Recent biotechnological advances in bioprospecting secondary metabolites from endolichenic fungi for drug discovery applications

Endolichenic fungi (ELF) are symbiotic organisms residing in lichens. Since the initial report of its application in natural products and drug discovery, they have emerged as unique valuable sources of compounds with a wide range of structural diversity and biological activities. In this review, we critically examine current strategies to expand ELF metabolite diversity, with emphasis on the One Strain, Many Compounds (OSMAC) approach and metabolomics-guided profiling. We highlight how co-culture systems, epigenetic modifiers, and advanced data acquisition platforms can open new avenues for chemical space exploration. Genomic and transcriptomic studies, though still limited in ELF, reveal untapped biosynthetic potential and point toward integrative omics pipelines. Recent computational and artificial intelligence tools further accelerate genome–metabolome mining, structural elucidation, and prediction of bioactivity. We propose a forward-looking framework that combines OSMAC, integrative omics, and AI to maximize the natural product bioprospecting potential of ELF, while also uncovering their ecological roles within the lichen holobiome.

地衣内生真菌（Endolichenic fungi，ELF）是栖息于地衣体内的共生生物。自其在天然产物与药物研发领域的应用被首次报道以来，这类真菌已成为兼具丰富结构多样性与多样生物活性的独特珍贵化合物来源。本综述批判性评析了当前用于拓展地衣内生真菌代谢物多样性的研究策略，重点聚焦于一株菌多种化合物（One Strain, Many Compounds, OSMAC）策略与代谢组学引导的代谢谱分析方法。本综述阐明了共培养体系、表观遗传调控剂以及先进的数据采集平台如何为化学空间探索开辟新路径。尽管针对地衣内生真菌的基因组学与转录组学研究仍较为有限，但已有研究揭示了其未被发掘的生物合成潜力，并指明了整合组学研究流程的发展方向。近年来，各类计算工具与人工智能工具进一步加速了基因组-代谢组挖掘、化合物结构解析以及生物活性预测的进程。本研究提出了一套融合OSMAC策略、整合组学技术与人工智能的前瞻性研究框架，以期最大化地衣内生真菌的天然产物生物勘探潜力，同时揭示其在地衣全共生体中的生态功能。