Metabolite essentiality elucidates robustness of Escherichia coli metabolism

Pan Jun Kim, Dong Yup Lee, Tae Yong Kim, Kwang Ho Lee, Hawoong Jeong*, Sang Yup Lee*, Sunwon Park

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

105 Citations (Scopus)

Abstract

Complex biological systems are very robust to genetic and environmental changes at all levels of organization. Many biological functions of Escherichia coli metabolism can be sustained against single-gene or even multiple-gene mutations by using redundant or alternative pathways. Thus, only a limited number of genes have been identified to be lethal to the cell. In this regard, the reactioncentric gene deletion study has a limitation in understanding the metabolic robustness. Here, we report the use of flux-sum, which is the summation of all incoming or outgoing fluxes around a particular metabolite under pseudo-steady state conditions, as a good conserved property for elucidating such robustness of E. coli from the metabolite point of view. The functional behavior, as well as the structural and evolutionary properties of metabolites essential to the cell survival, was investigated by means of a constraints-based flux analysis under perturbed conditions. The essential metabolites are capable of maintaining a steady flux-sum even against severe perturbation by actively redistributing the relevant fluxes. Disrupting the flux-sum maintenance was found to suppress cell growth. This approach of analyzing metabolite essentiality provides insight into cellular robustness and concomitant fragility, which can be used for several applications, including the development of new drugs for treating pathogens.

Original languageEnglish
Pages (from-to)13638-13642
Number of pages5
JournalProceedings of the National Academy of Sciences of the United States of America
Volume104
Issue number34
DOIs
Publication statusPublished - 21 Aug 2007

Scopus Subject Areas

  • General

User-Defined Keywords

  • Cellular robustness
  • Flux-sum
  • Metabolic networks

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