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Mining and rational design of psychrophilic catalases using metagenomics and deep learning models

Appl Microbiol Biotechnol. 2024-01; 
Shuning Wu, Guoshun Xu, Yongping Su, Huoqing Huang, Xinxin Xu, Yuhong Zhang, Jian Tian, Wei Zhang, Zhiwei Zhang, Bo Liu
Products/Services Used Details Operation
Gene Synthesis … The catalase-encoding genes were synthesized by GenScript Biotech Co. (Nanjing, China), and ligated into pET-28a( +) to generate the plasmid pET-28a/cat. pET-28a/cat was … Get A Quote

摘要

A complete catalase-encoding gene, designated soiCat1, was obtained from soil samples via metagenomic sequencing, assembly, and gene prediction. soiCat1 showed 73% identity to a catalase-encoding gene of Mucilaginibacter rubeus strain P1, and the amino acid sequence of soiCAT1 showed 99% similarity to the catalase of a psychrophilic bacterium, Pedobacter cryoconitis. soiCAT1 was identified as a psychrophilic enzyme due to the low optimum temperature predicted by the deep learning model Preoptem, which was subsequently validated through analysis of enzymatic properties. Experimental results showed that soiCAT1 has a very narrow range of optimum temperature, with maximal specific activity occurring at the lowest ... More

关键词

Catalase, Deep learning model, Metagenomics, Optimum temperature, Rational design