4.0 Article

Yeast 5-an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

期刊

BMC SYSTEMS BIOLOGY
卷 6, 期 -, 页码 -

出版社

BMC
DOI: 10.1186/1752-0509-6-55

关键词

Metabolic; Reconstruction; Yeast; Flux balance analysis; GEM; GENRE; Model

资金

  1. U.S. Dept. of Transportation, Federal Grant [DTOS59-07-G-00052]
  2. U.S. Department of Agriculture [2010-38502-21900]
  3. BBSRC/EPSRC grant [BB/C008219/ 1]
  4. EU Framework 7 grant UniCellSys [201142]
  5. EU Framework 7 grant BioPreDyn [289434]
  6. NIFA [2010-38502-21900, 579944] Funding Source: Federal RePORTER
  7. Biotechnology and Biological Sciences Research Council [BB/C008219/1] Funding Source: researchfish

向作者/读者索取更多资源

Background: Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results: Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model's predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Conclusions: Yeast 5 expands and refines the computational reconstruction of yeast metabolism and improves the predictive accuracy of a stoichiometrically constrained yeast metabolic model. It differs from previous reconstructions and models by emphasizing the distinction between the yeast metabolic reconstruction and the stoichiometrically constrained model, and makes both available as Additional file 4 and Additional file 5 and at http://yeast.sf.net/ as separate systems biology markup language (SBML) files. Through this separation, we intend to make the modeling process more accessible, explicit, transparent, and reproducible.

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