Title |
Flux Balance Analysis of Cyanobacterial Metabolism: The Metabolic Network of Synechocystis sp. PCC 6803
|
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Published in |
PLoS Computational Biology, June 2013
|
DOI | 10.1371/journal.pcbi.1003081 |
Pubmed ID | |
Authors |
Henning Knoop, Marianne Gründel, Yvonne Zilliges, Robert Lehmann, Sabrina Hoffmann, Wolfgang Lockau, Ralf Steuer |
Abstract |
Cyanobacteria are versatile unicellular phototrophic microorganisms that are highly abundant in many environments. Owing to their capability to utilize solar energy and atmospheric carbon dioxide for growth, cyanobacteria are increasingly recognized as a prolific resource for the synthesis of valuable chemicals and various biofuels. To fully harness the metabolic capabilities of cyanobacteria necessitates an in-depth understanding of the metabolic interconversions taking place during phototrophic growth, as provided by genome-scale reconstructions of microbial organisms. Here we present an extended reconstruction and analysis of the metabolic network of the unicellular cyanobacterium Synechocystis sp. PCC 6803. Building upon several recent reconstructions of cyanobacterial metabolism, unclear reaction steps are experimentally validated and the functional consequences of unknown or dissenting pathway topologies are discussed. The updated model integrates novel results with respect to the cyanobacterial TCA cycle, an alleged glyoxylate shunt, and the role of photorespiration in cellular growth. Going beyond conventional flux-balance analysis, we extend the computational analysis to diurnal light/dark cycles of cyanobacterial metabolism. |
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Geographical breakdown
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United Kingdom | 2 | 33% |
United States | 2 | 33% |
Unknown | 2 | 33% |
Demographic breakdown
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Scientists | 4 | 67% |
Members of the public | 2 | 33% |
Mendeley readers
Geographical breakdown
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United States | 4 | <1% |
France | 3 | <1% |
United Kingdom | 2 | <1% |
Brazil | 2 | <1% |
Malaysia | 1 | <1% |
Australia | 1 | <1% |
Norway | 1 | <1% |
Sweden | 1 | <1% |
Other | 10 | 2% |
Unknown | 435 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 118 | 25% |
Researcher | 72 | 15% |
Student > Master | 59 | 13% |
Student > Bachelor | 56 | 12% |
Student > Doctoral Student | 25 | 5% |
Other | 72 | 15% |
Unknown | 63 | 14% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 168 | 36% |
Biochemistry, Genetics and Molecular Biology | 98 | 21% |
Engineering | 30 | 6% |
Computer Science | 19 | 4% |
Chemistry | 15 | 3% |
Other | 49 | 11% |
Unknown | 86 | 18% |