Literature DB >> 12115428

Metabolic pathway analysis of a recombinant yeast for rational strain development.

Ross Carlson1, David Fell, Friedrich Srienc.   

Abstract

Elementary mode analysis has been used to study a metabolic pathway model of a recombinant Saccharomyces cerevisiae system that was genetically engineered to produce the bacterial storage compound poly-beta-hydroxybutyrate (PHB). The model includes biochemical reactions from the intermediary metabolism and takes into account cellular compartmentalization as well as the reversibility/irreversibility of the reactions. The reaction network connects the production and/or consumption of eight external metabolites including glucose, acetate, glycerol, ethanol, PHB, CO(2), succinate, and adenosine triphosphate (ATP). Elementary mode analysis of the wild-type S. cerevisiae system reveals 241 unique reaction combinations that balance the eight external metabolites. When the recombinant PHB pathway is included, and when the reaction model is altered to simulate the experimental conditions when PHB accumulates, the analysis reveals 20 unique elementary modes. Of these 20 modes, 7 produce PHB with the optimal mode having a theoretical PHB carbon yield of 0.67. Elementary mode analysis was also used to analyze the possible effects of biochemical network modifications and altered culturing conditions. When the natively absent ATP citrate-lyase activity is added to the recombinant reaction network, the number of unique modes increases from 20 to 496, with 314 of these modes producing PHB. With this topological modification, the maximum theoretical PHB carbon yield increases from 0.67 to 0.83. Adding a transhydrogenase reaction to the model also improves the theoretical conversion of substrate into PHB. The recombinant system with the transhydrogenase reaction but without the ATP citrate-lyase reaction has an increase in PHB carbon yield from 0.67 to 0.71. When the model includes both the ATP citrate-lyase reaction and the transhydrogenase reaction, the maximum theoretical carbon yield increases to 0.84. The reaction model was also used to explore the possibility of producing PHB under anaerobic conditions. In the absence of oxygen, the recombinant reaction network possesses two elementary modes capable of producing PHB. Interestingly, both modes also produce ethanol. Elementary mode analysis provides a means of deconstructing complex metabolic networks into their basic functional units. This information can be used for analyzing existing pathways and for the rational design of further modifications that could improve the system's conversion of substrate into product. Copyright 2002 Wiley Periodicals, Inc.

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Year:  2002        PMID: 12115428     DOI: 10.1002/bit.10305

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  32 in total

Review 1.  Thirteen years of building constraint-based in silico models of Escherichia coli.

Authors:  Jennifer L Reed; Bernhard Ø Palsson
Journal:  J Bacteriol       Date:  2003-05       Impact factor: 3.490

2.  Flux coupling analysis of genome-scale metabolic network reconstructions.

Authors:  Anthony P Burgard; Evgeni V Nikolaev; Christophe H Schilling; Costas D Maranas
Journal:  Genome Res       Date:  2004-01-12       Impact factor: 9.043

3.  Analysis of metabolic capabilities using singular value decomposition of extreme pathway matrices.

Authors:  Nathan D Price; Jennifer L Reed; Jason A Papin; Iman Famili; Bernhard O Palsson
Journal:  Biophys J       Date:  2003-02       Impact factor: 4.033

4.  The JAK-STAT signaling network in the human B-cell: an extreme signaling pathway analysis.

Authors:  Jason A Papin; Bernhard O Palsson
Journal:  Biophys J       Date:  2004-07       Impact factor: 4.033

5.  Engineering the monomer composition of polyhydroxyalkanoates synthesized in Saccharomyces cerevisiae.

Authors:  Bo Zhang; Ross Carlson; Friedrich Srienc
Journal:  Appl Environ Microbiol       Date:  2006-01       Impact factor: 4.792

Review 6.  Recent advances in elementary flux modes and yield space analysis as useful tools in metabolic network studies.

Authors:  Predrag Horvat; Martin Koller; Gerhart Braunegg
Journal:  World J Microbiol Biotechnol       Date:  2015-06-12       Impact factor: 3.312

7.  Network-level analysis of metabolic regulation in the human red blood cell using random sampling and singular value decomposition.

Authors:  Christian L Barrett; Nathan D Price; Bernhard O Palsson
Journal:  BMC Bioinformatics       Date:  2006-03-13       Impact factor: 3.169

Review 8.  Which metabolic pathways generate and characterize the flux space? A comparison among elementary modes, extreme pathways and minimal generators.

Authors:  Francisco Llaneras; Jesús Picó
Journal:  J Biomed Biotechnol       Date:  2010-05-11

9.  In silico approaches to study mass and energy flows in microbial consortia: a syntrophic case study.

Authors:  Reed Taffs; John E Aston; Kristen Brileya; Zackary Jay; Christian G Klatt; Shawn McGlynn; Natasha Mallette; Scott Montross; Robin Gerlach; William P Inskeep; David M Ward; Ross P Carlson
Journal:  BMC Syst Biol       Date:  2009-12-10

10.  Flux Design: In silico design of cell factories based on correlation of pathway fluxes to desired properties.

Authors:  Guido Melzer; Manely Eslahpazir Esfandabadi; Ezequiel Franco-Lara; Christoph Wittmann
Journal:  BMC Syst Biol       Date:  2009-12-25
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