| 合成生物系统的组合优化 |
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| 引用本文： | 顾群,李一凡,陈涛.合成生物系统的组合优化[J].生物工程学报,2013,29(8):1064-1074. |
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| 作者姓名： | 顾群 李一凡 陈涛 |
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| 作者单位： | 天津大学化工学院生物工程系,天津300072;教育部系统生物工程重点实验室,天津300072 |
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| 基金项目： | 国家重点基础研究发展计划 (973计划) (Nos. 2011CBA00804, 2012CB725203)，国家自然科学基金 (Nos. 21176182, 21206112)，国家高技术研究发展计划 (863计划) (Nos. 2012AA023102B, 2012AA022103B)，天津市自然科学基金 (No. 12JCYBJC12900)，教育部博士点基金 (No. 20100032120014) 资助。 |
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| 摘 要： | 合成生物学所面临的一项重要挑战是构建具有全新功能的生物系统.由于生物系统固有的复杂性,仅通过理性设计,通常难以使合成基因线路发挥出最优的功能.组合工程的兴起和发展为获得组合优化性状提供了有利条件,并大大促进了具有全新功能的生物系统的构建.文中主要从单个元件的微调、代谢通路的优化以及基因组范围内靶点的识别和组合修饰三个方面入手,总结和评述了近些年表现突出的合成生物系统的组合优化方法.
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| 关 键 词： | 合成生物学 组合工程 合成启动子文库 多元模块工程 组合转录工程优化法 可追踪多元重组工程 全转录工程 多元自动化基因组工程 |
| 收稿时间： | 2013/4/26 0:00:00 |
Combinatorial optimization of synthetic biological systems |
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| Qun Gu,Yifan Li and Tao Chen.Combinatorial optimization of synthetic biological systems[J].Chinese Journal of Biotechnology,2013,29(8):1064-1074. |
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| Authors: | Qun Gu Yifan Li and Tao Chen |
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| Institution: | Department of Biochemical Engineering, School of Chemical Engineering & Technology, Tianjin University, Tianjin 300072, China; Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin 300072, China;Department of Biochemical Engineering, School of Chemical Engineering & Technology, Tianjin University, Tianjin 300072, China; Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin 300072, China;Department of Biochemical Engineering, School of Chemical Engineering & Technology, Tianjin University, Tianjin 300072, China; Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin 300072, China |
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| Abstract: | A major challenge in synthetic biology is to engineer complex biological systems with novel functions. Due to the inherent complexity of biological systems, it is often difficult to rationally design every component in a synthetic gene network to achive an optimal performance. Combinatorial engineering is an important solution to this problem and can greatly facilitate the construction of novel biological functions. Here, we review methods and techniques developed in recent years for combinatorial optimization of synthetic biological systems, including methods for fine-tuning pathway components, strategies for systematically optimization of metabolic pathways, and techniques for introducing multiplex genome wide perturbations. |
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