Wang De-Gao, Hu Jia-Qi, Wang Chao-Yi, Liu Teng, Li Yue-Zhong, Wu Changsheng
State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, 266237 Qingdao, P. R. China.
Nat Prod Rep. 2025 Jun 12. doi: 10.1039/d4np00065j.
Covering: 2000. 01 to 2025. 03The soaring demand for novel drugs has led to an increase in the requirement for smart methods to aid in the exploration of microbial natural products (NPs). Cutting-edge metabolomics excels at prompt identification of compounds from complex mixtures and accordingly accelerates the targeted discovery process. Although MS-based metabolomics has become a staple in this field, the utilization of NMR-based metabolomics has severely trailed in comparison. Herein, we summarize the key methodological advancements in 1D and 2D NMR techniques in the past two decades, especially for the invention of computational technologies and/or introduction of artificial intelligence for automated data processing, which significantly strengthen the ability of NMR-based metabolomics to analyze crude microbial extracts. Preliminary fractionation is advocated to deconvolute samples and thus enhance detection sensitivity towards minor components overshadowed by a complex matrix. Particularly, the synergistic application of NMR-based metabolomics and genomics provides an expedient approach to correlate biosynthetic gene clusters with cognate metabolites, greatly improving the efficiency of dereplication and, thus, targeted discovery of novel compounds. A variety of microbial NPs involving distinct chemical skeletons and/or biosynthetic logics are enumerated to prove the genuine prowess of NMR-based metabolomics. Overall, this review aims to encourage the broader adoption of NMR-based metabolomics in the realm of microbial NP research.
2000年1月至2025年3月
对新型药物的需求激增,导致对有助于探索微生物天然产物(NPs)的智能方法的需求增加。前沿代谢组学擅长从复杂混合物中快速鉴定化合物,从而加速靶向发现过程。尽管基于质谱的代谢组学已成为该领域的主要方法,但基于核磁共振(NMR)的代谢组学的应用相比之下却严重滞后。在此,我们总结了过去二十年中一维和二维NMR技术的关键方法进展,特别是计算技术的发明和/或人工智能在自动化数据处理中的引入,这显著增强了基于NMR的代谢组学分析微生物粗提物的能力。提倡进行初步分级分离以解卷积样品,从而提高对被复杂基质掩盖的微量成分的检测灵敏度。特别是,基于NMR的代谢组学与基因组学的协同应用提供了一种便捷的方法,将生物合成基因簇与同源代谢物相关联,大大提高了去重复的效率,从而实现新型化合物的靶向发现。列举了多种具有不同化学骨架和/或生物合成逻辑的微生物NPs,以证明基于NMR的代谢组学的真正实力。总体而言,本综述旨在鼓励在微生物NP研究领域更广泛地采用基于NMR的代谢组学。