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Chance and necessity in the evolution of minimal metabolic networks

Naturevolume 440pages667670 (2006) | Download Citation



It is possible to infer aspects of an organism's lifestyle from its gene content1. Can the reverse also be done? Here we consider this issue by modelling evolution of the reduced genomes of endosymbiotic bacteria. The diversity of gene content in these bacteria may reflect both variation in selective forces and contingency-dependent loss of alternative pathways. Using an in silico representation of the metabolic network of Escherichia coli, we examine the role of contingency by repeatedly simulating the successive loss of genes while controlling for the environment. The minimal networks that result are variable in both gene content and number. Partially different metabolisms can thus evolve owing to contingency alone. The simulation outcomes do preserve a core metabolism, however, which is over-represented in strict intracellular bacteria. Moreover, differences between minimal networks based on lifestyle are predictable: by simulating their respective environmental conditions, we can model evolution of the gene content in Buchnera aphidicola and Wigglesworthia glossinidia with over 80% accuracy. We conclude that, at least for the particular cases considered here, gene content of an organism can be predicted with knowledge of its distant ancestors and its current lifestyle.

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We thank C. von Mering for providing early access to the updated STRING database. C.P., B.P. and P.C. are supported by the Hungarian Scientific Research Fund (OTKA). C.P. is also supported by an EMBO Long-term Fellowship. B.P. is a Fellow of the Human Frontier Science Program. M.J.L. acknowledges financial support by the Deutsche Forschungsgemeinschaft. Work on systems biology in S.G.O.'s laboratory is supported by the Biotechnology and Biological Sciences Research Council.

Author information

Author notes

  1. Csaba Pál and Balázs Papp: *These authors contributed equally to this work


  1. European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69012, Heidelberg, Germany

    • Csaba Pál
    •  & Martin J. Lercher
  2. Department of Zoology, University of Oxford, OX1 3PS, Oxford, UK

    • Csaba Pál
  3. Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, M13 9PT, Manchester, UK

    • Balázs Papp
    •  & Stephen G. Oliver
  4. Department of Biology & Biochemistry, University of Bath, Claverton Down, BA2 7AY, Bath, UK

    • Martin J. Lercher
    •  & Laurence D. Hurst
  5. Biochemistry, University of Bath, Claverton Down

    • Martin J. Lercher
    •  & Laurence D. Hurst
  6. Department of Medical Chemistry, Semmelweis University, PO Box 260, H-1444, Budapest, Hungary

    • Péter Csermely


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Competing interests

Reprints and permissions information is available at npg.nature.com/reprintsandpermissions. The authors declare no competing financial interests.

Corresponding author

Correspondence to Laurence D. Hurst.

Supplementary information

  1. Supplementary Notes

    This file contains the Supplementary Methods and Supplementary Tables 1–12. (DOC 760 kb)

  2. Supplementary Table 13

    Metabolic gene content of endosymbionts and simulated minimal genomes. (PDF 129 kb)

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