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dc.contributor.authorZhao, J
dc.contributor.authorZhu, Y
dc.contributor.authorHan, J
dc.contributor.authorLin, Y-W
dc.contributor.authorAichem, M
dc.contributor.authorWang, J
dc.contributor.authorChen, K
dc.contributor.authorVelkov, T
dc.contributor.authorSchreiber, F
dc.contributor.authorLi, J
dc.date.accessioned2020-12-09T22:33:38Z
dc.date.available2020-12-09T22:33:38Z
dc.date.issued2020-11-01
dc.identifierpii: microorganisms8111793
dc.identifier.citationZhao, J., Zhu, Y., Han, J., Lin, Y. -W., Aichem, M., Wang, J., Chen, K., Velkov, T., Schreiber, F. & Li, J. (2020). Genome-Scale Metabolic Modeling Reveals Metabolic Alterations of Multidrug-Resistant Acinetobacter baumannii in a Murine Bloodstream Infection Model. MICROORGANISMS, 8 (11), https://doi.org/10.3390/microorganisms8111793.
dc.identifier.issn2076-2607
dc.identifier.urihttp://hdl.handle.net/11343/253001
dc.description.abstractMultidrug-resistant (MDR) Acinetobacter baumannii is a critical threat to human health globally. We constructed a genome-scale metabolic model iAB5075 for the hypervirulent, MDR A. baumannii strain AB5075. Predictions of nutrient utilization and gene essentiality were validated using Biolog assay and a transposon mutant library. In vivo transcriptomics data were integrated with iAB5075 to elucidate bacterial metabolic responses to the host environment. iAB5075 contains 1530 metabolites, 2229 reactions, and 1015 genes, and demonstrated high accuracies in predicting nutrient utilization and gene essentiality. At 4 h post-infection, a total of 146 metabolic fluxes were increased and 52 were decreased compared to 2 h post-infection; these included enhanced fluxes through peptidoglycan and lipopolysaccharide biosynthesis, tricarboxylic cycle, gluconeogenesis, nucleotide and fatty acid biosynthesis, and altered fluxes in amino acid metabolism. These flux changes indicate that the induced central metabolism, energy production, and cell membrane biogenesis played key roles in establishing and enhancing A. baumannii bloodstream infection. This study is the first to employ genome-scale metabolic modeling to investigate A. baumannii infection in vivo. Our findings provide important mechanistic insights into the adaption of A. baumannii to the host environment and thus will contribute to the development of new therapeutic agents against this problematic pathogen.
dc.languageEnglish
dc.publisherMDPI
dc.titleGenome-Scale Metabolic Modeling Reveals Metabolic Alterations of Multidrug-Resistant Acinetobacter baumannii in a Murine Bloodstream Infection Model
dc.typeJournal Article
dc.identifier.doi10.3390/microorganisms8111793
melbourne.affiliation.departmentPharmacology and Therapeutics
melbourne.source.titleMicroorganisms
melbourne.source.volume8
melbourne.source.issue11
melbourne.source.pages1-18
dc.rights.licenseCC BY
melbourne.elementsid1480217
melbourne.openaccess.pmchttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696501
melbourne.contributor.authorVelkov, Tony
dc.identifier.eissn2076-2607
melbourne.accessrightsOpen Access


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