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用于代谢工程的下一代基因组规模模型。

Next-generation genome-scale models for metabolic engineering.

作者信息

King Zachary A, Lloyd Colton J, Feist Adam M, Palsson Bernhard O

机构信息

Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.

Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Lyngby, Denmark.

出版信息

Curr Opin Biotechnol. 2015 Dec;35:23-9. doi: 10.1016/j.copbio.2014.12.016. Epub 2015 Jan 7.

Abstract

Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict optimal genetic modifications that improve the rate and yield of chemical production. A new generation of COBRA models and methods is now being developed--encompassing many biological processes and simulation strategies-and next-generation models enable new types of predictions. Here, three key examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering.

摘要

基于约束的重建与分析(COBRA)方法已成为学术和工业实验室中代谢工程广泛使用的工具。通过采用宿主生物体代谢网络的基因组规模计算机模拟表示,COBRA方法可用于预测能提高化学生产速率和产量的最佳基因改造。新一代的COBRA模型和方法正在开发中——涵盖许多生物过程和模拟策略——并且下一代模型能够进行新型预测。在此,展示并讨论了将COBRA方法应用于菌株优化的三个关键示例。然后,对下一代COBRA模型以及它们将为系统代谢工程带来的新型预测进行了展望。

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