Strategies for mining new secondary metabolites from fungi: from Classical Approaches to Genomics-Based Mining

Authors

  • Li-Juan Zhang School of Food and Pharmaceutical Engineering, Guizhou Institute of Technology, Guiyang 550003, China https://orcid.org/0000-0002-3234-6757
  • Ruvishika S. Jayawardena School of Science, Mae Fah Luang University, Chiang Rai 57100, Thailand
  • Ausana Mapook Center of Excellence in Fungal Research, Mae Fah Luang University, Chiang Rai 57100, Thailand
  • Ning-Guo Liu School of Food and Pharmaceutical Engineering, Guizhou Institute of Technology, Guiyang 550003, China
  • Jian Ma School of Food and Pharmaceutical Engineering, Guizhou Institute of Technology, Guiyang 550003, China
  • Xing-Juan Xiao School of Food and Pharmaceutical Engineering, Guizhou Institute of Technology, Guiyang 550003, China
  • Walker Arttapon School of Science, Mae Fah Luang University, Chiang Rai 57100, Thailand
  • Yuan-Ping Xiao
  • Kevin D. Hyde School of Science, Mae Fah Luang University, Chiang Rai 57100, Thailand
  • Yong-Zhong Lu School of Food and Pharmaceutical Engineering, Guizhou Institute of Technology, Guiyang 550003, China https://orcid.org/0000-0002-1033-5782
  • Jing-Zu Sun State Key Laboratory of Microbial Diversity and Innovative Utilization, Chinese Academy of Sciences, Beijing 100101, China https://orcid.org/0000-0003-1893-1869

Keywords:

Fungal secondary metabolites, Genome mining, Biosynthetic gene clusters (BGCs), Dereplication, Culture condition optimization, Natural product discovery

Abstract

Fungi are prolific producers of structurally diverse secondary metabolites, which play significant ecological and pharmacological roles. However, the rate of discovering new fungal natural products has slowed in recent decades, highlighting the need for innovative approaches to unlock their biosynthetic potential. Recent advances in genome sequencing and bioinformatics have revealed the complexity of fungal biosynthetic gene clusters, enabling the development of strategies to activate silent pathways and improve the efficiency of compound identification. This review synthesizes current methodologies for mining novel fungal metabolites, including classical approaches that modify culture conditions, genomics-based genome mining, and dereplication techniques to efficiently distinguish known from unknown compounds. We further highlight integrated, multi-strategy frameworks that maximize discovery efficiency and discuss emerging directions such as multi-omics integration and machine learning-assisted pathway prediction. By providing a comprehensive and forward-looking overview, this work aims to guide the effective exploitation of fungal resources in the search for new natural products.

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Published

2026-05-26

How to Cite

Zhang, L., Ruvishika, J., Mapook, A., Liu, N.-G., Ma, J., Xiao, X.-J., Arttapon, W., Xiao, Y.-P., Hyde, K. D., Lu, Y., & Sun, J.-Z. (2026). Strategies for mining new secondary metabolites from fungi: from Classical Approaches to Genomics-Based Mining. PhytoMycology, 2(1). retrieved from https://li04.tci-thaijo.org/index.php/Phytomycol/article/view/8839

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Section

Review