Genome-scale modeling of <I>Synechocystis</I> sp. PCC 6803 and prediction of pathway insertion Export

@article{citeulike:3935307, abstract = {BACKGROUND: 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 {\copyright} 2008 Society of Chemical Industry}, address = {Department of Molecular Biosciences \& Bioengineering, University of Hawaii, 1955 East-West Road, Honolulu, Hawaii 96822-2321, USA}, author = {Fu, Pengcheng}, citeulike-article-id = {3935307}, citeulike-linkout-0 = {http://dx.doi.org/10.1002/jctb.2065}, citeulike-linkout-1 = {http://www3.interscience.wiley.com/cgi-bin/abstract/121453132/ABSTRACT}, doi = {10.1002/jctb.2065}, journal = {Journal of Chemical Technology \& Biotechnology}, keywords = {cyanobacteria, fba, synechocystis}, number = {9999}, pages = {n/a+}, posted-at = {2009-01-24 09:02:48}, priority = {2}, title = {Genome-scale modeling of <I>Synechocystis</I> sp. PCC 6803 and prediction of pathway insertion}, url = {http://dx.doi.org/10.1002/jctb.2065}, volume = {9999}, year = {2008} }

TY - JOUR ID - citeulike:3935307 L3 - citeulike-article-id:3935307 N2 - BACKGROUND: 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 IS - 9999 JF - Journal of Chemical Technology & Biotechnology AD - Department of Molecular Biosciences & Bioengineering, University of Hawaii, 1955 East-West Road, Honolulu, Hawaii 96822-2321, USA TI - Genome-scale modeling of <I>Synechocystis</I> sp. PCC 6803 and prediction of pathway insertion VL - 9999 SP - n/a KW - cyanobacteria KW - fba KW - synechocystis AU - Fu, Pengcheng PY - 2008/// UR - http://dx.doi.org/10.1002/jctb.2065 ER -