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<p>Fungal secondary metabolites (SMs) represent a vast reservoir of bioactive compounds with immense therapeutic, agricultural, and industrial potential. These small molecules, including antibiotics, immunosuppressants, and anticancer agents, are synthesized through dedicated biosynthetic gene clusters (BGCs) regulated by various epigenetic, transcriptional, and environmental mechanisms. However, their cryptic biosynthesis and low natural yields pose significant challenges for large-scale production. This review comprehensively analyzes the regulatory landscape governing fungal SMs biosynthesis, advanced OMICS-driven approaches for identification of cryptic BGCs, and significantly emphasizes strategies to enhance SMs production. Furthermore, the integration of statistical and computational models (e.g., response surface methodology, artificial neural networks) is discussed for optimizing fermentation processes. The review underscores the diverse applications of fungal SMs in pharmaceuticals, agriculture, and cosmetics, while advocating for interdisciplinary innovations in synthetic biology and AI-driven metabolic engineering to sustainably harness fungal biodiversity.</p>

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Regulation and induction of fungal secondary metabolites: a comprehensive review

  • 期刊论文

  • 发表日期：

    2025年7月1日

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  • Shaurya Prakash,
  • Hemlata Kumari,
  • Minakshi Sinha,
  • Antresh Kumar

摘要

Fungal secondary metabolites (SMs) represent a vast reservoir of bioactive compounds with immense therapeutic, agricultural, and industrial potential. These small molecules, including antibiotics, immunosuppressants, and anticancer agents, are synthesized through dedicated biosynthetic gene clusters (BGCs) regulated by various epigenetic, transcriptional, and environmental mechanisms. However, their cryptic biosynthesis and low natural yields pose significant challenges for large-scale production. This review comprehensively analyzes the regulatory landscape governing fungal SMs biosynthesis, advanced OMICS-driven approaches for identification of cryptic BGCs, and significantly emphasizes strategies to enhance SMs production. Furthermore, the integration of statistical and computational models (e.g., response surface methodology, artificial neural networks) is discussed for optimizing fermentation processes. The review underscores the diverse applications of fungal SMs in pharmaceuticals, agriculture, and cosmetics, while advocating for interdisciplinary innovations in synthetic biology and AI-driven metabolic engineering to sustainably harness fungal biodiversity.