Feature-Based Molecular Networking Approach for Exploring the Chemical Profile and Quantification of Polyphenols in
Heba Handoussa1,2, Livhuwani Mafhala2, Sukhmanpreet Kaur2
1Department of Pharmaceutical Biology, German University in Cairo GUC, New Cairo City, Cairo 11835, Egypt.
None:
Stevia rebaudiana (Bertoni) (SR) is a natural sweetener rich in bioactive diterpene glycosides and therapeutic metabolites. Despite intensive research, its full metabolomic profile has not yet been revealed. In the current research, tandem MS data obtained from UHPLC-ESI-Orbitrap-high-resolution mass spectrometry were utilized to generate a feature-based molecular networking (FBMN) via variable data-dependent acquisition (DDA) mode to qualitatively and quantitatively annotate the phytoconstituents. Three solid-to-solvent ratios (1%, 4%, and 8% w/v) of SR aqueous extracts were used. FBMN analysis through the Global Natural Products Social Molecular Networking (GNPS2) platform yielded 7956 nodes, 2903 edges, and 315 molecular families. Fourteen compounds, including three glycosides, five stevioside isomers, and six hydroxycinnamic acid derivatives, were annotated to regioisomeric levels for the first time. Targeted quantification of eight major metabolites related to the classes under study revealed significant concentration-dependent variations. These findings highlight the phytochemical map with insights into the interconnected biosynthetic pathways.
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