Nontargeted Metabolomic Profiling of a Single <i>Paeonia Lactiflora</i> Plant and its Quality Marker Identification
Paeonia lactiflora Pall., a widely used medicinal plant in traditional Chinese medicine (TCM), has diverse therapeutic properties, though its chemical composition remains inadequately explored. This study employs nontargeted metabolomics to provide a comprehensive chemical profile of a single P. lactiflora plant using Orbitrap high-resolution, accurate-mass (HRAM) mass spectrometry. A total of 214 compounds are identified, including 45 previously unreported metabolites. These compounds, spanning classes such as glycosides, flavonoids, organic acids, and triterpenes, are detected across its seven parts (leaf, petiole, stem, flower, root, xylem in root, cortex in root), with the root showing the highest chemical diversity. Six root samples collected from traditional habitats are also analyzed to propose their quality markers. From 37 compounds common to all root samples, 8 compounds are proposed as potential quality markers based on their widespread presence and abundance across traditional growing regions. This research not only enriches the chemical understanding of P. lactiflora but also sets the foundation for future studies on its medicinal potential and quality control in pharmaceutical applications.
Authors
- Rongchun Han (ORCID: https://orcid.org/0000-0001-7520-9413)
- Jinmei Ou (ORCID: https://orcid.org/0000-0002-9336-8781)
- Chuanshan Jin
- Xiaohui Tong (ORCID: https://orcid.org/0000-0001-8815-1230)
- Lanmeng Yan
- Rui Guan (ORCID: https://orcid.org/0000-0001-8094-4420)
- Yanan Wu
Institutions
- Anhui University of Traditional Chinese Medicine (CN)
Publication Details
- Journal
- ChemistryOpen
- Published
- 2025-05-24
- DOI
- https://doi.org/10.1002/open.202400520
- Citations
- 3
- Primary Topic
- Traditional Chinese Medicine Analysis
- Type
- article
- Field-Weighted Citation Impact
- 7.14
Funders
- Anhui University
- Anhui University of Chinese Medicine
- Anhui Provincial Department of Science and Technology
- Joint Research Centre