Dataset Information

Nogales2012 - Genome-scale metabolic network of Synechocystis sp. PCC6803 (iJN678)

ABSTRACT: Nogales2012 - Genome-scale metabolic network of Synechocystis sp. (iJN678) This model is described in the article: Detailing the optimality of photosynthesis in cyanobacteria through systems biology analysis. Nogales J, Gudmundsson S, Knight EM, Palsson BO, Thiele I. Proc. Natl. Acad. Sci. U.S.A. 2012 Feb; 109(7): 2678-2683 Abstract: Photosynthesis has recently gained considerable attention for its potential role in the development of renewable energy sources. Optimizing photosynthetic organisms for biomass or biofuel production will therefore require a systems understanding of photosynthetic processes. We reconstructed a high-quality genome-scale metabolic network for Synechocystis sp. PCC6803 that describes key photosynthetic processes in mechanistic detail. We performed an exhaustive in silico analysis of the reconstructed photosynthetic process under different light and inorganic carbon (Ci) conditions as well as under genetic perturbations. Our key results include the following. (i) We identified two main states of the photosynthetic apparatus: a Ci-limited state and a light-limited state. (ii) We discovered nine alternative electron flow pathways that assist the photosynthetic linear electron flow in optimizing the photosynthesis performance. (iii) A high degree of cooperativity between alternative pathways was found to be critical for optimal autotrophic metabolism. Although pathways with high photosynthetic yield exist for optimizing growth under suboptimal light conditions, pathways with low photosynthetic yield guarantee optimal growth under excessive light or Ci limitation. (iv) Photorespiration was found to be essential for the optimal photosynthetic process, clarifying its role in high-light acclimation. Finally, (v) an extremely high photosynthetic robustness drives the optimal autotrophic metabolism at the expense of metabolic versatility and robustness. The results and modeling approach presented here may promote a better understanding of the photosynthetic process. They can also guide bioengineering projects toward optimal biofuel production in photosynthetic organisms. This model is hosted on BioModels Database and identified by: MODEL1507180046. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Nicolas Le Novère

PROVIDER: MODEL1507180046 | BioModels | 2015-07-30

REPOSITORIES: BioModels

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Publications

Detailing the optimality of photosynthesis in cyanobacteria through systems biology analysis.

Nogales Juan J Gudmundsson Steinn S Knight Eric M EM Palsson Bernhard O BO Thiele Ines I

Proceedings of the National Academy of Sciences of the United States of America 20120130 7

Photosynthesis has recently gained considerable attention for its potential role in the development of renewable energy sources. Optimizing photosynthetic organisms for biomass or biofuel production will therefore require a systems understanding of photosynthetic processes. We reconstructed a high-quality genome-scale metabolic network for Synechocystis sp. PCC6803 that describes key photosynthetic processes in mechanistic detail. We performed an exhaustive in silico analysis of the reconstructe ...[more]

PMID: 22308420

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Project description:Transcriptional response of the photoheterotrophic marine bacterium D. shibea to changing light regimes. Second part of the study analysing the transition from photoheterotrophic light to heterotrophic dark growth. Bacterial aerobic anoxygenic photosynthesis (AAP) is an important mechanism of energy gain in aquatic habitats, accounting for up to 5% of the surface ocean’s photosynthetic electron transport. The dominant AAP bacteria in marine communities belong to the Roseobacter clade. For this reason we used Dinoroseobacter shibae as a model organism to study the transcriptional response of AAP bacteria to changing light regimes. We used continuous cultivation of D. shibae in a chemostat in combination with time series microarray analysis in order to identify gene regulatory patterns after a change in illumination. The change from heterotrophic growth in the dark to photoheterotrophic growth in the light was accompanied by a strong but transient activation of a broad stress response to cope with the formation of harmful singlet oxygen during photophosphorylation, an immediate downregulation of photosynthesis-related genes, fine-tuning of the expression of electron transport chain components and upregulation of the transcriptional and translational apparatus. Furthermore, our data indicate that D. shibae might use the 3-hydroxypropionate cycle for CO2 fixation. Analysis of the transcriptome dynamics after the switch from light to dark demonstrates that only few genes are directly regulated in response to light and other signals such as singlet oxygen concentration, electron flow, redox status and energy charge of the cell must be involved in the regulation of the processes accompanying AAP. Based on the transcriptome data first hypothesis about transcriptional control of AAP could be formulated. This study provides the first analysis of AAP on the level of transcriptome dynamics. Our data allow the formulation of testable hypotheses about the mechanisms involved in the regulation of this important biological process. Samples from light grown cells were used as a reference, 6 timepoints in the dark, biological replicates: 2

Dataset Information

Nogales2012 - Genome-scale metabolic network of Synechocystis sp. PCC6803 (iJN678)

Publications

Detailing the optimality of photosynthesis in cyanobacteria through systems biology analysis.

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