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Montagud2010 - Genome-scale metabolic network of Synechocystis sp. PCC6803 (iSyn669)

ABSTRACT: Montagud2010 - Genome-scale metabolic network of Synechocystis sp. PCC6803 (iSyn669) This model is described in the article: Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium. Montagud A, Navarro E, Fernández de Córdoba P, Urchueguía JF, Patil KR. BMC Syst Biol 2010; 4: 156 Abstract: BACKGROUND: Synechocystis sp. PCC6803 is a cyanobacterium considered as a candidate photo-biological production platform--an attractive cell factory capable of using CO2 and light as carbon and energy source, respectively. In order to enable efficient use of metabolic potential of Synechocystis sp. PCC6803, it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the Synechocystis metabolic network. RESULTS: We report the most comprehensive metabolic model of Synechocystis sp. PCC6803 available, iSyn669, which includes 882 reactions, associated with 669 genes, and 790 metabolites. The model includes a detailed biomass equation which encompasses elementary building blocks that are needed for cell growth, as well as a detailed stoichiometric representation of photosynthesis. We demonstrate applicability of iSyn669 for stoichiometric analysis by simulating three physiologically relevant growth conditions of Synechocystis sp. PCC6803, and through in silico metabolic engineering simulations that allowed identification of a set of gene knock-out candidates towards enhanced succinate production. Gene essentiality and hydrogen production potential have also been assessed. Furthermore, iSyn669 was used as a transcriptomic data integration scaffold and thereby we found metabolic hot-spots around which gene regulation is dominant during light-shifting growth regimes. CONCLUSIONS: iSyn669 provides a platform for facilitating the development of cyanobacteria as microbial cell factories. This model is hosted on BioModels Database and identified by: MODEL1507180008. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Nicolas Le Novère

PROVIDER: MODEL1507180008 | BioModels | 2015-07-30

REPOSITORIES: BioModels

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	MODEL1507180008?filename=MODEL1507180008-biopax2.owl	Owl
	MODEL1507180008?filename=MODEL1507180008-biopax3.owl	Owl
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Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium.

Montagud Arnau A Navarro Emilio E Fernández de Córdoba Pedro P Urchueguía Javier F JF Patil Kiran Raosaheb KR

BMC systems biology 20101117

<h4>Background</h4>Synechocystis sp. PCC6803 is a cyanobacterium considered as a candidate photo-biological production platform--an attractive cell factory capable of using CO2 and light as carbon and energy source, respectively. In order to enable efficient use of metabolic potential of Synechocystis sp. PCC6803, it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the Synechocystis metabolic network.<h4>Results</h4>We report the most comprehensive met ...[more]

PMID: 21083885

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Project description:Nogales2012 - Genome-scale metabolic network of Synechocystis sp. (iJN678) This model is described in the article: Detailing the optimality of photosynthesis in cyanobacteria through systems biology analysis. Nogales J, Gudmundsson S, Knight EM, Palsson BO, Thiele I. Proc. Natl. Acad. Sci. U.S.A. 2012 Feb; 109(7): 2678-2683 Abstract: Photosynthesis has recently gained considerable attention for its potential role in the development of renewable energy sources. Optimizing photosynthetic organisms for biomass or biofuel production will therefore require a systems understanding of photosynthetic processes. We reconstructed a high-quality genome-scale metabolic network for Synechocystis sp. PCC6803 that describes key photosynthetic processes in mechanistic detail. We performed an exhaustive in silico analysis of the reconstructed photosynthetic process under different light and inorganic carbon (Ci) conditions as well as under genetic perturbations. Our key results include the following. (i) We identified two main states of the photosynthetic apparatus: a Ci-limited state and a light-limited state. (ii) We discovered nine alternative electron flow pathways that assist the photosynthetic linear electron flow in optimizing the photosynthesis performance. (iii) A high degree of cooperativity between alternative pathways was found to be critical for optimal autotrophic metabolism. Although pathways with high photosynthetic yield exist for optimizing growth under suboptimal light conditions, pathways with low photosynthetic yield guarantee optimal growth under excessive light or Ci limitation. (iv) Photorespiration was found to be essential for the optimal photosynthetic process, clarifying its role in high-light acclimation. Finally, (v) an extremely high photosynthetic robustness drives the optimal autotrophic metabolism at the expense of metabolic versatility and robustness. The results and modeling approach presented here may promote a better understanding of the photosynthetic process. They can also guide bioengineering projects toward optimal biofuel production in photosynthetic organisms. This model is hosted on BioModels Database and identified by: MODEL1507180046. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.