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Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation.
Hartman, Hassan B; Fell, David A; Rossell, Sergio; Jensen, Peter Ruhdal; Woodward, Martin J; Thorndahl, Lotte; Jelsbak, Lotte; Olsen, John Elmerdahl; Raghunathan, Anu; Daefler, Simon; Poolman, Mark G.
Afiliación
  • Hartman HB; Department of Medical and Biological Sciences, Oxford Brookes University, Gipsy Lane, Headington, Oxford OX3 OBP, UK.
  • Fell DA; Department of Medical and Biological Sciences, Oxford Brookes University, Gipsy Lane, Headington, Oxford OX3 OBP, UK.
  • Rossell S; Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark.
  • Jensen PR; Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark.
  • Woodward MJ; Department of Food and Nutritional Sciences, University of Reading, Reading, UK.
  • Thorndahl L; Department of Veterinary Disease Biology, University of Copenhagen, Copenhagen, Denmark.
  • Jelsbak L; Department of Veterinary Disease Biology, University of Copenhagen, Copenhagen, Denmark.
  • Olsen JE; Department of Veterinary Disease Biology, University of Copenhagen, Copenhagen, Denmark.
  • Raghunathan A; Department of Infectious Diseases, Mount Sinai School of Medicine, New York, NY, USA.
  • Daefler S; Department of Infectious Diseases, Mount Sinai School of Medicine, New York, NY, USA.
  • Poolman MG; Department of Medical and Biological Sciences, Oxford Brookes University, Gipsy Lane, Headington, Oxford OX3 OBP, UK.
Microbiology (Reading) ; 160(Pt 6): 1252-1266, 2014 Jun.
Article en En | MEDLINE | ID: mdl-24777662
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Salmonella typhimurium / Redes y Vías Metabólicas Tipo de estudio: Diagnostic_studies Idioma: En Revista: Microbiology (Reading) Asunto de la revista: MICROBIOLOGIA Año: 2014 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Salmonella typhimurium / Redes y Vías Metabólicas Tipo de estudio: Diagnostic_studies Idioma: En Revista: Microbiology (Reading) Asunto de la revista: MICROBIOLOGIA Año: 2014 Tipo del documento: Article País de afiliación: Reino Unido