Genome‐scale modeling of Synechocystis sp. PCC 6803 and prediction of pathway insertion

Abstract

AbstractBACKGROUND: Cyanobacterium Synechocystis sp. PCC 6803 has been used widely as a model system for the study of photosynthetic organisms and higher plants. The aim of this work was to integrate the genomic information, biochemistry and physiological information available for Synechocystis sp. PCC 6803 to reconstruct a metabolic network for system biology investigations.RESULTS: A genome‐scale Synechocystis sp. PCC 6803 metabolic network, including 633 genes, 704 metabolites and 831 metabolic reactions, was reconstructed for the study of optimal Synechocystis growth, network capacity and functions. Heterotrophic, photoautotrophic and mixotrophic growth conditions were simulated. The Synechocystis model was used for in silico predictions for the insertion of ethanol fermentation pathway, which is a novel approach for bioenergy and biofuels production developed in the authors' laboratory. Simulations of Synechocystis cell growth and ethanol production were compared with actual metabolic measurements which showed a satisfactory agreement.CONCLUSION: The Synechocystis metabolic network developed in this study is the first genome‐scale mathematical model for photosynthetic organisms. The model may be used not only in global understanding of cellular metabolism and photosynthesis, but also in designing metabolic engineering strategies for desirable bio‐products. Copyright © 2008 Society of Chemical Industry