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dc.contributor.authorWodke, Judith A H
dc.contributor.authorPuchałka, Jacek
dc.contributor.authorLluch-Senar, Maria
dc.contributor.authorMarcos, Josep
dc.contributor.authorYus, Eva
dc.contributor.authorGodinho, Miguel
dc.contributor.authorGutiérrez-Gallego, Ricardo
dc.contributor.authordos Santos, Vitor A P Martins
dc.contributor.authorSerrano, Luis
dc.contributor.authorKlipp, Edda
dc.contributor.authorMaier, Tobias
dc.date.accessioned2013-10-08T13:50:36Z
dc.date.available2013-10-08T13:50:36Z
dc.date.issued2013
dc.identifier.citationDissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling. 2013, 9:653 Mol. Syst. Biol.en
dc.identifier.issn1744-4292
dc.identifier.pmid23549481
dc.identifier.doi10.1038/msb.2013.6
dc.identifier.urihttp://hdl.handle.net/10033/302985
dc.description.abstractMycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint-based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time-dependent changes, albeit using a static model. By performing an in silico knock-out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms.
dc.language.isoenen
dc.rightsArchived with thanks to Molecular systems biologyen
dc.subject.meshComputer Simulationen
dc.subject.meshEnergy Metabolismen
dc.subject.meshGene Expression Regulation, Bacterialen
dc.subject.meshGenome, Bacterialen
dc.subject.meshMetabolic Networks and Pathwaysen
dc.subject.meshModels, Biologicalen
dc.subject.meshMutationen
dc.subject.meshMycoplasma pneumoniaeen
dc.titleDissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling.en
dc.typeArticleen
dc.contributor.departmentEMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain.en
dc.identifier.journalMolecular systems biologyen
refterms.dateFOA2018-06-13T07:35:14Z
html.description.abstractMycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint-based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time-dependent changes, albeit using a static model. By performing an in silico knock-out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms.


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