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

Markus J. Herrgård; Neil Swainston; Paul Dobson; Warwick B. Dunn; K. Yalçin Arga; Mikko Arvas; Nils Büthgen; Simon Borger; Roeland Costenoble; Matthias Heinemann; Michael Hucka; Nicolas Le Novère; Peter Li; Wolfram Liebermeister; Monica L. Mo; Ana Paula Oliveira; Dina Petranovic; Stephen Pettifer; Evangelos Simeonidis; Kieran Smallbone; Irena Spasić; Dieter Weichart; Roger Brent; David S. Broomhead; Hans V. Westerhoff; Betül Kirdar; Merja Penttilä; Edda Klipp; Bernhard Palsson; Uwe Sauer; Stephen G. Oliver; Pedro Mendes; Jens Nielsen; Douglas B. Kell

doi:10.1038/nbt1492

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

Markus J. Herrgård
, Neil Swainston
, Paul Dobson
, Warwick B. Dunn
, K. Yalçin Arga
, Mikko Arvas
, Nils Büthgen
, Simon Borger
, Roeland Costenoble
, Matthias Heinemann
, Michael Hucka
, Nicolas Le Novère
, Peter Li
, Wolfram Liebermeister
, Monica L. Mo
, Ana Paula Oliveira
, Dina Petranovic
, Stephen Pettifer
, Evangelos Simeonidis
, Kieran Smallbone

Irena Spasić, Dieter Weichart, Roger Brent, David S. Broomhead, Hans V. Westerhoff, Betül Kirdar, Merja Penttilä, Edda Klipp, Bernhard Palsson, Uwe Sauer, Stephen G. Oliver, Pedro Mendes, Jens Nielsen, Douglas B. Kell^*

^*Corresponding author for this work

University of California System
Synthetic Genomics, Inc.
University of Manchester
Boğaziçi University
VTT (former employee or external)
Max Planck Institute for Molecular Genetics
Swiss Federal Institute of Technology in Zurich (ETH Zürich)
California Institute of Technology
European Bioinformatics Institute (EMBL-EBI)
Technical University of Denmark (DTU)
Chalmers University of Technology
Molecular Sciences Institute (MSI)
Vrije Universiteit Brussel
University of Cambridge
Virginia Tech

Research output: Contribution to journal › Article › Scientific › peer-review

496 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	1155-1160
Journal	Nature Biotechnology
Volume	26
Issue number	10
DOIs	https://doi.org/10.1038/nbt1492
Publication status	Published - 1 Oct 2008
MoE publication type	A1 Journal article-refereed

Funding

The Manchester groups thank the UK Biotechnology and Biological Sciences Research Council (BBSRC) and the Engineering and Physical Sciences Research Council (EPSRC) for financial support including for the Manchester Centre for Integrative Systems Biology (http://www.mcisb.org/). The UCSD participants thank the National Institutes of Health for financial support (NIH R01 GM071808). We thank Diane Kelly, Sarah Keating and Norman Paton for many useful discussions. The Jamboree was held under the auspices and with the sponsorship of the Yeast Systems Biology Network (EC Contract: LSHG-CT-2005-018942).

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Herrgård, M. J., Swainston, N., Dobson, P., Dunn, W. B., Arga, K. Y., Arvas, M., Büthgen, N., Borger, S., Costenoble, R., Heinemann, M., Hucka, M., Le Novère, N., Li, P., Liebermeister, W., Mo, M. L., Oliveira, A. P., Petranovic, D., Pettifer, S., Simeonidis, E., ... Kell, D. B. (2008). A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nature Biotechnology, 26(10), 1155-1160. https://doi.org/10.1038/nbt1492

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title = "A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology",

abstract = "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.",

author = "Herrg{\aa}rd, \{Markus J.\} and Neil Swainston and Paul Dobson and Dunn, \{Warwick B.\} and Arga, \{K. Yal{\c c}in\} and Mikko Arvas and Nils B{\"u}thgen and Simon Borger and Roeland Costenoble and Matthias Heinemann and Michael Hucka and \{Le Nov{\`e}re\}, Nicolas and Peter Li and Wolfram Liebermeister and Mo, \{Monica L.\} and Oliveira, \{Ana Paula\} and Dina Petranovic and Stephen Pettifer and Evangelos Simeonidis and Kieran Smallbone and Irena Spasi{\'c} and Dieter Weichart and Roger Brent and Broomhead, \{David S.\} and Westerhoff, \{Hans V.\} and Bet{\"u}l Kirdar and Merja Penttil{\"a} and Edda Klipp and Bernhard Palsson and Uwe Sauer and Oliver, \{Stephen G.\} and Pedro Mendes and Jens Nielsen and Kell, \{Douglas B.\}",

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Herrgård, MJ, Swainston, N, Dobson, P, Dunn, WB, Arga, KY, Arvas, M, Büthgen, N, Borger, S, Costenoble, R, Heinemann, M, Hucka, M, Le Novère, N, Li, P, Liebermeister, W, Mo, ML, Oliveira, AP, Petranovic, D, Pettifer, S, Simeonidis, E, Smallbone, K, Spasić, I, Weichart, D, Brent, R, Broomhead, DS, Westerhoff, HV, Kirdar, B, Penttilä, M, Klipp, E, Palsson, B, Sauer, U, Oliver, SG, Mendes, P, Nielsen, J & Kell, DB 2008, 'A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology', Nature Biotechnology, vol. 26, no. 10, pp. 1155-1160. https://doi.org/10.1038/nbt1492

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AU - Herrgård, Markus J.

AU - Swainston, Neil

AU - Dobson, Paul

AU - Dunn, Warwick B.

AU - Arga, K. Yalçin

AU - Arvas, Mikko

AU - Büthgen, Nils

AU - Borger, Simon

AU - Costenoble, Roeland

AU - Heinemann, Matthias

AU - Hucka, Michael

AU - Le Novère, Nicolas

AU - Li, Peter

AU - Liebermeister, Wolfram

AU - Mo, Monica L.

AU - Oliveira, Ana Paula

AU - Petranovic, Dina

AU - Pettifer, Stephen

AU - Simeonidis, Evangelos

AU - Smallbone, Kieran

AU - Spasić, Irena

AU - Weichart, Dieter

AU - Brent, Roger

AU - Broomhead, David S.

AU - Westerhoff, Hans V.

AU - Kirdar, Betül

AU - Penttilä, Merja

AU - Klipp, Edda

AU - Palsson, Bernhard

AU - Sauer, Uwe

AU - Oliver, Stephen G.

AU - Mendes, Pedro

AU - Nielsen, Jens

AU - Kell, Douglas B.

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PY - 2008/10/1

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N2 - 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.

AB - 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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DO - 10.1038/nbt1492

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SN - 1087-0156

VL - 26

SP - 1155

EP - 1160

JO - Nature Biotechnology

JF - Nature Biotechnology

IS - 10

ER -

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

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