Non-targeted metabolomic profiling of Cremastra appendiculata providing insights for phytochemical analyses

Abstract

Background. Cremastra appendiculata (D. Don) Makino, known as ‘‘Shan Cigu’’ in China, is a valuable medicinal plant historically employed for its antibacterial and anti-inflammatory properties. However, its comprehensive metabolome remains underexplored, hindering the establishment of standardized quality control. Methods. In this study, a non-targeted metabolomics approach based on the Thermo Fisher Orbitrap Exploris 120 LC-MS (Liquid Chromatography-Mass Spectrometry) platform was employed to systematically profile the metabolites of C. appendiculata. Results. A total of 174 compounds were annotated through a dual-validation workflow integrating Compound Discoverer 3.3 and manual tandem mass spectrometry spectral verification. Orthogonal partial least squares discriminant analysis prioritized 30 candidate quality markers, of which, six were further validated through network pharmacology-based bioactivity screening. Hierarchical clustering analysis revealed distinct metabolic patterns across the different tissues (roots, pseudobulbs, and leaves), establishing a tissue-specific chemical atlas. The integration of chemometric, network pharmacological, and chemotaxonomic analyses resulted in a robust, molecularly guided quality control framework, providing novel insights for phytochemical research and medical applications of C. appendiculata.