Perspective abstract


Nature Biotechnology 26, 1155 - 1160 (2008)
Published online: 9 October 2008 | Corrected online: 7 May 2012 | doi:10.1038/nbt1492

A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

Markus J Herrgård1,19,20, Neil Swainston2,3,20, Paul Dobson3,4, Warwick B Dunn3,4, K Yalçin Arga5, Mikko Arvas6, Nils Blüthgen3,7, Simon Borger8, Roeland Costenoble9, Matthias Heinemann9, Michael Hucka10, Nicolas Le Novère11, Peter Li2,3, Wolfram Liebermeister8, Monica L Mo1, Ana Paula Oliveira12, Dina Petranovic12,19, Stephen Pettifer2,3, Evangelos Simeonidis3,7, Kieran Smallbone3,13, Irena Spasié2,3, Dieter Weichart3,4, Roger Brent14, David S Broomhead3,13, Hans V Westerhoff3,7,15, Betül Kürdar5, Merja Penttilä6, Edda Klipp8, Bernhard Ø Palsson1, Uwe Sauer9, Stephen G Oliver3,16, Pedro Mendes2,3,17, Jens Nielsen12,18 & Douglas B Kell3,4


Genomic data allow the large-scale manual or semi-automated assembly of metabolic network reconstructions, which provide highly curated organism-specific knowledge bases. Although several genome-scale network reconstructions describe Saccharomyces cerevisiae metabolism, they differ in scope and content, and use different terminologies to describe the same chemical entities. This makes comparisons between them difficult and underscores the desirability of a consolidated metabolic network that collects and formalizes the 'community knowledge' of yeast metabolism. We describe how we have produced a consensus metabolic network reconstruction for S. cerevisiae. In drafting it, we placed special emphasis on referencing molecules to persistent databases or using database-independent forms, such as SMILES or InChI strings, as this permits their chemical structure to be represented unambiguously and in a manner that permits automated reasoning. The reconstruction is readily available via a publicly accessible database and in the Systems Biology Markup Language (http://www.comp-sys-bio.org/yeastnet). It can be maintained as a resource that serves as a common denominator for studying the systems biology of yeast. Similar strategies should benefit communities studying genome-scale metabolic networks of other organisms.

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  1. Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093-0412, USA.
  2. School of Computer Science, The University of Manchester, Oxford Rd., Manchester M13 9PL, UK.
  3. The Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, The University of Manchester, 131 Princess St., Manchester M1 7DN, UK.
  4. School of Chemistry, The University of Manchester, Manchester M13 9PL, UK.
  5. Department of Chemical Engineering, Boğaziçi University, Bebek 34342, Istanbul, Turkey.
  6. VTT Biotechnology Espoo, PO Box 1500, FIN-02044, Finland.
  7. School of Chemical Engineering and Analytical Science, The University of Manchester, UK.
  8. Max-Planck-Institut für Molekulare Genetik, Ihnestrasse 73, 14195 Berlin, Germany.
  9. Institut für Molekulare Systembiologie, ETH Zurich Wolfgang-Pauli-Str. 16, 8093 Zürich, Switzerland.
  10. Control and Dynamical Systems, California Institute of Technology, Pasadena, California 91125, USA.
  11. Computational Neurobiology, EMBL-EBI, Wellcome-Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
  12. Center for Microbial Biotechnology, Department of Systems Biology, Technical University of Denmark, Building 223, DK-2800 Kgs. Lyngby, Denmark.
  13. School of Mathematics, The University of Manchester, Manchester M13 9PL, UK.
  14. The Molecular Sciences Institute, 2168 Shattuck Avenue, Berkeley, California 94704, USA.
  15. Department of Molecular Cell Physiology, Vrije Universiteit, de Boelelaan 1085, 1081 HV Amsterdam, The Netherlands.
  16. Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA, UK.
  17. Virginia Bioinformatics Institute, Virginia Tech, Washington St. 0477, Blacksburg, Virginia 24061, USA.
  18. Department of Chemical and Biological Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden.
  19. Present addresses: Synthetic Genomics, Inc., 11149 N. Torrey Pines Rd., La Jolla, California 92037, USA (M.J.H.) and Department of Chemical and Biological Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden (D.P.).
  20. These authors contributed equally to this work.

Correspondence to: Douglas B Kell3,4 e-mail: dbk@manchester.ac.uk

* In the HTML version of this article initially published, Nils Blüthgen’s name was spelled as Büthgen. The error has been corrected in the HTML version of the article.

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