Quantitation of Usnic Acid from Three Usnea Species, Its Commercial Formulations Using High-Performance Thin-Layer Chromatography-Mass Spectrometry (HPTLC-MS) and Their Metabolite Profiling Using UPLC-QTof-MSE.
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Abstract
Background: The genus Usnea (Parmeliaceae; lichenized Ascomycetes) is pale grayish-green fruticose lichens, which grow as leafless mini-shrubs and comprise about 360 species. Most of the Usnea species are edible and are utilized in preparation of traditional foods as well as in medicines to combat a wide range of ailments.
Objective: This study aimed to quantify usnic acid (UA) in three Usnea spp. (Usnea ghattensis [UG], Usnea orientalis [UO], and Usnea undulata [UU]) using HPTLC-MS. Additionally, chemical profiling of acetone extracts using UPLC-QTof-MSE resulted in the identification of 16 compounds based on their MS/MS fragmentation patterns.
Methods: Hyphenated techniques, HPTLC-MS, and UPLC-QTof-MSE have been proposed to quantify UA and analyze metabolites in crude extracts qualitatively. This method allowed tentative characterization of metabolites from Usnea spp.
Results: The quantification study showed excellent linearity for UA at 0.25-1 µg/band with a correlation coefficient r2 > 0.99, and the LOD and LOQ were found to be 51.7 and 156.6 ng/band, respectively. Furthermore, UPLC-QTof-MSE analysis of crude extracts led to identification of lichen secondary metabolites through their exact molecular masses and MS/MS fragmentation studies.
Conclusion: The present study summarizes an HPTLC method for quantification of UA in three different Usnea spp. Additionally, two herbal formulations containing Usnea spp. as an ingredient, the developed method was validated as per the ICH guidelines and further UPLC-QTof-MSE analysis facilitated tentative characterization of 16 different secondary metabolites based on their MS/MS fragmentation patterns.
Highlights: A rapid HPTLC method for quantification of UA in three different Usnea spp., along with two herbal formulations, and metabolite profiling using UPLC-QTof-MSE.
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