4.5 Article

Secreting recombinant barnase by Lactococcus lactis and its application in reducing RNA from forages

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ENZYME AND MICROBIAL TECHNOLOGY
卷 164, 期 -, 页码 -

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.enzmictec.2022.110191

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Barnase; Lactococcus lactis; SCP

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Barnase is an enzyme used for plasmid purification, targeted gene therapy, and protein interaction studies. The barnase gene from Bacillus amyloliquefaciens BH072 was successfully cloned into Lactococcus lactis, and its secretion was controlled using signal peptides. The optimal conditions for barnase activity and enzymatic reduction of nucleic acids in SCP forages were investigated. Homology modeling of barnase revealed its three-dimensional structure and substrate simulation docking predicted key active residues and bonding patterns.
Barnase is a ribonuclease used for plasmid purification, targeted gene therapy and studies of protein interactions. To make the use of barnase easier, the barnase gene from Bacillus amyloliquefaciens BH072 was cloned into Lactococcus lactis under the control of the PP5 or PnisA promoters. Four recombinant expression vectors were constructed with one or two signal peptides to control the enzyme secretion. 310 mg/L barnase was obtained in the presence of its inhibitor barstar after 36 h induction. The properties of barnase were investigated, showing that the optimal reaction temperature and pH were 50 degrees C and 5.0, respectively, and the highest enzyme activity reached 16.5 kU/mL. Barnase stored at 40 degrees C for 72 h retained 90 % of its initial activity, and maintained more than 80 % of its initial activity after 72 h of storage at pH 5.0-9.0. Furthermore, the optimal conditions for enzymatic reduction of nucleic acids in single-cell proteins (SCP) forages was investigated. 1 % salt solution with an SCP-enzyme ratio of 1000:1, pH 5.0 and incubated at 50 degrees C for 1 h, allowed 82 % RNA content reduction. Finally, homology modeling of barnase demonstrates its three-dimensional structure, and substrate simulation docking predicts key active residues as well as bonding patterns.

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