Hartman, Hassan B.7; Fell, David A.7; Rossell, Sergio1; Jensen, Peter Ruhdal2; Woodward, Martin J.8; Thorndahl, Lotte5; Jelsbak, Lotte5; Elmerdahl Olsen, John5; Raghunathan, Anu6; Daefler, Simon6; Poolman, Mark G.7
1 Department of Systems Biology, Technical University of Denmark2 Systems Biotechnology, Department of Systems Biology, Technical University of Denmark3 Oxford Brookes University4 University of Reading5 University of Copenhagen6 Mount Sinai School of Medicine7 Oxford Brookes University8 University of Reading
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.
Microbiology, 2014, Vol 160, Issue 6, p. 1252-1266