OptKnock: A bilevel programming framework for identifying gene knockout strategies for microbial strain optimization

被引:852
作者
Burgard, AP [1 ]
Pharkya, P [1 ]
Maranas, CD [1 ]
机构
[1] Penn State Univ, Dept Chem Engn, University Pk, PA 16802 USA
关键词
genome-scale stoichiometric models; bilevel programming; strain optimization;
D O I
10.1002/bit.10803
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
The advent of genome-scale models of metabolism has laid the foundation for the development of computational procedures for suggesting genetic manipulations that lead to overproduction. In this work, the computational OptKnock framework is introduced for suggesting gene deletion strategies leading to the overproduction of chemicals or biochemicals in E. coli. This is accomplished by ensuring that a drain towards growth resources (i.e., carbon, redox potential, and energy) must be accompanied, due to stoichiometry, by the production of a desired product. Computational results for gene deletions for succinate, lactate, and 1,3-propanediol (PDO) production are in good agreement with mutant strains published in the literature. While some of the suggested deletion strategies are straightforward and involve eliminating competing reaction pathways, many others suggest complex and nonintuitive mechanisms of compensating for the removed functionalities. Finally, the OptKnock procedure, by coupling biomass formation with chemical production, hints at a growth selection/adaptation system for indirectly evolving overproducing mutants. (C) 2003 Wiley Periodicals.
引用
收藏
页码:647 / 657
页数:11
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