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Functional cartography of complex metabolic networks

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Abstract

High-throughput techniques are leading to an explosive growth in the size of biological databases and creating the opportunity to revolutionize our understanding of life and disease. Interpretation of these data remains, however, a major scientific challenge. Here, we propose a methodology that enables us to extract and display information contained in complex networks1,2,3. Specifically, we demonstrate that we can find functional modules4,5 in complex networks, and classify nodes into universal roles according to their pattern of intra- and inter-module connections. The method thus yields a ‘cartographic representation’ of complex networks. Metabolic networks6,7,8 are among the most challenging biological networks and, arguably, the ones with most potential for immediate applicability9. We use our method to analyse the metabolic networks of twelve organisms from three different superkingdoms. We find that, typically, 80% of the nodes are only connected to other nodes within their respective modules, and that nodes with different roles are affected by different evolutionary constraints and pressures. Remarkably, we find that metabolites that participate in only a few reactions but that connect different modules are more conserved than hubs whose links are mostly within a single module.

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Figure 1: Performance of module identification methods.
Figure 2: Roles and regions in the z–P parameter space.
Figure 3: Cartographic representation of the metabolic network of E. coli.
Figure 4: Roles of metabolites and inter-species conservation.

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Acknowledgements

We thank L. Broadbelt, V. Hatzimanikatis, A. A. Moreira, E. T. Papoutsakis, M. Sales-Pardo and D. B. Stouffer for discussions and suggestions, and H. Ma and A. P. Zeng for providing us with their metabolic networks' database. R.G. thanks the Fulbright Program and the Spanish Ministry of Education, Culture & Sports. L.A.N.A. acknowledges the support of a Searle Leadership Fund Award and of a NIH/NIGMS K-25 award.

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Authors and Affiliations

  1. NICO and Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, 60208, USA

    Roger Guimerà & Luís A. Nunes Amaral

Authors
  1. Roger Guimerà
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  2. Luís A. Nunes Amaral
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Correspondence to Luís A. Nunes Amaral.

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The authors declare that they have no competing financial interests.

Supplementary information

Supplementary Discussion

Additional information on role definition, application of the method to metabolic networks, and discussion of the results. This file contains 13 figures (S1-S13). (PDF 1699 kb)

Supplementary Table 1

Module description (including metabolite list) for the 12 organisms as obtained from the MZ database. (XLS 60 kb)

Supplementary Table 2 (module)

Module description (including metabolite list) for the 12 organisms as obtained from the KEGG database. (XLS 123 kb)

Supplementary Table 2 (role)

Role description (including metabolite list) for the 12 organisms as obtained from the KEGG database. (XLS 112 kb)

Supplementary Table 3

Role description (including metabolite list) for the 12 organisms as obtained from the MZ database. (XLS 72 kb)

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Guimerà, R., Nunes Amaral, L. Functional cartography of complex metabolic networks. Nature 433, 895–900 (2005). https://doi.org/10.1038/nature03288

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