Affiliation:
1. grid.33763.32 0000000417612484 Key Laboratory of Systems Bioengineering (Ministry of Education) School of Chemical Engineering and Technology Tianjin University 300072 Tianjin People’s Republic of China
2. grid.33763.32 0000000417612484 SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin) 300072 Tianjin People’s Republic of China
Abstract
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.
Funder
Ministry of Science and Technology of China
National Natural Science Foundation of China
Publisher
Oxford University Press (OUP)
Subject
Applied Microbiology and Biotechnology,Biotechnology,Bioengineering
Cited by
10 articles.
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