<?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%">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%">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%">Nagarajan, Harish</style></author><author><style face="normal" font="default" size="100%">Butler, Jessica E</style></author><author><style face="normal" font="default" size="100%">Klimes, Anna</style></author><author><style face="normal" font="default" size="100%">Qiu, Yu</style></author><author><style face="normal" font="default" size="100%">Zengler, Karsten</style></author><author><style face="normal" font="default" size="100%">Ward, Joy</style></author><author><style face="normal" font="default" size="100%">Young, Nelson D</style></author><author><style face="normal" font="default" size="100%">Methé, Barbara A</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%">Barrett, Christian L</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">De Novo assembly of the complete genome of an enhanced electricity-producing variant of Geobacter sulfurreducens using only short reads.</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%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Electricity</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%">Polymerase Chain Reaction</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%">5</style></volume><pages><style face="normal" font="default" size="100%">e10922</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">State-of-the-art DNA sequencing technologies are transforming the life sciences due to their ability to generate nucleotide sequence information with a speed and quantity that is unapproachable with traditional Sanger sequencing. Genome sequencing is a principal application of this technology, where the ultimate goal is the full and complete sequence of the organism of interest. Due to the nature of the raw data produced by these technologies, a full genomic sequence attained without the aid of Sanger sequencing has yet to be demonstrated.We have successfully developed a four-phase strategy for using only next-generation sequencing technologies (Illumina and 454) to assemble a complete microbial genome de novo. We applied this approach to completely assemble the 3.7 Mb genome of a rare Geobacter variant (KN400) that is capable of unprecedented current production at an electrode. Two key components of our strategy enabled us to achieve this result. First, we integrated the two data types early in the process to maximally leverage their complementary characteristics. And second, we used the output of different short read assembly programs in such a way so as to leverage the complementary nature of their different underlying algorithms or of their different implementations of the same underlying algorithm.The significance of our result is that it demonstrates a general approach for maximizing the efficiency and success of genome assembly projects as new sequencing technologies and new assembly algorithms are introduced. The general approach is a meta strategy, wherein sequencing data are integrated as early as possible and in particular ways and wherein multiple assembly algorithms are judiciously applied such that the deficiencies in one are complemented by another.</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/20544019?dopt=Abstract</style></custom1></record></records></xml>