A Novel High Glucose-Tolerant β-Glucosidase: Targeted Computational Approach for Metagenomic Screening

Abstract

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 K _i (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.

Keywords: high glucose tolerance; in silico screening; lignocellulosic biomass; metagenome; novel β-glucosidase.