Further developments towards a genome-scale metabolic model of yeast

Paul D. Dobson, Kieran Smallbone, Daniel Jameson, Evangelos Simeonidis, Karin Lanthaler, Pınar Pir, Chuan Lu, Neil Swainston, Warwick B. Dunn, Paul Fisher, Duncan Hull, Marie Brown, Olusegun Oshota, Natalie J. Stanford, Douglas B. Kell, Ross Donald King, Stephen G. Oliver, Robert D. Stevens, Pedro Mendes

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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/.
Original languageEnglish
Article number145
JournalBMC Systems Biology
Volume4
DOIs
Publication statusPublished - 28 Oct 2010

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