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Open Access Highly Accessed Research article

Further developments towards a genome-scale metabolic model of yeast

Paul D Dobson1, Kieran Smallbone23*, Daniel Jameson24, Evangelos Simeonidis25, Karin Lanthaler12, Pınar Pir6, Chuan Lu7, Neil Swainston24, Warwick B Dunn12, Paul Fisher4, Duncan Hull1, Marie Brown1, Olusegun Oshota258, Natalie J Stanford258, Douglas B Kell1, Ross D King7, Stephen G Oliver6, Robert D Stevens4 and Pedro Mendes249

Author Affiliations

1 School of Chemistry, The University of Manchester, Manchester M13 9PL, UK

2 Manchester Centre for Integrative Systems Biology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK

3 School of Mathematics, The University of Manchester, Oxford Road, Manchester M13 9PL, UK

4 School of Computer Science, Kilburn Building, The University of Manchester, Oxford Road, Manchester M13 9PL, UK

5 School of Chemical Engineering and Analytical Science, The University of Manchester, Oxford Road, Manchester M13 9PL, UK

6 Cambridge Systems Biology Centre & Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK

7 Department of Computer Science, Aberystwyth University, SY23 3DB, UK

8 Doctoral Training Centre for Integrative Systems Biology, The University of Manchester

9 Virginia Bioinformatics Institute, Virginia Tech, Washington Street 0477, Virginia 24061, USA

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BMC Systems Biology 2010, 4:145  doi:10.1186/1752-0509-4-145

Published: 28 October 2010

Abstract

Background

To date, several genome-scale network reconstructions have been used to describe the metabolism of the yeast Saccharomyces cerevisiae, each differing in scope and content. The recent community-driven reconstruction, while rigorously evidenced and well annotated, under-represented metabolite transport, lipid metabolism and other pathways, and was not amenable to constraint-based analyses because of lack of pathway connectivity.

Results

We have expanded the yeast network reconstruction to incorporate many new reactions from the literature and represented these in a well-annotated and standards-compliant manner. The new reconstruction comprises 1102 unique metabolic reactions involving 924 unique metabolites - significantly larger in scope than any previous reconstruction. The representation of lipid metabolism in particular has improved, with 234 out of 268 enzymes linked to lipid metabolism now present in at least one reaction. Connectivity is emphatically improved, with more than 90% of metabolites now reachable from the growth medium constituents. The present updates allow constraint-based analyses to be performed; viability predictions of single knockouts are comparable to results from in vivo experiments and to those of previous reconstructions.

Conclusions

We report the development of the most complete reconstruction of yeast metabolism to date that is based upon reliable literature evidence and richly annotated according to MIRIAM standards. The reconstruction is available in the Systems Biology Markup Language (SBML) and via a publicly accessible database http://www.comp-sys-bio.org/yeastnet/ webcite.