Reconstruction and verification of a genome-scale metabolic model for Synechocystis sp. PCC6803
Reconstruction and verification of a genome-scale metabolic model for Synechocystis sp. PCC6803
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DOI：
10.1007/s00253-011-3559-x
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发表时间：
2011-09
影响因子：
5
通讯作者：
Katsunori Yoshikawa;Yuta Kojima;Tsubasa Nakajima;C. Furusawa;T. Hirasawa;H. Shimizu
中科院分区：
文献类型：
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作者：
Katsunori Yoshikawa;Yuta Kojima;Tsubasa Nakajima;C. Furusawa;T. Hirasawa;H. Shimizu
在产生可持续能源方面，利用蓝藻生产能源和其他有用材料的前景已经吸引了越来越多的关注，因为这些过程仅需要二氧化碳和太阳能。为了建立具有高生产率的生产过程，非常需要计算机模型来预测蓝藻的代谢活性。在这项研究中，我们重建了一个基因组规模的代谢模型的蓝藻Synechocystissp。PCC 6803，包括465种代谢产物和493种代谢反应。使用这个模型，我们进行了基于约束的代谢模拟，以获得在各种环境条件下的代谢通量分布。我们通过比较这些与实验结果from 13 C-示踪剂代谢通量分析，这是在异养和兼养条件下获得的模拟结果进行评估。在这两种情况下，有一个很好的协议的模拟和实验结果。此外，使用我们的模型，我们评估了乙醇的生产集胞藻。PCC 6803，这使我们能够定量估计其生产力如何取决于环境条件。基因组尺度的代谢模型为集胞藻代谢能力的评价和代谢特征的预测提供了有用的信息。PCC6803。
In terms of generating sustainable energy resources, the prospect of producing energy and other useful materials using cyanobacteria has been attracting increasing attention since these processes require only carbon dioxide and solar energy. To establish production processes with a high productivity, in silico models to predict the metabolic activity of cyanobacteria are highly desired. In this study, we reconstructed a genome-scale metabolic model of the cyanobacteriumSynechocystissp. PCC6803, which included 465 metabolites and 493 metabolic reactions. Using this model, we performed constraint-based metabolic simulations to obtain metabolic flux profiles under various environmental conditions. We evaluated the simulated results by comparing these with experimental results from13C-tracer metabolic flux analyses, which were obtained under heterotrophic and mixotrophic conditions. There was a good agreement of simulation and experimental results under both conditions. Furthermore, using our model, we evaluated the production of ethanol bySynechocystissp. PCC6803, which enabled us to estimate quantitatively how its productivity depends on the environmental conditions. The genome-scale metabolic model provides useful information for the evaluation of the metabolic capabilities, and prediction of the metabolic characteristics, ofSynechocystissp. PCC6803.