@article {3132, title = {Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii.}, journal = {Microb Cell Fact}, volume = {12}, year = {2013}, month = {2013 Nov 25}, pages = {118}, abstract = {

BACKGROUND: The metabolic capabilities of acetogens to ferment a wide range of sugars, to grow autotrophically on H2/CO2, and more importantly on synthesis gas (H2/CO/CO2) make them very attractive candidates as production hosts for biofuels and biocommodities. Acetogenic metabolism is considered one of the earliest modes of bacterial metabolism. A thorough understanding of various factors governing the metabolism, in particular energy conservation mechanisms, is critical for metabolic engineering of acetogens for targeted production of desired chemicals.

RESULTS: Here, we present the genome-scale metabolic network of Clostridium ljungdahlii, the first such model for an acetogen. This genome-scale model (iHN637) consisting of 637 genes, 785 reactions, and 698 metabolites captures all the major central metabolic and biosynthetic pathways, in particular pathways involved in carbon fixation and energy conservation. A combination of metabolic modeling, with physiological and transcriptomic data provided insights into autotrophic metabolism as well as aided the characterization of a nitrate reduction pathway in C. ljungdahlii. Analysis of the iHN637 metabolic model revealed that flavin based electron bifurcation played a key role in energy conservation during autotrophic growth and helped identify genes for some of the critical steps in this mechanism.

CONCLUSIONS: iHN637 represents a predictive model that recapitulates experimental data, and provides valuable insights into the metabolic response of C. ljungdahlii to genetic perturbations under various growth conditions. Thus, the model will be instrumental in guiding metabolic engineering of C. ljungdahlii for the industrial production of biocommodities and biofuels.

}, keywords = {Acetates, Biofuels, Clostridium, Genome, Metabolic Engineering, Metabolic Networks and Pathways}, issn = {1475-2859}, doi = {10.1186/1475-2859-12-118}, author = {Nagarajan, Harish and Sahin, Merve and Nogales, Juan and Latif, Haythem and Lovley, Derek R and Ebrahim, Ali and Zengler, Karsten} } @article {438, title = {Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments.}, journal = {ISME J}, volume = {5}, year = {2011}, month = {2011 Feb}, pages = {305-16}, abstract = {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.}, keywords = {Acetates, Anaerobiosis, Biodegradation, Environmental, Biomass, Comamonadaceae, Genome, Genome, Bacterial, Geobacter, Models, Biological, Nitrogen Fixation, Quaternary Ammonium Compounds, RNA, Ribosomal, 16S, Uranium, Water Microbiology, Water Pollutants, Radioactive}, issn = {1751-7370}, doi = {10.1038/ismej.2010.117}, author = {Zhuang, Kai and Izallalen, Mounir and Mouser, Paula and Richter, Hanno and Risso, Carla and Mahadevan, Radhakrishnan and Lovley, Derek R} }