Improvement of the thermostability and catalytic efficiency of a highly active β-glucanase from Talaromyces leycettanus JCM12802 by optimizing residual charge–charge interactions. Issue 1 (December 2016) - You, Shuai; Tu, Tao; Zhang, Lujia; Wang, Yuan; Huang, Huoqing; Ma, Rui; Shi, Pengjun; Bai, Yingguo; Su, Xiaoyun; Lin, Zhemin; Luo, Huiying; Yao, Bin
Abstract Background β-Glucanase is one of the most extensively used biocatalysts in biofuel, food and animal feed industries. However, the poor thermostability and low catalytic efficiency of most reported β-glucanases limit their applications. Currently, two strategies are used to overcome these bottlenecks, i.e., mining for novel enzymes from extremophiles and engineering existing enzymes. Results A novel endo-β-1, 3-1, 4-glucanase of GH16 (Tlglu16A ) from the thermophilic fungusTalaromyces leycettanus JCM12802 was produced inPichia pastoris and characterized. For potential industrial applications, recombinantTl Glu16A exhibits favorable enzymatic properties over most reported glucanases, i.e., remarkable stability over a wide pH range from 1.0 to 10.0 and superior activity on glucan substrates (up to 15, 197 U/mg). The only weakness ofTl Glu16A is the thermolability at 65 °C and higher. To improve the thermostability, the enzyme thermal stability system was then used to engineerTl Glu16A through optimization of residual charge–charge interactions. Eleven mutants were constructed and compared to the wild-typeTl Glu16A. Four mutants, H58D, E134R, D235G and D296K, showed longer half-life time at 80 °C (31, 7, 25, 22 vs. 0.5 min), and two mutants, D235G and D296K, had greater specific activities (158.2 and 122.2 %, respectively) and catalytic efficiencies (k cat /K m, 170 and 114 %, respectively). Conclusions The engineeredTl Glu16A has great application potentials from the perspectives of enzyme yield and properties. Its thermostability and activity were apparently improved in the engineered enzymes through charge optimization. This study spans the genetic, functional and structural fields, and provides a combination of gene mining and protein engineering approaches for the systematic improvement of enzyme performance.