Mapping the Helichrysum metabolome: uncovering species-specific chemistry through an AI-guided LC-MS/MS workflow

Abstract

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.

Graphical abstract: Mapping the Helichrysum metabolome: uncovering species-specific chemistry through an AI-guided LC-MS/MS workflow

Supplementary files

Article information

Article type
Research Article
Submitted
02 Jun 2025
Accepted
23 Sep 2025
First published
10 Nov 2025
This article is Open Access
Creative Commons BY license

Mol. Omics, 2025, Advance Article

Mapping the Helichrysum metabolome: uncovering species-specific chemistry through an AI-guided LC-MS/MS workflow

M. M. Lephatsi, M. S. Choene, A. P. Kappo, N. E. Madala and F. Tugizimana, Mol. Omics, 2025, Advance Article , DOI: 10.1039/D5MO00118H

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