Structural and functional analyses of microbial metabolic networks reveal novel insights into genome-scale metabolic fluxes

Gaoyang Li, Huansheng Cao, Ying Xu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


We present here an integrated analysis of structures and functions of genome-scale metabolic networks of 17 microorganisms. Our structural analyses of these networks revealed that the node degree of each network, represented as a (simplified) reaction network, follows a power-law distribution, and the clustering coefficient of each network has a positive correlation with the corresponding node degree. Together, these properties imply that each network has exactly one large and densely connected subnetwork or core. Further analyses revealed that each network consists of three functionally distinct subnetworks: (i) a core, consisting of a large number of directed reaction cycles of enzymes for interconversions among intermediate metabolites; (ii) a catabolic module, with a largely layered structure consisting of mostly catabolic enzymes; (iii) an anabolic module with a similar structure consisting of virtually all anabolic genes; and (iv) the three subnetworks cover on average ∼56, ∼31 and ∼13% of a network's nodes across the 17 networks, respectively. Functional analyses suggest: (1) cellular metabolic fluxes generally go from the catabolic module to the core for substantial interconversions, then the flux directions to anabolic module appear to be determined by input nutrient levels as well as a set of precursors needed for macromolecule syntheses; and (2) enzymes in each subnetwork have characteristic ranges of kinetic parameters, suggesting optimized metabolic and regulatory relationships among the three subnetworks.

Original languageEnglish (US)
Pages (from-to)1590-1603
Number of pages14
JournalBriefings in bioinformatics
Issue number4
StatePublished - Mar 27 2018


  • clustering coefficient distribution
  • flux balance analysis
  • functional modularity
  • metabolic network
  • network organizing principle
  • scale-free network

ASJC Scopus subject areas

  • Information Systems
  • Molecular Biology


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