Open Access Highly Accessed Open Badges Research article

Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium

Arnau Montagud13*, Emilio Navarro2, Pedro Fernández de Córdoba1, Javier F Urchueguía1 and Kiran Raosaheb Patil3

Author affiliations

1 Instituto Universitario de Matemática Pura y Aplicada, Universidad Politécnica de Valencia, Camino de Vera 14, 46022 Valencia, Spain

2 Departamento de Lenguajes y Ciencias de la Computación, Campus de Teatrinos, Universidad de Málaga, 29071 Málaga, Spain

3 Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69117 Heidelberg, Germany

For all author emails, please log on.

Citation and License

BMC Systems Biology 2010, 4:156  doi:10.1186/1752-0509-4-156

Published: 17 November 2010



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.


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.


iSyn669 provides a platform for facilitating the development of cyanobacteria as microbial cell factories.