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<p>Bioprospecting lignocellulolytic enzymes is critical to overcome the challenges associated with the efficient utilization of lignocellulosic biomass (LCB) for biofuel production. The recalcitrant nature of LCB necessitates the development of robust enzymes capable of withstanding inhibitory compounds released at the pretreatment step and achieving effective hydrolysis under industrially relevant conditions. This review emphasizes the use of advanced strategies, to understand the cellulase enzyme expression/repression and signal transduction mechanism to reveal the well knitted enzyme production machinery for the identification of novel enzyme candidates. Further, the use of advance genetic engineering techniques such as CRISPR-Cas systems, heterologous overexpression, and codon optimization have demonstrated significant potential in enhancing catalytic efficiency and reducing production costs. Integration of multi-omics data facilitates the elucidation of regulatory pathways and the optimization of enzyme formulations tailored to diverse biomass feedstocks. These combined approaches hold the potential to drive the development of sustainable and economically feasible solutions for the future of biofuel production.</p>

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Advancement in lignocellulolytic enzyme production: tailored strategies to overcome challenges in biomass hydrolysis

  • 期刊论文

  • 发表日期：

    2025年3月3日

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  • Yashika Raheja,
  • Prachi Gaur,
  • Tayyab Islam,
  • Amit Kumar Chaurasia,
  • Vivek Kumar Gaur,
  • Bhupinder Singh Chadha

摘要

Bioprospecting lignocellulolytic enzymes is critical to overcome the challenges associated with the efficient utilization of lignocellulosic biomass (LCB) for biofuel production. The recalcitrant nature of LCB necessitates the development of robust enzymes capable of withstanding inhibitory compounds released at the pretreatment step and achieving effective hydrolysis under industrially relevant conditions. This review emphasizes the use of advanced strategies, to understand the cellulase enzyme expression/repression and signal transduction mechanism to reveal the well knitted enzyme production machinery for the identification of novel enzyme candidates. Further, the use of advance genetic engineering techniques such as CRISPR-Cas systems, heterologous overexpression, and codon optimization have demonstrated significant potential in enhancing catalytic efficiency and reducing production costs. Integration of multi-omics data facilitates the elucidation of regulatory pathways and the optimization of enzyme formulations tailored to diverse biomass feedstocks. These combined approaches hold the potential to drive the development of sustainable and economically feasible solutions for the future of biofuel production.