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Robustness Analysis of the Escherichiacoli Metabolic Network

Authors

  • Jeremy S. Edwards,

    1. Department of Bioengineering, University of California-San Diego, La Jolla, California 92093–0412
    Current affiliation:
    1. Department of Genetics, Harvard Medical School, Boston, MA 02115
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  • Bernhard O. Palsson

    Corresponding author
    1. Department of Bioengineering, University of California-San Diego, La Jolla, California 92093–0412
    • Department of Bioengineering, University of California-San Diego, La Jolla, California 92093–0412. Ph: (619) 534–5668. Fax: (619) 822–0240
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Abstract

Genomic, biochemical, and strain-specific data can be assembled to define an in silico representation of the metabolic network for a select group of single cellular organisms. Flux-balance analysis and phenotypic phase planes derived therefrom have been developed and applied to analyze the metabolic capabilities and characteristics of Escherichia coli K-12. These analyses have shown the existence of seven essential reactions in the central metabolic pathways (glycolysis, pentose phosphate pathway, tricarboxylic acid cycle) for the growth in glucose minimal media. The corresponding seven gene products can be grouped into three categories: (1) pentose phosphate pathway genes, (2) three-carbon glycolytic genes, and (3) tricarboxylic acid cycle genes. Here we develop a procedure that calculates the sensitivity of optimal cellular growth to altered flux levels of these essential gene products. The results indicate that the E. coli metabolic network is robust with respect to the flux levels of these enzymes. The metabolic flux in the transketolase and the tricarboxylic acid cycle reactions can be reduced to 15% and 19%, respectively, of the optimal value without significantly influencing the optimal growth flux. The metabolic network also exhibited robustness with respect to the ribose-5-phosphate isomerase, and the ribose-5-phosephate isomerase flux was reduced to 28% of the optimal value without significantly effecting the optimal growth flux. The metabolic network exhibited limited robustness to the three-carbon glycolytic fluxes both increased and decreased. The development presented another dimension to the use of FBA to study the capabilities of metabolic networks.

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