Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

The large-scale organization of metabolic networks

Abstract

In a cell or microorganism, the processes that generate mass, energy, information transfer and cell-fate specification are seamlessly integrated through a complex network of cellular constituents and reactions1. However, despite the key role of these networks in sustaining cellular functions, their large-scale structure is essentially unknown. Here we present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life. We show that, despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems2. This may indicate that metabolic organization is not only identical for all living organisms, but also complies with the design principles of robust and error-tolerant scale-free networks2,3,4,5, and may represent a common blueprint for the large-scale organization of interactions among all cellular constituents.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Attributes of generic network structures.
Figure 2: Connectivity distributions P(k) for substrates.
Figure 3: Properties of metabolic networks.

Similar content being viewed by others

References

  1. Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. From molecular to modular cell biology. Nature 402, C47–52 (1999).

    Article  CAS  Google Scholar 

  2. Barabási, A.-L. & Albert, R. Emergence of scaling in random networks. Science 286, 509– 512 (1999).

    Article  ADS  MathSciNet  Google Scholar 

  3. West, G. B., Brown, J. H. & Enquist, B. J. The fourth dimension of life: fractal geometry and allometric scaling of organisms. Science 284, 1677–1679 (1999).

    Article  ADS  MathSciNet  CAS  Google Scholar 

  4. Banavar, J. R., Maritan, A. & Rinaldo, A. Size and form in efficient transportation networks. Nature 399, 130–132 (1999).

    Article  ADS  CAS  Google Scholar 

  5. Albert, R., Jeong, H. & Barabási, A.-L. Error and attack tolerance of complex networks. Nature 406, 378–382 ( 2000).

    Article  ADS  CAS  Google Scholar 

  6. Ingber, D. E. Cellular tensegrity: defining new rules of biological design that govern the cytoskeleton. J. Cell Sci. 104, 613 –627 (1993).

    PubMed  Google Scholar 

  7. Bray, D. Protein molecules as computational elements in living cells. Nature 376, 307–312 (1995).

    Article  ADS  CAS  Google Scholar 

  8. McAdams, H. H. & Arkin, A. It's a noisy business! Genetic regulation at the nanomolar scale. Trends Genet. 15, 65–69 (1999).

    Article  CAS  Google Scholar 

  9. Gardner, T. S., Cantor, C. R. & Collins, J. J. Construction of a genetic toggle switch in Escherichia coli. Nature 403, 339– 342 (2000).

    Article  ADS  CAS  Google Scholar 

  10. Elowitz, M. B. & Leibler, S. A synthetic oscillatory network of transcriptional regulators. Nature 403, 335–338 (2000).

    Article  ADS  CAS  Google Scholar 

  11. Hasty, J., Pradines, J., Dolnik, M. & Collins, J. J. Noise-based switches and amplifiers for gene expression. Proc. Natl Acad. Sci. USA 97, 2075–2080 ( 2000).

    Article  ADS  CAS  Google Scholar 

  12. Becskei, A. & Serrano, L. Engineering stability in gene networks by autoregulation. Nature 405, 590– 593 (2000).

    Article  ADS  CAS  Google Scholar 

  13. Kirschner, M., Gerhart, J. & Mitchison, T. Molecular ‘vitalism’. Cell 100, 79–88 (2000).

    Article  CAS  Google Scholar 

  14. Barkai, N. & Leibler, S. Robustness in simple biochemical networks. Nature 387, 913– 917 (1997).

    Article  ADS  CAS  Google Scholar 

  15. Yi, T. M., Huang, Y., Simon, M. I. & Doyle, J. Robust perfect adaptation in bacterial chemotaxis through integral feedback control. Proc. Natl Acad. Sci. USA 97, 4649–4653 (2000).

    Article  ADS  CAS  Google Scholar 

  16. Bhalla, U. S. & Iyengar, R. Emergent properties of networks of biological signaling pathways. Science 283, 381–387 (1999).

    Article  ADS  CAS  Google Scholar 

  17. Karp, P. D., Krummenacker, M., Paley, S. & Wagg, J. Integrated pathway–genome databases and their role in drug discovery. Trends Biotechnol. 17, 275– 281 (1999).

    Article  CAS  Google Scholar 

  18. Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27– 30 (2000).

    Article  CAS  Google Scholar 

  19. Overbeek, R. et al. WIT: integrated system for high-throughput genome sequence analysis and metabolic reconstruction. Nucleic Acids Res. 28, 123–125 (2000).

    Article  CAS  Google Scholar 

  20. Erdös, P. & Rényi, A. On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci. 5, 17–61 (1960).

    MathSciNet  MATH  Google Scholar 

  21. Bollobás, B. Random Graphs (Academic, London, 1985).

    MATH  Google Scholar 

  22. Albert, R., Jeong, H. & Barabási, A.-L. Diameter of the World-Wide Web. Nature 400, 130–131 ( 1999).

    Article  ADS  Google Scholar 

  23. Faloutsos, M., Faloutsos, P. & Faloutsos, C. On power-law relationships of the internet topology. Comp. Comm. Rev. 29, 251 ( 1999).

    Article  Google Scholar 

  24. Amaral, L. A. N., Scala, A., Barthelemy, M. & Stanley, H. E. Classes of behavior of small-world networks. (cited 31 January 2000) 〈http://xxx.lanl.gov/abs/cond-mat/0001458〉 (2000).

  25. Dorogovtsev, S. N. & Mendes, J. F. F. Evolution of reference networks with aging (cited 28 January 2000) 〈http://xxx.lanl.gov/abs/cond-mat/0001419〉 (2000).

  26. Watts, D. J. & Strogatz, S. H. Collective dynamics of ‘small-world’ networks. Nature 393, 440– 442 (1998).

    Article  ADS  CAS  Google Scholar 

  27. Barthelemy, M. & Amaral, L. A. N. Small-world networks: Evidence for a crossover picture. Phys. Rev. Lett. 82, 3180–3183 (1999).

    Article  ADS  CAS  Google Scholar 

  28. Edwards, J. S. & Palsson, B. O. The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc. Natl Acad. Sci. USA 97, 5528–5533 (2000).

    Article  ADS  CAS  Google Scholar 

Download references

Acknowledgements

We thank all members of the WIT project for making this invaluable database publicly available. We also thank C. Waltenbaugh and H. S. Seifert for comments on the manuscript. Research at the University of Notre Dame was supported by the National Science Foundation, and at Northwestern University by grants from the National Cancer Institute.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Z. N. Oltvai or A.-L. Barabási.

Supplementary Information

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jeong, H., Tombor, B., Albert, R. et al. The large-scale organization of metabolic networks. Nature 407, 651–654 (2000). https://doi.org/10.1038/35036627

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/35036627

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing