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Flux Balance Analysis of Cyanobacterial Metabolism: The Metabolic Network of Synechocystis sp. PCC 6803

Overview of attention for article published in PLoS Computational Biology, June 2013
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Title
Flux Balance Analysis of Cyanobacterial Metabolism: The Metabolic Network of Synechocystis sp. PCC 6803
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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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 465 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 5 1%
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 %
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 %
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%