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A Novel High Glucose-Tolerant β-Glucosidase: Targeted Computational Approach for Metagenomic Screening
Frontiers in Bioengineering and Biotechnology ( IF 4.3 ) Pub Date : 2020-07-30 , DOI: 10.3389/fbioe.2020.00813
Shohreh Ariaeenejad 1 , Safura Nooshi-Nedamani 1 , Mahdie Rahban 2 , Kaveh Kavousi 2 , Atefeh Ghasemi Pirbalooti 1 , SeyedSoheil Mirghaderi 2 , Mahsa Mohammadi 1 , Mehdi Mirzaei 3 , Ghasem Hosseini Salekdeh 1, 3
Affiliation  

The rate-limiting component of cellulase for efficient degradation of lignocellulosic biomass through the enzymatic route depends on glucosidase’s sensitivity to the end product (glucose). Therefore, there is still a keen interest in finding glucose-tolerant β-glucosidase (BGL) that is active at high glucose concentrations. The main objective of this study was to identify, isolate, and characterize novel highly glucose-tolerant and halotolerant β-glucosidase gene (PersiBGL1) from the mixed genome DNA of sheep rumen metagenome as a suitable environment for efficient cellulase by computationally guided experiments instead of costly functional screening. At first, an in silico screening approach was utilized to find primary candidate enzymes with superior properties. The structure-dependent mechanism of glucose tolerance was investigated for candidate enzymes. Among the computationally selected candidates, PersiBGL1 was cloned, isolated, and structurally characterized, which achieved very high activity in relatively high temperatures and alkaline pH and was successfully used for the hydrolysis of cellobiose. This enzyme exhibits a very high glucose tolerance, with the highest inhibition constant Ki (8.8 M) among BGLs reported so far and retained 75% of its initial activity in the presence of 10 M glucose. Furthermore, a group of multivalent metal, including Mg2+, Mn2+, and Ca2+, as a cofactor, could improve the catalytic efficiency of PersiBGL1. Our results demonstrated the power of computational selected candidates to discover novel glucose tolerance BGL, effective for the bioconversion of lignocellulosic biomass.

中文翻译:

一种新的高葡萄糖耐受性 β-葡萄糖苷酶:宏基因组筛选的靶向计算方法

通过酶促途径有效降解木质纤维素生物质的纤维素酶的限速组分取决于葡萄糖苷酶对终产物(葡萄糖)的敏感性。因此,寻找在高葡萄糖浓度下有活性的耐葡萄糖β-葡萄糖苷酶(BGL)仍然存在浓厚的兴趣。本研究的主要目的是从绵羊瘤胃宏基因组的混合基因组 DNA 中鉴定、分离和表征新的高度耐葡萄糖和耐盐的 β-葡萄糖苷酶基因 (PersiBGL1) 作为高效纤维素酶的合适环境,通过计算指导实验代替昂贵的功能筛选。首先,利用计算机筛选方法来寻找具有优异特性的主要候选酶。研究了候选酶的葡萄糖耐量的结构依赖性机制。在计算选择的候选物中,PersiBGL1 被克隆、分离和结构表征,其在相对高温和碱性 pH 值下具有非常高的活性,并成功用于纤维二糖的水解。该酶表现出非常高的葡萄糖耐受性,在迄今为止报道的 BGL 中具有最高的抑制常数 Ki (8.8 M),并且在 10 M 葡萄糖存在下保留了其初始活性的 75%。此外,一组多价金属,包括 Mg2+、Mn2+ 和 Ca2+,作为辅助因子,可以提高 PersiBGL1 的催化效率。我们的结果证明了计算选择的候选者发现新的葡萄糖耐量 BGL 的能力,
更新日期:2020-07-30
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