword><keyword><style  face="normal" font="default" size="100%">Sulfur Oxides</style></keyword><keyword><style  face="normal" font="default" size="100%">Temperature</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">42</style></volume><pages><style face="normal" font="default" size="100%">172-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">AIMS: To identify physical and physiological conditions that affect the survival of Sinorhizobium meliloti USDA 1021 during desiccation.

METHODS AND RESULTS: An assay was developed to study desiccation response of S. meliloti USDA 1021 over a range of environmental conditions. We determined the survival during desiccation in relation to (i) matrices and media, (ii) growth phase, (iii) temperature, and (iv) chloride and sulfate availability.

CONCLUSIONS: This study indicates that survival of S. meliloti USDA 1021 during desiccation is enhanced: (i) when cells were dried in the stationary phase, (ii) with increasing drying temperature at an optimum of 37 degrees C, and (iii) during an increase of chloride and sulfate, but not sodium or potassium availability. In addition, we resolved that the best matrix to test survival was nitrocellulose filters.

SIGNIFICANCE AND IMPACT OF THE STUDY: The identification of physical and physiological factors that determine the survival during desiccation of S. meliloti USDA 1021 may aid in (i) the strategic development of improved seed inocula, (ii) the isolation, and (iii) the development of rhizobial strains with improved ability to survive desiccation. Furthermore, this work may provide insights into the survival of rhizobia under drought conditions.</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/16441384?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%">Hancock, Leandria C</style></author><author><style face="normal" font="default" size="100%">Behta, Ryan P</style></author><author><style face="normal" font="default" size="100%">Lopes, John M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genomic analysis of the Opi- phenotype.</style></title><secondary-title><style face="normal" font="default" size="100%">Genetics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genetics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Fungal</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Fungal</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Reporter</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Fungal</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Inositol</style></keyword><keyword><style  face="normal" font="default" size="100%">Lac Operon</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</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%">Phospholipids</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Folding</style></keyword><keyword><style  face="normal" font="default" size="100%">Repressor Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Saccharomyces cerevisiae</style></keyword><keyword><style  face="normal" font="default" size="100%">Saccharomyces cerevisiae Proteins</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006 Jun</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">173</style></volume><pages><style face="normal" font="default" size="100%">621-34</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Most of the phospholipid biosynthetic genes of Saccharomyces cerevisiae are coordinately regulated in response to inositol and choline. Inositol affects the intracellular levels of phosphatidic acid (PA). Opi1p is a repressor of the phospholipid biosynthetic genes and specifically binds PA in the endoplasmic reticulum. In the presence of inositol, PA levels decrease, releasing Opi1p into the nucleus where it represses transcription. The opi1 mutant overproduces and excretes inositol into the growth medium in the absence of inositol and choline (Opi(-) phenotype). To better understand the mechanism of Opi1p repression, the viable yeast deletion set was screened to identify Opi(-) mutants. In total, 89 Opi(-) mutants were identified, of which 7 were previously known to have the Opi(-) phenotype. The Opi(-) mutant collection included genes with roles in phospholipid biosynthesis, transcription, protein processing/synthesis, and protein trafficking. Included in this set were all nonessential components of the NuA4 HAT complex and six proteins in the Rpd3p-Sin3p HDAC complex. It has previously been shown that defects in phosphatidylcholine synthesis (cho2 and opi3) yield the Opi(-) phenotype because of a buildup of PA. However, in this case the Opi(-) phenotype is conditional because PA can be shuttled through a salvage pathway (Kennedy pathway) by adding choline to the growth medium. Seven new mutants present in the Opi(-) collection (fun26, kex1, nup84, tps1, mrpl38, mrpl49, and opi10/yol032w) were also suppressed by choline, suggesting that these affect PC synthesis. Regulation in response to inositol is also coordinated with the unfolded protein response (UPR). Consistent with this, several Opi(-) mutants were found to affect the UPR (yhi9, ede1, and vps74).</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/16582425?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%">Morita, Yasu S</style></author><author><style face="normal" font="default" size="100%">Velasquez, René</style></author><author><style face="normal" font="default" size="100%">Taig, Ellen</style></author><author><style face="normal" font="default" size="100%">Waller, Ross F</style></author><author><style face="normal" font="default" size="100%">Patterson, John H</style></author><author><style face="normal" font="default" size="100%">Tull, Dedreia</style></author><author><style face="normal" font="default" size="100%">Williams, Spencer J</style></author><author><style face="normal" font="default" size="100%">Billman-Jacobe, Helen</style></author><author><style face="normal" font="default" size="100%">McConville, Malcolm J</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Compartmentalization of lipid biosynthesis in mycobacteria.</style></title><secondary-title><style face="normal" font="default" size="100%">J Biol Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Biol. Chem.</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%">Biochemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Membrane</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Wall</style></keyword><keyword><style  face="normal" font="default" size="100%">Hemagglutinins</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipid Metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipids</style></keyword><keyword><style  face="normal" font="default" size="100%">Mannosides</style></keyword><keyword><style  face="normal" font="default" size="100%">Mannosyltransferases</style></keyword><keyword><style  face="normal" font="default" size="100%">Microscopy, Electron</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Mycobacterium smegmatis</style></keyword><keyword><style  face="normal" font="default" size="100%">Phosphatidylethanolamines</style></keyword><keyword><style  face="normal" font="default" size="100%">Phosphatidylinositols</style></keyword><keyword><style  face="normal" font="default" size="100%">Phospholipids</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Structure, Tertiary</style></keyword><keyword><style  face="normal" font="default" size="100%">Subcellular Fractions</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005 Jun 3</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">280</style></volume><pages><style face="normal" font="default" size="100%">21645-52</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The plasma membrane of Mycobacterium sp. is the site of synthesis of several distinct classes of lipids that are either retained in the membrane or exported to the overlying cell envelope. Here, we provide evidence that enzymes involved in the biosynthesis of two major lipid classes, the phosphatidylinositol mannosides (PIMs) and aminophospholipids, are compartmentalized within the plasma membrane. Enzymes involved in the synthesis of early PIM intermediates were localized to a membrane subdomain termed PMf, that was clearly resolved from the cell wall by isopyknic density centrifugation and amplified in rapidly dividing Mycobacterium smegmatis. In contrast, the major pool of apolar PIMs and enzymes involved in polar PIM biosynthesis were localized to a denser fraction that contained both plasma membrane and cell wall markers (PM-CW). Based on the resistance of the PIMs to solvent extraction in live but not lysed cells, we propose that polar PIM biosynthesis occurs in the plasma membrane rather than the cell wall component of the PM-CW. Enzymes involved in phosphatidylethanolamine biosynthesis also displayed a highly polarized distribution between the PMf and PM-CW fractions. The PMf was greatly reduced in non-dividing cells, concomitant with a reduction in the synthesis and steady-state levels of PIMs and amino-phospholipids and the redistribution of PMf marker enzymes to non-PM-CW fractions. The formation of the PMf and recruitment of enzymes to this domain may thus play a role in regulating growth-specific changes in the biosynthesis of membrane and cell wall lipids.</style></abstract><issue><style face="normal" font="default" size="100%">22</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/15805104?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%">Lovley, Derek R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Crystal ball. In silico biology meets in situ phenomenology.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Microbiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Microbiol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bacterial Physiological Phenomena</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">478-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/15816920?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%">Lovley, Derek R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cleaning up with genomics: applying molecular biology to bioremediation.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Rev Microbiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat. Rev. Microbiol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bacteria</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacterial Physiological Phenomena</style></keyword><keyword><style  face="normal" font="default" size="100%">Biodegradation, Environmental</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecology</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Microbiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Fungi</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Vectors</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Fungal</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Biology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2003 Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">35-44</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Bioremediation has the potential to restore contaminated environments inexpensively yet effectively, but a lack of information about the factors controlling the growth and metabolism of microorganisms in polluted environments often limits its implementation. However, rapid advances in the understanding of bioremediation are on the horizon. Researchers now have the ability to culture microorganisms that are important in bioremediation and can evaluate their physiology using a combination of genome-enabled experimental and modelling techniques. In addition, new environmental genomic techniques offer the possibility for similar studies on as-yet-uncultured organisms. Combining models that can predict the activity of microorganisms that are involved in bioremediation with existing geochemical and hydrological models should transform bioremediation from a largely empirical practice into a science.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/15040178?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%">Gardocki, Mary Elizabeth</style></author><author><style face="normal" font="default" size="100%">Lopes, John M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Expression of the yeast PIS1 gene requires multiple regulatory elements including a Rox1p binding site.</style></title><secondary-title><style face="normal" font="default" size="100%">J Biol Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Biol. Chem.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Anoxia</style></keyword><keyword><style  face="normal" font="default" size="100%">Base Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Binding Sites</style></keyword><keyword><style  face="normal" font="default" size="100%">Carbon</style></keyword><keyword><style  face="normal" font="default" size="100%">Chloramphenicol O-Acetyltransferase</style></keyword><keyword><style  face="normal" font="default" size="100%">Choline</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromatography, Thin Layer</style></keyword><keyword><style  face="normal" font="default" size="100%">Conserved Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA, Complementary</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Deletion</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Fungal</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Reporter</style></keyword><keyword><style  face="normal" font="default" size="100%">Inositol</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipid Metabolism</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%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Oxygen</style></keyword><keyword><style  face="normal" font="default" size="100%">Phospholipids</style></keyword><keyword><style  face="normal" font="default" size="100%">Plasmids</style></keyword><keyword><style  face="normal" font="default" size="100%">Promoter Regions, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Binding</style></keyword><keyword><style  face="normal" font="default" size="100%">Repressor Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Saccharomyces cerevisiae</style></keyword><keyword><style  face="normal" font="default" size="100%">Saccharomyces cerevisiae Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Transferases (Other Substituted Phosphate Groups)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2003 Oct 3</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">278</style></volume><pages><style face="normal" font="default" size="100%">38646-52</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The PIS1 gene is required for de novo synthesis of phosphatidylinositol (PI), an essential phospholipid in Saccharomyces cerevisiae. PIS1 gene expression is unusual because it is uncoupled from the other phospholipid biosynthetic genes, which are regulated in response to inositol and choline. Relatively little is known about regulation of transcription of the PIS1 gene. We reported previously that PIS1 transcription is sensitive to carbon source. To further our understanding of the regulation of PIS1 transcription, we carried out a promoter deletion analysis that identified three regions required for PIS1 gene expression (upstream activating sequence (UAS) elements 1-3). Deletion of either UAS1 or UAS2 resulted in an approximately 45% reduction in expression, whereas removal of UAS3 yielded an 84% decrease in expression. A comparison of promoters among several Saccharomyces species shows that these sequences are highly conserved. Curiously, the UAS3 element region (-149 to -138) includes a Rox1p binding site. Rox1p is a repressor of hypoxic genes under aerobic growth conditions. Consistent with this, we have found that expression of a PIS1-cat reporter was repressed under aerobic conditions, and this repression was dependent on both Rox1p and its binding site. Furthermore, PI levels were elevated under anaerobic conditions. This is the first evidence that PI levels are affected by regulation of PIS1 transcription.</style></abstract><issue><style face="normal" font="default" size="100%">40</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/12890676?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%">Sandler, S J</style></author><author><style face="normal" font="default" size="100%">McCool, J D</style></author><author><style face="normal" font="default" size="100%">Do, T T</style></author><author><style face="normal" font="default" size="100%">Johansen, R U</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PriA mutations that affect PriA-PriC function during replication restart.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Microbiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol. Microbiol.</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%">Bacteriophage mu</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Division</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Replication</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Escherichia coli</style></keyword><keyword><style  face="normal" font="default" size="100%">Escherichia coli Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Lethal</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation, Missense</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Replication Protein A</style></keyword><keyword><style  face="normal" font="default" size="100%">SOS Response (Genetics)</style></keyword><keyword><style  face="normal" font="default" size="100%">Ultraviolet Rays</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2001 Aug</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">41</style></volume><pages><style face="normal" font="default" size="100%">697-704</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In Escherichia coli, repair and restart of collapsed replication forks is thought to be essential for cell growth. The replication restart proteins, PriA, PriB, PriC, DnaB, DnaC, DnaG, DnaT and Rep, form redundant pathways that recognize repaired replication forks and restart them. Recognition, modulation of specific DNA structures and loading of the replicative helicase by the replication restart proteins, is likely to be important for replication restart. It has been hypothesized that PriB and PriC function with PriA in genetically separate and redundant PriA-PriB and PriA-PriC pathways. In this study, the del(priB)302 or priC303:kan mutations were used to isolate the PriA-PriB and PriA-PriC pathways genetically so that the effects of three priA missense mutations, priA300 (K230R), priA301 (C479Y) and priA306 (L557P), on these pathways could be assessed. In a wild-type background, the three priA mutations had little, if any, effect on the phenotypes of UV resistance, basal levels of SOS expression and cell viability. In the priB mutant, priA300 and priA301 caused dramatic negative changes in the three phenotypes listed above (and others), whereas the third priA mutant allele, priA306, showed very little negative effect. In the priC mutant, all three priA mutations behaved similarly, producing little, if any, changes in phenotypes. We conclude that priA300 and priA301 mostly affect the PriA-PriC pathway and do so more than priA306. We suggest that PriA's helicase activity is important for the PriA-PriC pathway of replication restart.</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/11532137?dopt=Abstract</style></custom1></record></records></xml>