Helichrysum species, of which 35% are native to South Africa, are renowned for their diverse medicinal properties, yet their chemical composition remains largely unexplored. As such, continuous efforts are needed to comprehensively characterize the phytochemistry of Helichrysum species which will subsequently contribute to the discovery and exploration of Helichrysum-derived natural products for drug discovery. Thus, a computational metabolomics work is reported herein to comprehensively characterize the metabolic landscape of three medicinal species (H. italicum, H. petiolare, and H. splendidum), which are less studied. The metabolites were extracted using hexane, ethyl acetate, and methanol and analyzed on a liquid chromatography-tandem mass spectrometry (LC-MS/MS) system. Different solvents were utilized to increase metabolome coverage in Helichrysum species. Spectral data were mined using molecular networking (MN) strategies. The results revealed that multiple extraction methods provide a more comprehensive analysis of the metabolome of the three plants. The measured metabolome of Helichrysum species is rich in phenylpropanoids, lipids and lipid-like molecules, pointing to a rich chemistry with potential bioactivities. Comparative analysis of the H. italicum, H. petiolare and H. splendidum metabolomes revealed that the flavonoid glucoside and triterpenoid profiles of the three species differ distinctively. These results expand the knowledge base on the chemistry of Helichrysum plants and provide deconvoluted details of the various chemical classes that differentially define the metabolome of the Helichrysum plants. Such actionable insights point to Helichrysum's potential as a valuable source of natural compounds with promising medicinal properties.
Mapping the Helichrysum metabolome: uncovering species-specific chemistry through an AI-guided LC-MS/MS workflow.
M. Lephatsi,M. Choene,A. Kappo,N. Madala,F. Tugizimana
Published 2025 in Molecular Omics
ABSTRACT
PUBLICATION RECORD
- Publication year
2025
- Venue
Molecular Omics
- Publication date
2025-11-10
- Fields of study
Medicine, Chemistry, Environmental Science, Computer Science
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- External record
- Source metadata
Semantic Scholar, PubMed
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