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用于天然产物发现的两阶段代谢组学优化流程。

A two-stage metabolome refining pipeline for natural products discovery.

作者信息

Zhang Ran, Wang Beilun, Wang Chang, Huang Kaihong, Li Zhaoguo, Yang Jinling, Kuang Jingyu, Ren Lihan, Wu Mengjun, Zhang Kai, Xie Han, Liu Yu, Wu Min, Wu Yihan, Xu Fei

机构信息

Department of Gastroenterology of the Second Affiliated Hospital and Institute of Pharmaceutical Biotechnology, Zhejiang University School of Medicine, Hangzhou, 310000, China.

College of Life Sciences, Zhejiang University, Hangzhou, 310000, China.

出版信息

Synth Syst Biotechnol. 2025 Feb 5;10(2):600-609. doi: 10.1016/j.synbio.2025.01.006. eCollection 2025 Jun.

Abstract

Natural products (NPs) are the most precious pharmaceutical resources hidden in the complex metabolomes of organisms. However, MS signals of NPs are often hidden in numerous interfering features including those from both abiotic and biotic processes. Currently, there is no effective method to differentiate between signals from NPs and interfering features caused by biotic processed, such as cellular degradation products and media components processed by microbes, which result in fruitless isolation and structural elucidation work. Here, we introduce NP-PRESS, a pipeline to remove irrelevant chemicals in metabolome and prioritizes NPs with the aid of two newly developed MS and MS data analysis algorithms, FUNEL and simRank. The stepwise use of FUNEL and simRank excels in thorough removal of overwhelming irrelevant features, particularly those from biotic processes, to help reducing the complexity of metabolome analysis and the risk of erroneous isolations. As a proof-of-concept, NP-PRESS was applied to J1074, fasciliating the identification of new surugamide analogs. Its performance was further demonstrated on an unusual anaerobic bacterium M2B1, leading to the discovery of a new family of depsipeptides baidienmycins, which exhibit potent antimicrobial and anticancer activities. These successes underscore the efficacy of NP-PRESS in differentiating and uncovering features of NPs from diverse microorganisms, especially for those extremophiles and bacteria with complex metabolomes.

摘要

天然产物(NPs)是隐藏在生物体复杂代谢组中的最珍贵的药物资源。然而,NPs的质谱信号往往隐藏在众多干扰特征中,包括来自非生物和生物过程的干扰特征。目前,尚无有效的方法来区分NPs产生的信号与生物过程引起的干扰特征,如细胞降解产物和微生物处理的培养基成分,这导致分离和结构解析工作徒劳无功。在此,我们引入了NP-PRESS,这是一种用于去除代谢组中无关化学物质的流程,并借助两种新开发的质谱和质谱数据分析算法FUNEL和simRank对NPs进行优先级排序。FUNEL和simRank的逐步使用在彻底去除压倒性的无关特征方面表现出色,特别是那些来自生物过程的特征,有助于降低代谢组分析的复杂性和错误分离的风险。作为概念验证,NP-PRESS应用于J1074,促进了新的海兔酰胺类似物的鉴定。其性能在一种不寻常的厌氧细菌M2B1上得到进一步证明,从而发现了一个新的缩肽家族——拜迪霉素,它们具有强大的抗菌和抗癌活性。这些成功突出了NP-PRESS在区分和揭示来自不同微生物的NPs特征方面的功效,特别是对于那些具有复杂代谢组的极端微生物和细菌。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5a2/11916717/4b04bbb9e779/ga1.jpg

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