50
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          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.

          Related collections

          Most cited references42

          • Record: found
          • Abstract: found
          • Article: not found

          Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0.

          Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a substantial update of this in silico toolbox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include (i) network gap filling, (ii) (13)C analysis, (iii) metabolic engineering, (iv) omics-guided analysis and (v) visualization. As with the first version, the COBRA Toolbox reads and writes systems biology markup language-formatted models. In version 2.0, we improved performance, usability and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the toolbox and validate results. This toolbox lowers the barrier of entry to use powerful COBRA methods.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Functional Characterization of the S. cerevisiae Genome by Gene Deletion and Parallel Analysis

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              ChEBI: a database and ontology for chemical entities of biological interest

              Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on ‘small’ chemical compounds. The molecular entities in question are either natural products or synthetic products used to intervene in the processes of living organisms. Genome-encoded macromolecules (nucleic acids, proteins and peptides derived from proteins by cleavage) are not as a rule included in ChEBI. In addition to molecular entities, ChEBI contains groups (parts of molecular entities) and classes of entities. ChEBI includes an ontological classification, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified. ChEBI is available online at http://www.ebi.ac.uk/chebi/
                Bookmark

                Author and article information

                Journal
                BMC Syst Biol
                BMC Syst Biol
                BMC Systems Biology
                BioMed Central
                1752-0509
                2012
                4 June 2012
                : 6
                : 55
                Affiliations
                [1 ]Department of Biological & Environmental Engineering, Cornell University, Ithaca, NY, 14853, USA
                [2 ]Manchester Centre for Integrative Systems Biology, University of Manchester, Manchester, M1 7DN, UK
                [3 ]Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, 14853, USA
                [4 ]School of Computer Science, University of Manchester, Manchester, M13 9PL, UK
                Article
                1752-0509-6-55
                10.1186/1752-0509-6-55
                3413506
                22663945
                b95770f5-358e-46ec-adb4-0db82817eed3
                Copyright ©2012 Heavner et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 2 March 2012
                : 4 June 2012
                Categories
                Research Article

                Quantitative & Systems biology
                genre,reconstruction,gem,flux balance analysis,metabolic,model,yeast
                Quantitative & Systems biology
                genre, reconstruction, gem, flux balance analysis, metabolic, model, yeast

                Comments

                Comment on this article