Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation

Hassan B. Hartman, David A. Fell, Sergio Rossell, Peter Ruhdal Jensen, Martin J. Woodward, Lotte Thorndahl, Lotte Jelsbak, John Elmerdahl Olsen, Anu Raghunathan, Simon Daefler, Mark G. Poolman

    Research output: Contribution to journalJournal articleResearchpeer-review

    993 Downloads (Pure)

    Abstract

    Salmonella enterica sv. Typhimurium is an established model organism for Gram-negative, intracellular pathogens. Owing to the rapid spread of resistance to antibiotics among this group of pathogens, new approaches to identify suitable target proteins are required. Based on the genome sequence of S. Typhimurium and associated databases, a genome-scale metabolic model was constructed. Output was based on an experimental determination of the biomass of Salmonella when growing in glucose minimal medium. Linear programming was used to simulate variations in the energy demand while growing in glucose minimal medium. By grouping reactions with similar flux responses, a subnetwork of 34 reactions responding to this variation was identified (the catabolic core). This network was used to identify sets of one and two reactions that when removed from the genome-scale model interfered with energy and biomass generation. Eleven such sets were found to be essential for the production of biomass precursors. Experimental investigation of seven of these showed that knockouts of the associated genes resulted in attenuated growth for four pairs of reactions, whilst three single reactions were shown to be essential for growth.
    Original languageEnglish
    JournalMicrobiology (United Kingdom)
    Volume160
    Issue number6
    Pages (from-to)1252-1266
    ISSN1350-0872
    DOIs
    Publication statusPublished - 2014

    Bibliographical note

    © 2014 The Authors

    Keywords

    • Physiology and Biochemistry

    Fingerprint

    Dive into the research topics of 'Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation'. Together they form a unique fingerprint.

    Cite this