Comparative analysis of L-sorbose dehydrogenase by docking strategy for 2-keto-L-gulonic acid production in Ketogulonicigenium vulgare and Bacillus endophyticus consortium.

Si Chen, Nan Jia, Ming-Zhu Ding, Ying-Jin Yuan

Journal: Journal of industrial microbiology & biotechnology 2017;43(11):1507-1516

PMID: 27565673

Abstract

Improving the yield of 2-keto-L-gulonic acid (2-KGA), the direct precursor of vitamin C, draws more and more attention in industrial production. In this study, we try to increase the 2-KGA productivity by computer-aided selection of genes encoding L-sorbose dehydrogenases (SDH) of Ketogulonicigenium vulgare. First, six SDHs were modeled by docking strategy to predict the binding mode with co-factor PQQ. The binding energy between SSDA1-H/SSDA1-L and PQQ was the highest, followed by SSDA3/SSDA2. The binding energy between SSDA1-P/SSDB and PQQ was the lowest. Then, these genes were overexpressed, respectively, in an industrial strain K. vulgare HKv604. Overexpression of ssda1-l and ssda1-h enhanced the 2-KGA production by 7.89 and 12.56 % in mono-cultured K. vulgare, and by 13.21 and 16.86 % when K. vulgare was co-cultured with Bacillus endophyticus. When the engineered K. vulgare SyBE_Kv000116013 (overexpression of ssda1-p) or SyBE_Kv000116016 (overexpression of ssdb) was co-cultured with B. endophyticus, the 2-KGA production decreased significantly. The docking results were in accordance with the experimental data, which indicated that computer-aided modeling is an efficient strategy for screening more efficient enzymes.

Address: Key Laboratory of Systems Bioengineering (Ministry of Education) School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, People's Republic of China.; SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin, 300072, People's Republic of China.; Key Laboratory of Systems Bioengineering (Ministry of Education) School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, People's Republic of China. [email protected].; SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin, 300072, People's Republic of China. [email protected].

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