Mining metagenomes from extremophiles as a resource for novel glycoside hydrolases for industrial applications

Ellie Ashcroft, Melissa Poma, Dirk Tischler, Jose Munoz-Munoz*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The exploration of metagenomes from extremophiles has emerged as a promising approach for discovering novel glycoside hydrolases (GHs) with potential industrial applications. Extremophiles, which thrive in harsh conditions such as high salinity, extreme temperatures, and acidic or alkaline environments, produce enzymes naturally adapted to function under these conditions. This unique adaptability makes them highly desirable for industrial processes requiring robust and efficient biocatalysts. These biocatalysts reduce reliance on harsh chemicals and energy-intensive processes, contributing to greener industrial operations. This review underscores the power of metagenomics in bypassing the need to culture large libraries of extremophiles in the lab. High-throughput sequencing and bioinformatics enable the identification of novel GH-encoding genes directly from environmental DNA. While metagenomic mining has yielded promising results, challenges such as the expression of extremophile-derived genes in mesophilic hosts, low activity yields, and scalability remain. Advances in synthetic biology and protein engineering could address these bottlenecks, enabling more efficient utilization of GHs. Additionally, integrating machine learning for predictive functional annotation may accelerate the identification of high-value candidates.

Original languageEnglish
Title of host publicationMethods in Enzymology
Place of Publication Amsterdam, Netherlands
PublisherAcademic Press Inc.
DOIs
Publication statusE-pub ahead of print - 6 Mar 2025

Publication series

NameMethods in Enzymology
ISSN (Print)0076-6879
ISSN (Electronic)1557-7988

Keywords

  • Extremophiles
  • Glycoside hydrolases
  • Industrial applications
  • Metagenomes

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