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An Alkali-tolerant Carbonyl Reductase from Bacillus subtilis by Gene Mining: Identification and Application

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Abstract

Enantiopure alcohols have received much attention due to their widespread use as pharmaceutical intermediates. In the asymmetric biosynthesis of enantiopure alcohols, the excellent performance of carbonyl reductase makes it be the best choice as the biocatalysts. In this work, an alkali-tolerant carbonyl reductase (BsCR, encoded by yueD) from Bacillus subtilis (strain 168) was obtained through gene mining, and successfully heterologously expressed in Escherichia coli with pET-32a. BsCR showed excellent alkali resistance and even can keep more than 70% of its peak activity after incubation in Tris–HCl buffer at pH 9.0 for 40 h. The Michaelis constants and maximal velocity of the BsCR to NADPH (A) and ethyl 4-chloroacetoacetate (B) are \(K_{m}^{A}\) = 5.390 × 10−2 mmol/L, \(K_{m}^{B}\) = 1.855 mmol/L, and \(V_{max}\) = 147.3 μmol·min−1·mg−1, respectively. Applying the E. coli BL21(DE3)/pET-32a-yueD to catalyze asymmetric reduction of ethyl 4-chloroacetoacetate and acetophenone, the yield of S-CHBE reached 89.9% and S-1-phenyl ethanol reached 66.7%, and e.e. of both products reached more than 99%. This work provides a novel CR for asymmetric reduction.

Graphic Abstract

A carbonyl reductase (BsCR) and its gene were identified through gene mining, and overexpressed in Escherichia coli BL21(DE3) for whole-cell biocatalytic asymmetric reduction

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Acknowledgments

The authors acknowledge all the financial supports for this research by the National Natural Science Foundation of China (Grant No. 21376184), Foundation from the Educational Commission of Hubei Province of China (Grant No. D20121108), the National Key Research and Development Project (2017YFF0205803, Ministry of Science and Technology of China), and the National Institute of Metrology of China (21-AKY1615).

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Correspondence to Zhong-Hua Yang.

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Luo, W., Du, HJ., Bonku, E.M. et al. An Alkali-tolerant Carbonyl Reductase from Bacillus subtilis by Gene Mining: Identification and Application. Catal Lett 149, 2973–2983 (2019). https://doi.org/10.1007/s10562-019-02873-w

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