%0 Journal Article %1 FEB4:FEB412208 %A Dannheim, Henning %A Will, Sabine E. %A Schomburg, Dietmar %A Neumann-Schaal, Meina %D 2017 %J FEBS Open Bio %K Clostridioides difficile genomics myown polysaccharide secretion %N 4 %P 602--615 %R 10.1002/2211-5463.12208 %T Clostridioides difficile 630Δerm in silico and in vivo – quantitative growth and extensive polysaccharide secretion %U http://dx.doi.org/10.1002/2211-5463.12208 %V 7 %X Antibiotic-associated infections with Clostridioides difficile are a severe and often lethal risk for hospitalized patients, and can also affect populations without these classical risk factors. For a rational design of therapeutical concepts, a better knowledge of the metabolism of the pathogen is crucial. Metabolic modeling can provide a simulation of quantitative growth and usage of metabolic pathways, leading to a deeper understanding of the organism. Here, we present an elaborate genome-scale metabolic model of C. difficile 630Δerm. The model iHD992 includes experimentally determined product and substrate uptake rates and is able to simulate the energy metabolism and quantitative growth of C. difficile. Dynamic flux balance analysis was used for time-resolved simulations of the quantitative growth in two different media. The model predicts oxidative Stickland reactions and glucose degradation as main sources of energy, while the resulting reduction potential is mostly used for acetogenesis via the Wood–Ljungdahl pathway. Initial modeling experiments did not reproduce the observed growth behavior before the production of large quantities of a previously unknown polysaccharide was detected. Combined genome analysis and laboratory experiments indicated that the polysaccharide is an acetylated glucose polymer. Time-resolved simulations showed that polysaccharide secretion was coupled to growth even during unstable glucose uptake in minimal medium. This is accomplished by metabolic shifts between active glycolysis and gluconeogenesis which were also observed in laboratory experiments.

@article{FEB4:FEB412208, abstract = {Antibiotic-associated infections with Clostridioides difficile are a severe and often lethal risk for hospitalized patients, and can also affect populations without these classical risk factors. For a rational design of therapeutical concepts, a better knowledge of the metabolism of the pathogen is crucial. Metabolic modeling can provide a simulation of quantitative growth and usage of metabolic pathways, leading to a deeper understanding of the organism. Here, we present an elaborate genome-scale metabolic model of C. difficile 630Δerm. The model iHD992 includes experimentally determined product and substrate uptake rates and is able to simulate the energy metabolism and quantitative growth of C. difficile. Dynamic flux balance analysis was used for time-resolved simulations of the quantitative growth in two different media. The model predicts oxidative Stickland reactions and glucose degradation as main sources of energy, while the resulting reduction potential is mostly used for acetogenesis via the Wood–Ljungdahl pathway. Initial modeling experiments did not reproduce the observed growth behavior before the production of large quantities of a previously unknown polysaccharide was detected. Combined genome analysis and laboratory experiments indicated that the polysaccharide is an acetylated glucose polymer. Time-resolved simulations showed that polysaccharide secretion was coupled to growth even during unstable glucose uptake in minimal medium. This is accomplished by metabolic shifts between active glycolysis and gluconeogenesis which were also observed in laboratory experiments.}, added-at = {2017-07-27T09:26:01.000+0200}, author = {Dannheim, Henning and Will, Sabine E. and Schomburg, Dietmar and Neumann-Schaal, Meina}, biburl = {https://www.bibsonomy.org/bibtex/23adb1ee12b6a4288ad4543e9ea6ba38c/brenda_bs}, doi = {10.1002/2211-5463.12208}, interhash = {5e28eb2171859cab43cf83dab0593ff0}, intrahash = {3adb1ee12b6a4288ad4543e9ea6ba38c}, issn = {2211-5463}, journal = {FEBS Open Bio}, keywords = {Clostridioides difficile genomics myown polysaccharide secretion}, number = 4, pages = {602--615}, timestamp = {2017-10-30T09:31:45.000+0100}, title = {Clostridioides difficile 630Δerm in silico and in vivo – quantitative growth and extensive polysaccharide secretion}, url = {http://dx.doi.org/10.1002/2211-5463.12208}, volume = 7, year = 2017 }