Skip to main content
Log in

Inferring Minimal Feasible Metabolic Networks of Escherichia coli

  • Published:
Applied Biochemistry and Biotechnology Aims and scope Submit manuscript

Abstract

Since the organism contains many redundant reactions, the minimal feasible metabolic network that contains the basic growth function is not the collection of reactions that associate the essential genes. To identify minimal metabolic reaction set is a challenging work in theoretical approach. A new method is presented here to identify the smallest required reaction set of growth-sustaining metabolic networks. The content and number of the minimal reactions for growth are variable in different random processes. Though the different carbon sources also vary the content of the reactions in the minimal metabolic networks, most essential reactions locate in the same metabolic subsystems, such as cofactor and prosthetic group biosynthesis, cell envelope biosynthesis, and membrane lipid metabolism.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N., & Barabási, A. L. (2000). The large-scale organization of metabolic networks. Nature, 407, 651–654. doi:10.1038/35036627.

    Article  CAS  Google Scholar 

  2. Sharan, R., & Ideker, T. (2006). Modeling cellular machinery through biological network comparison. Nature Biotechnology, 24, 427–433. doi:10.1038/nbt1196.

    Article  CAS  Google Scholar 

  3. Becker, D., Selbach, M., Rollenhagen, C., Ballmaier, M., Meyer, T. F., Mann, M., et al. (2006). Robust Salmonella metabolism limits possibilities for new antimicrobials. Nature, 440, 303–307. doi:10.1038/nature04616.

    Article  CAS  Google Scholar 

  4. Schuster, S., Fell, D. A., & Dandekar, T. (2000). A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nature Biotechnology, 18, 326–332. doi:10.1038/73786.

    Article  CAS  Google Scholar 

  5. Burgard, A. P., Vaidyaraman, S., & Maranas, C. D. (2001). Minimal reaction sets for Escherichia coli metabolism under different growth requirements and uptake environments. Biotechnology Progress, 17, 791–797. doi:10.1021/bp0100880.

    Article  CAS  Google Scholar 

  6. Pal, C., Papp, B., Lercher, M. J., Csermely, P., Oliver, S. G., & Hurst, L. D. (2006). Chance and necessity in the evolution of minimal metabolic networks. Nature, 440, 667–670. doi:10.1038/nature04568.

    Article  CAS  Google Scholar 

  7. Kauffman, K. J., Prakash, P., & Edwards, J. S. (2003). Advances in flux balance analysis. Current Opinion in Biotechnology, 14, 491–496. doi:10.1016/j.copbio.2003.08.001.

    Article  CAS  Google Scholar 

  8. Lee, J. M., Gianchandani, E. P., & Papin, J. A. (2006). Flux balance analysis in the era of metabolomics. Briefings in Bioinformatics, 7, 140–150. doi:10.1093/bib/bbl007.

    Article  Google Scholar 

  9. Edwards, J. S., & Palsson, B. O. (2000). The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities. Proceedings of the National Academy of Sciences of the United States of America, 97, 5528–5533. doi:10.1073/pnas.97.10.5528.

    Article  CAS  Google Scholar 

  10. Reed, J. L., Vo, T. D., Schilling, C. H., & Palsson, B. O. (2003). An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biology, 4, R54. doi:10.1186/gb-2003–4–9-r54.

    Article  Google Scholar 

  11. Feist, A. M., & Palsson, B. O. (2008). The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli. Nature Biotechnology, 26, 659–667. doi:10.1038/nbt1401.

    Article  CAS  Google Scholar 

  12. Fong, S. S., & Palsson, B. O. (2004). Metabolic gene-deletion strains of Escherichia coli evolve to computationally predicted growth phenotypes. Nature Genetics, 36, 1056–1058. doi:10.1038/ng1432.

    Article  CAS  Google Scholar 

  13. Fischer, E., & Sauer, U. (2005). Large-scale in vivo flux analysis shows rigidity and suboptimal performance of Bacillus subtilis metabolism. Nature Genetics, 37, 636–640. doi:10.1038/ng1555.

    Article  CAS  Google Scholar 

  14. Schuetz, R., Kuepfer, L., & Sauer, U. (2007). Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli. Molecular Systems Biology, 3, 119. doi:10.1038/msb4100162.

    Article  Google Scholar 

  15. Nielsen, J. (2007). Principles of optimal metabolic network operation. Molecular Systems Biology, 3, 126. doi:10.1038/msb4100169.

    Article  Google Scholar 

  16. Papp, B., Pal, C., & Hurst, L. D. (2004). Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast. Nature, 429, 661–664. doi:10.1038/nature02636.

    Article  CAS  Google Scholar 

  17. Ghim, C. M., Goh, K. I., & Kahng, B. (2005). Lethality and synthetic lethality in the genome-wide metabolic network of Escherichia coli. Journal of Theoretical Biology, 237, 401–411. doi:10.1016/j.jtbi.2005.04.025.

    Article  CAS  Google Scholar 

  18. Fell, D. A., & Wagner, A. (2000). The small world of metabolism. Nature Biotechnology, 18, 1121–1122. doi:10.1038/81025.

    Article  CAS  Google Scholar 

  19. Wagner, A., & Fell, D. A. (2001). The small world inside large metabolic networks. Proceedings of the Royal Society of London. Series B. Biological Sciences, 268, 1803–1810. doi:10.1098/rspb.2001.1711.

    Article  CAS  Google Scholar 

  20. Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., & Barabási, A. L. (2002). Hierarchical organization of modularity in metabolic networks. Science, 297, 1551–1555. doi:10.1126/science.1073374.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

Da Jiang, Hui Liu and Shuigeng Zhou are supported by National Natural Science Foundation of China under grant no. 60496327 and Shanghai Leading Academic Discipline Project (Project number B114).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yi-Ping Phoebe Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jiang, D., Zhou, S., Liu, H. et al. Inferring Minimal Feasible Metabolic Networks of Escherichia coli . Appl Biochem Biotechnol 160, 222–231 (2010). https://doi.org/10.1007/s12010-009-8572-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12010-009-8572-5

Keywords

Navigation