Exploring the Effects of Carbon Sources on the Metabolic Capacity for Shikimic Acid Production in Escherichia coli Using In Silico Metabolic Predictions

被引:34
作者
Ahn, Jung Oh [1 ]
Lee, Hong Weon [1 ]
Saha, Rajib [2 ]
Park, Myong Soo [1 ]
Jung, Joon-Ki [1 ]
Lee, Dong-Yup [2 ,3 ]
机构
[1] Korea Res Inst Biosci & Biotechnol, Div Biotechnol R&BD, Taejon 305333, South Korea
[2] Natl Univ Singapore, Dept Chem & Biomol Engn, Singapore 117576, Singapore
[3] Agcy Sci Technol & Res, Bioproc Technol Inst, Singapore 138668, Singapore
关键词
Shikimic acid production; constraints-based flux analysis; genome-scale in silico model; Escherichia coli; carbon sources;
D O I
10.4014/jmb.0700.705
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
Effects of various industrially important carbon sources (glucose, sucrose, xylose, gluconate, and glycerol) on shikimic acid (SA) biosynthesis in Escherichia coli were investigated to gain new insight into the metabolic capability for overproducing SA. At the outset, constraints-based flux analysis using the genome-scale in silico model of E. coli was conducted to quantify the theoretical maximum SA yield. The corresponding flux distributions fueled by different carbon sources under investigation were compared with respect to theoretical yield and energy utilization, thereby identifying the indispensable pathways for achieving optimal SA production on each carbon source. Subsequently, a shikimate-kinase-deficient E. coli mutant was developed by blocking the aromatic amino acid pathway, and the production of SA on various carbon sources was experimentally examined during 5 1 batch culture. As a result, the highest production rate, 1.92 mmol SA/h, was obtained when glucose was utilized as a carbon source, whereas the efficient SA production from glycerol was obtained with the highest yield, 0.21 mol SA formed per moll carbon atom of carbon source consumed. The current strain can be further improved to satisfy the theoretically achievable SA production that was predicted by in silico analysis.
引用
收藏
页码:1773 / 1784
页数:12
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