后基因组时代微生物天然产物高效发掘体系设计与展望  

Design and Prospects of an Efficient Mining Pipeline for Microbial Natural Products in the Post-Genome Era

作　　者：潘华奇[1] PAN Hua-qi(Institute of Applied Ecology,Chinese Academy of Science,Shenyang 110016)

机构地区：[1]中国科学院沈阳应用生态研究所,辽宁沈阳110016

出　　处：《微生物学杂志》2022年第3期1-14,共14页Journal of Microbiology

基　　金：国家自然科学基金面上项目(31872036,41576136);中国科学院战略性先导科技专项A类(XDA28090300);中科院青年创新促进会会员项目(2018229);辽宁省兴辽英才计划项目(XLYC1807268)。

摘　　要：微生物天然产物具有丰富的化学结构多样性和诱人的生物活性,持续启迪着创新医药和农药的发现。近年来,随着高通量测序技术的快速发展,巨大的微生物基因组数据揭示了多样生物合成和新颖天然产物的潜能远高于以前的认知。然而,如何高效地激活隐性的生物合成基因簇(BGCs)并识别相应的化合物,以及避免已知代谢产物的重复发现等挑战依然严峻。本文描述了面对这些问题时基因组学、生物信息学、机器学习、代谢组学、基因编辑和合成生物学等新技术在发现药用先导化合物过程中提供的机遇;总结并论述了在潜力菌株优选、BGCs的生物信息学预测、沉默BGCs的高效激活以及目标产物的识别和跟踪方面的新见解;提出了基于潜力菌株选择和多组学挖掘技术从微生物天然产物中高效发现先导结构的系统线路(SPLSD),并讨论了未来天然产物药用先导发现的机遇和挑战。Microbial natural products possess enormous diversity of chemical structures and fascinating biological activities,which continue to inspire novel discoveries in medicine and pesticide.In recent years,with the rapid development of high-throughput sequencing technology,massive microbial genomic data have revealed a much greater potential for the biosynthesis of diverse and novel natural products than previously appreciated.However,activating cryptic biosynthetic gene clusters(BGCs)and identifying the corresponding compounds,as well as avoiding rediscovery of known metabolites are still challenging.Here,this paper describes the new technologies such as genomics,bioinformatics,machine learning,metabolomics,gene editing and synthetic biology in the discovery of drug lead compounds to address the aforementioned problems.New insights into prioritizing promising strains,bioinformatics prediction of BGCs,efficient activation of silent BGCs,and identification and tracking of target products are summarized and presented.Finally,a systematic pipeline for efficient lead structure discovery from microbial natural products by promising strain selection and multi-omics mining(SPLSD)is established,and future opportunities and challenges in workflows of natural product drug lead discovery are discussed.

关 键 词：潜力菌株 先导化合物 泛生物合成基因簇 沉默基因簇 基因组挖掘 代谢组学 次级代谢产物 合成生物学 

分 类 号：Q936[生物学—微生物学]