Cong Wang, Ke Che, Guanglei Zhang, Hao Yu, Junsong Wang
{"title":"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。","authors":"Cong Wang, Ke Che, Guanglei Zhang, Hao Yu, Junsong Wang","doi":"10.3390/metabo15070423","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The relationship between medicinal efficacy and the geographical environment in <i>Thesium chinense</i> Turcz. (<i>T. chinense</i> 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 <i>T. chinense</i> Turcz. from Anhui, Henan, and Shanxi Provinces.</p><p><strong>Methods: </strong>Metabolomic profiling was conducted on <i>T. chinense</i> 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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>This study established the first geo-specific molecular marker system for <i>T. chinense</i> 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.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 7","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrating Metabolomics and Machine Learning to Analyze Chemical Markers and Ecological Regulatory Mechanisms of Geographical Differentiation in <i>Thesium chinense</i> Turcz.\",\"authors\":\"Cong Wang, Ke Che, Guanglei Zhang, Hao Yu, Junsong Wang\",\"doi\":\"10.3390/metabo15070423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The relationship between medicinal efficacy and the geographical environment in <i>Thesium chinense</i> Turcz. (<i>T. chinense</i> 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 <i>T. chinense</i> Turcz. from Anhui, Henan, and Shanxi Provinces.</p><p><strong>Methods: </strong>Metabolomic profiling was conducted on <i>T. chinense</i> 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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>This study established the first geo-specific molecular marker system for <i>T. chinense</i> 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.</p>\",\"PeriodicalId\":18496,\"journal\":{\"name\":\"Metabolites\",\"volume\":\"15 7\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metabolites\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.3390/metabo15070423\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metabolites","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3390/metabo15070423","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
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.
MetabolitesBiochemistry, 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.