文献类型：期刊文献

英文题名：IdealKnock: A framework for efficiently identifying knockout strategies leading to targeted overproduction

作者：Gu, Deqing[1];Zhang, Cheng[1];Zhou, Shengguo[1];Wei, Liujing[1];Hua, Qiang[1,2]

机构：[1]E China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China;[2]Shanghai Collaborat Innovat Ctr Biomfg Technol, Shanghai, Peoples R China

年份：2016

卷号：61

起止页码：229

外文期刊名：COMPUTATIONAL BIOLOGY AND CHEMISTRY

收录：;EI(收录号：20161002056956);WOS:【SCI-EXPANDED(收录号:WOS:000374368200024)】；

基金：This work was financially supported by the National Basic Research Program of China (973 Program) (2012CB721101), and the National Natural Science Foundation of China (21576089).

语种：英文

外文关键词：Genome-scale metabolic network models; OptKnock; OptGene; Knockout strategies

摘要：In recent years, computer aided redesigning methods based on genome-scale metabolic network models (GEMs) have played important roles in metabolic engineering studies; however, most of these methods are hindered by intractable computing times. In particular, methods that predict knockout strategies leading to overproduction of desired biochemical are generally unable to do high level prediction because the computational time will increase exponentially. In this study, we propose a new framework named IdealKnock, which is able to efficiently evaluate potentials of the production for different biochemical in a system by merely knocking out pathways. In addition, it is also capable of searching knockout strategies when combined with the OptKnock or OptGene framework. Furthermore, unlike other methods, IdealKnock suggests a series of mutants with targeted overproduction, which enables researchers to select the one of greatest interest for experimental validation. By testing the overproduction of a large number of native metabolites, IdealKnock showed its advantage in successfully breaking through the limitation of maximum knockout number in reasonable time and suggesting knockout strategies with better performance than other methods. In addition, gene-reaction relationship is well considered in the proposed framework. (C) 2016 Elsevier Ltd. All rights reserved.