结合代谢组学和机器学习分析中国梧桐地理分化的化学标记和生态调控机制。

IF 3.7 3区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Metabolites Pub Date : 2025-06-20 DOI:10.3390/metabo15070423
Cong Wang, Ke Che, Guanglei Zhang, Hao Yu, Junsong Wang
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引用次数: 0

摘要

背景:中药中药疗效与地理环境的关系。(T. chinense Turcz.),一种传统的中国草药,仍未被系统地开发。本研究将代谢组学、机器学习和生态因子分析相结合,阐明中国柽柳次生代谢物的地理变异模式和调控机制。来自安徽、河南和山西。方法:采用代谢组学分析方法。样本来自安徽、河南和山西三个地理来源。机器学习算法(随机森林,LASSO回归)通过交叉分析识别区域特异性生物标志物。代谢途径富集采用MetaboAnalyst 5.0进行目标预测。分光光度法测定抗氧化活性(清除DPPH/羟基自由基)。环境相关分析采用冗余分析、Mantel检验和Pearson相关性将19个WorldClim变量合并。结果:共鉴定出43种地理标记化合物(主要为黄酮类化合物和生物碱类化合物)。随机森林和LASSO回归算法确定了各产区的核心标记:安徽(4个)、河南(6个)和山西(3个)。代谢途径富集分析表明,这些标志物通过神经活性配体-受体相互作用和PI3K-Akt信号通路发挥药理作用。冗余分析表明,安徽样品的抗氧化活性(DPPH和羟基自由基清除率)明显高于其他地区,这与稳定的低温环境(年平均温度)和降水模式密切相关。结论:本研究建立了首个中国柽柳地理特异性分子标记体系。表明地理环境对代谢特征和生物活性有重要影响。研究结果为地物药材的质量控制标准提供了科学依据,并为可持续栽培提供了植物-环境相互作用的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating Metabolomics and Machine Learning to Analyze Chemical Markers and Ecological Regulatory Mechanisms of Geographical Differentiation in Thesium chinense Turcz.

Background: The relationship between medicinal efficacy and the geographical environment in Thesium chinense Turcz. (T. chinense Turcz.), a traditional Chinese herb, remains systematically unexplored. This study integrates metabolomics, machine learning, and ecological factor analysis to elucidate the geographical variation patterns and regulatory mechanisms of secondary metabolites in T. chinense Turcz. from Anhui, Henan, and Shanxi Provinces.

Methods: Metabolomic profiling was conducted on T. chinense Turcz. samples collected from three geographical origins across Anhui, Henan, and Shanxi Provinces. Machine learning algorithms (Random Forest, LASSO regression) identified region-specific biomarkers through intersection analysis. Metabolic pathway enrichment employed MetaboAnalyst 5.0 with target prediction. Antioxidant activity (DPPH/hydroxyl radical scavenging) was quantified spectrophotometrically. Environmental correlation analysis incorporated 19 WorldClim variables using redundancy analysis, Mantel tests, and Pearson correlations.

Results: We identified 43 geographical marker compounds (primarily flavonoids and alkaloids). Random forest and LASSO regression algorithms determined core markers for each production area: Anhui (4 markers), Henan (6 markers), and Shanxi (3 markers). Metabolic pathway enrichment analysis revealed these markers exert pharmacological effects through neuroactive ligand-receptor interaction and PI3K-Akt signaling pathways. Redundancy analysis demonstrated Anhui samples exhibited significantly higher antioxidant activity (DPPH and hydroxyl radical scavenging rates) than other regions, strongly correlating with stable low-temperature environments (annual mean temperature) and precipitation patterns.

Conclusions: This study established the first geo-specific molecular marker system for T. chinense Turcz., demonstrating that the geographical environment critically influences metabolic profiles and bioactivity. Findings provide a scientific basis for quality control standards of geo-authentic herbs and offer insights into plant-environment interactions for sustainable cultivation practices.

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来源期刊
Metabolites
Metabolites Biochemistry, Genetics and Molecular Biology-Molecular Biology
CiteScore
5.70
自引率
7.30%
发文量
1070
审稿时长
17.17 days
期刊介绍: Metabolites (ISSN 2218-1989) is an international, peer-reviewed open access journal of metabolism and metabolomics. Metabolites publishes original research articles and review articles in all molecular aspects of metabolism relevant to the fields of metabolomics, metabolic biochemistry, computational and systems biology, biotechnology and medicine, with a particular focus on the biological roles of metabolites and small molecule biomarkers. Metabolites encourages scientists to publish their experimental and theoretical results in as much detail as possible. Therefore, there is no restriction on article length. Sufficient experimental details must be provided to enable the results to be accurately reproduced. Electronic material representing additional figures, materials and methods explanation, or supporting results and evidence can be submitted with the main manuscript as supplementary material.
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