A novel high glucose-tolerant β-glucosidase: targeted computational approach for metagenomic screening

Shohreh Ariaeenejad, Safura Nooshi-Nedamani, Mahdie Rahban, Kaveh Kavousi, Atefeh Ghasemi Pirbalooti, Seyed Soheil Mirghaderi, Mahsa Mohammadi, Mehdi Mirzaei, Ghasem Hosseini Salekdeh*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    28 Citations (Scopus)
    19 Downloads (Pure)

    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 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.

    Original languageEnglish
    Article number813
    Pages (from-to)1-14
    Number of pages14
    JournalFrontiers in Bioengineering and Biotechnology
    Volume8
    DOIs
    Publication statusPublished - 30 Jul 2020

    Bibliographical note

    Copyright the Author(s) 2020. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

    Keywords

    • novel β-glucosidase
    • in silico screening
    • lignocellulosic biomass
    • high glucose tolerance
    • metagenome

    Fingerprint

    Dive into the research topics of 'A novel high glucose-tolerant β-glucosidase: targeted computational approach for metagenomic screening'. Together they form a unique fingerprint.

    Cite this