Tropical Journal of Pharmaceutical Research

Original Research Article | OPEN ACCESS

Enhancement of L-Serine Production by Corynebacterium glutamicum SYPS-062 Directly from Sucrose

Xiaomei Zhang¹, Hui Li¹, Wenfang Dou¹, Xin Xu², Zhenghong Xu¹

¹School of Pharmaceutical Science, Jiangnan University, Wuxi 214122; ²Wuxi No. 2 People's Hospital, Wuxi, 214002, China.

For correspondence:- Zhenghong Xu Email: zhenghxu@jiangnan.edu.cn Tel:+86-510-85918206

Received: 22 July 2013 Accepted: 30 October 2014 Published: 15 December 2014

Citation: Zhang X, Li H, Dou W, Xu X, Xu Z. Enhancement of L-Serine Production by Corynebacterium glutamicum SYPS-062 Directly from Sucrose. Trop J Pharm Res 2014; 13(12):2011-2014 doi: 10.4314/tjpr.v13i12.9

© 2014 The authors.
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Abstract

Purpose: To improve the production of L-serine from sucrose directly by wild type Corynebacterium glutamicum SYPS-062.

Methods: The culture medium for the production of L-serine was optimized using a statistical experimental design. Sucrose, ammonium sulfate ((NH₄)₂SO₄) and biotin were the key factors, based on previous studies. A three-level Box–Behnken factorial design combined with response surface methodology were used to optimize the medium for the production of L-serine. Validation experiments were also carried out to establish the adequacy and accuracy of the model obtained.

Results: Under optimal conditions (sucrose 81 g/l, (NH₄)₂SO₄ 30 g/l and biotin 27 μg/l), L-serine concentration increased to 14.90 g/l which is about 2.5-fold increase over that of the original medium (6 g/l). L-serine concentration in a 5 L fermenter reached 16.4 g/L.

Conclusion: The results show that statistical medium design method is effective in improving L-serine production. The optimization medium is considered fundamental and useful for the development of C. glutamicum SYPS-062 cultivation process for efficient production of L-serine on a large scale.

Keywords: L-Serine, Sugar, Medium optimization, Corynebacterium glutamicum Box-Behnken factorial design, Response surface methodology