Exploring microbial natural products through NMR-based metabolomics.

IF 10.2 1区 化学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
De-Gao Wang, Jia-Qi Hu, Chao-Yi Wang, Teng Liu, Yue-Zhong Li, Changsheng Wu
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引用次数: 0

Abstract

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.

通过核磁共振代谢组学探索微生物天然产物。
覆盖:2000。01到2025年。对新药的需求激增导致对智能方法的需求增加,以帮助探索微生物天然产物(NPs)。尖端代谢组学擅长于从复杂混合物中迅速识别化合物,从而加速目标发现过程。尽管基于质谱的代谢组学已经成为该领域的主要研究方向,但相比之下,基于核磁共振的代谢组学的应用却严重滞后。在此,我们总结了过去二十年来一维和二维核磁共振技术在方法上的关键进步,特别是计算技术的发明和/或人工智能的引入,用于自动数据处理,这大大增强了基于核磁共振代谢组学分析粗微生物提取物的能力。初步分馏是提倡反卷积样品,从而提高检测灵敏度对次要成分掩盖了一个复杂的矩阵。特别是,基于核磁共振的代谢组学和基因组学的协同应用为生物合成基因簇与同源代谢物的关联提供了一种便利的方法,极大地提高了去复制的效率,从而有针对性地发现新化合物。列举了各种涉及不同化学骨架和/或生物合成逻辑的微生物NPs,以证明基于核磁共振的代谢组学的真正实力。总的来说,这篇综述旨在鼓励在微生物NP研究领域更广泛地采用基于核磁共振的代谢组学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Natural Product Reports
Natural Product Reports 化学-生化与分子生物学
CiteScore
21.20
自引率
3.40%
发文量
127
审稿时长
1.7 months
期刊介绍: Natural Product Reports (NPR) serves as a pivotal critical review journal propelling advancements in all facets of natural products research, encompassing isolation, structural and stereochemical determination, biosynthesis, biological activity, and synthesis. With a broad scope, NPR extends its influence into the wider bioinorganic, bioorganic, and chemical biology communities. Covering areas such as enzymology, nucleic acids, genetics, chemical ecology, carbohydrates, primary and secondary metabolism, and analytical techniques, the journal provides insightful articles focusing on key developments shaping the field, rather than offering exhaustive overviews of all results. NPR encourages authors to infuse their perspectives on developments, trends, and future directions, fostering a dynamic exchange of ideas within the natural products research community.
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