Skip to main content
Journal cover image

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

Publication ,  Journal Article
Li, G; Cao, H; Xu, Y
Published in: Briefings in bioinformatics
July 2019

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.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Briefings in bioinformatics

DOI

EISSN

1477-4054

ISSN

1467-5463

Publication Date

July 2019

Volume

20

Issue

4

Start / End Page

1590 / 1603

Related Subject Headings

  • Models, Biological
  • Microbiological Phenomena
  • Metabolic Networks and Pathways
  • Kinetics
  • Genome, Microbial
  • Gene Expression Profiling
  • Escherichia coli K12
  • Computational Biology
  • Cluster Analysis
  • Bioinformatics
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Li, G., Cao, H., & Xu, Y. (2019). Structural and functional analyses of microbial metabolic networks reveal novel insights into genome-scale metabolic fluxes. Briefings in Bioinformatics, 20(4), 1590–1603. https://doi.org/10.1093/bib/bby022
Li, Gaoyang, Huansheng Cao, and Ying Xu. “Structural and functional analyses of microbial metabolic networks reveal novel insights into genome-scale metabolic fluxes.Briefings in Bioinformatics 20, no. 4 (July 2019): 1590–1603. https://doi.org/10.1093/bib/bby022.
Li, Gaoyang, et al. “Structural and functional analyses of microbial metabolic networks reveal novel insights into genome-scale metabolic fluxes.Briefings in Bioinformatics, vol. 20, no. 4, July 2019, pp. 1590–603. Epmc, doi:10.1093/bib/bby022.
Journal cover image

Published In

Briefings in bioinformatics

DOI

EISSN

1477-4054

ISSN

1467-5463

Publication Date

July 2019

Volume

20

Issue

4

Start / End Page

1590 / 1603

Related Subject Headings

  • Models, Biological
  • Microbiological Phenomena
  • Metabolic Networks and Pathways
  • Kinetics
  • Genome, Microbial
  • Gene Expression Profiling
  • Escherichia coli K12
  • Computational Biology
  • Cluster Analysis
  • Bioinformatics