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    Genome-Scale Metabolic Modeling Reveals Metabolic Alterations of Multidrug-Resistant Acinetobacter baumannii in a Murine Bloodstream Infection Model

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    Author
    Zhao, J; Zhu, Y; Han, J; Lin, Y-W; Aichem, M; Wang, J; Chen, K; Velkov, T; Schreiber, F; Li, J
    Date
    2020-11-01
    Source Title
    Microorganisms
    Publisher
    MDPI
    University of Melbourne Author/s
    Velkov, Tony
    Affiliation
    Pharmacology and Therapeutics
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Zhao, 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.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/253001
    DOI
    10.3390/microorganisms8111793
    Open Access at PMC
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696501
    Abstract
    Multidrug-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.

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