In silico metabolic engineering of Bacillus subtilis for improved production of riboflavin, Egl-237, (R,R)-2,3-butanediol and isobutanol

被引:45
作者
Hao, Tong [1 ,2 ,3 ,4 ]
Han, Binbin [1 ,3 ,4 ]
Ma, Hongwu [1 ,4 ,5 ]
Fu, Jing [1 ,3 ,4 ]
Wang, Hui [1 ,3 ,4 ]
Wang, Zhiwen [1 ,3 ,4 ]
Tang, Bincai [1 ,3 ,4 ]
Chen, Tao [1 ,3 ,4 ]
Zhao, Xueming [1 ,3 ,4 ]
机构
[1] Tianjin Univ, Sch Chem Engn & Technol, Dept Biochem Engn, Tianjin 300072, Peoples R China
[2] Tianjin Normal Univ, Coll Life Sci, Tianjin 300387, Peoples R China
[3] Tianjin Univ, Minist Educ, Key Lab Syst Bioengn, Tianjin 300072, Peoples R China
[4] Tianjin Univ, Edinburgh Tianjin Joint Res Ctr Syst Biol & Synth, Tianjin 300072, Peoples R China
[5] Chinese Acad Sci, Tianjin Inst Ind Biotechnol, Tianjin 300072, Peoples R China
基金
中国国家自然科学基金;
关键词
CARBON FLUXES; GROWTH; RECONSTRUCTION; SEQUENCE; MODEL; BIOSYNTHESIS; PROTEINS; DATABASE; NETWORK; CLONING;
D O I
10.1039/c3mb25568a
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Bacillus subtilis is a Gram-positive sporiferous bacterium widely used in a variety of industrial fields as a producer of high-quality vitamins, enzymes and proteins. Many genetic modifications and evolutionary engineering optimisations aiming at obtaining a better performing strain for its products have been studied. As genome-scale metabolic network models have gained significant popularity as effective tools in metabolic phenotype studies, we reconstructed a genome-scale metabolic network of B. subtilis - iBsu1147. The accuracy of iBsu1147 is validated by growth on various carbon sources, single gene knockout and large fragment non-essential gene knockout simulations. The model is used for the in silico metabolic engineering design of reactions over/underexpressed or knockout for increasing the production of four important products of B. subtilis: riboflavin, cellulase Egl-237, (R,R)-2,3-butanediol and isobutanol. The simulation predicted candidate reactions related to the improvement of strain performance on related products. The prediction is partly supported by previously published results. Due to the complexity of the biological system, it is difficult to manually find the factors that are not directly related to the production of the target compounds. The in silico predictions provide more choices for further strain improvement for these products.
引用
收藏
页码:2034 / 2044
页数:11
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