Metabolomics-based profiling of five Salvia L. (Lamiaceae) species using untargeted data analysis workflow

doi:10.1002/pca.3423

KIB OpenIR

	Metabolomics-based profiling of five Salvia L. (Lamiaceae) species using untargeted data analysis workflow
	Kharazian, Navaz; Dehkordi, Farzaneh Jafari; Xiang, Chun-Lei
	2025
发表期刊	PHYTOCHEMICAL ANALYSIS
ISSN	0958-0344
卷号	36 期号:1 页码:113-143
摘要	Introduction: The genus Salvia L., a member of the family Lamiaceae, is a keystone genus with a wide range of medicinal properties. It possesses a rich metabolite source that has long been used to treat different disorders. Objectives: Due to a deficiency of untargeted metabolomic profiling in the genus Salvia, this work attempts to investigate a comprehensive mass spectral library matching, computational data annotations, exclusive biomarkers, specific chemotypes, intraspecific metabolite profile variation, and metabolite enrichment by a case study of five medicinal species of Salvia. Material and methods: Aerial parts of each species were subjected to QTRAP liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis workflow based on untargeted metabolites. A comprehensive and multivariate analysis was acquired on the metabolite dataset utilizing MetaboAnalyst 6.0 and the Global Natural Products Social Molecular Networking (GNPS) Web Platform. Results: The untargeted approach empowered the identification of 117 metabolites by library matching and 92 nodes annotated by automated matching. A machine learning algorithm as substructural topic modeling, MS2LDA, was further implemented to explore the metabolite substructures, resulting in four Mass2Motifs. The automated library newly discovered a total of 23 metabolites. In addition, 87 verified biomarkers of library matching, 58 biomarkers of GNPS annotations, and 11 specific chemotypes were screened. Conclusion: Integrative spectral library matching and automated annotation by the GNPS platform provide comprehensive metabolite profiling through a workflow. In addition, QTRAP LC-MS/MS with multivariate analysis unveiled reliable information about inter and intraspecific levels of differentiation. The rigorous investigation of metabolite profiling presents a large-scale overview and new insights for chemotaxonomy and pharmaceutical studies.
DOI	10.1002/pca.3423
WOS记录号	WOS:001272249000001
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.kib.ac.cn/handle/151853/76288
专题	中国科学院昆明植物研究所
推荐引用方式 GB/T 7714	Kharazian, Navaz,Dehkordi, Farzaneh Jafari,Xiang, Chun-Lei. Metabolomics-based profiling of five Salvia L. (Lamiaceae) species using untargeted data analysis workflow[J]. PHYTOCHEMICAL ANALYSIS,2025,36(1):113-143.
APA	Kharazian, Navaz,Dehkordi, Farzaneh Jafari,&Xiang, Chun-Lei.(2025).Metabolomics-based profiling of five Salvia L. (Lamiaceae) species using untargeted data analysis workflow.PHYTOCHEMICAL ANALYSIS,36(1),113-143.
MLA	Kharazian, Navaz,et al."Metabolomics-based profiling of five Salvia L. (Lamiaceae) species using untargeted data analysis workflow".PHYTOCHEMICAL ANALYSIS 36.1(2025):113-143.

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10.1002_pca.3423.pdf（7851KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载