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

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 is utilized in preparation of traditional foods as well as in medicines to combat wide range of ailments. Objective The goal of this work was to quantify usnic acid in three Usnea spp. [Usnea ghattensis (UG), Usnea orientalis (UO) and Usnea undulata (UU)] using HPTLC-MS and chemical profiling of acetone extracts using UPLC-QTof-MSE resulted in the identification of sixteen compounds based on their MS/MS fragmentation patterns. Methods Hyphenated techniques, HPTLC-MS and UPLC-QTof-MSE have been proposed to quantify usnic acid and analysis of metabolites in the crude extracts qualitatively. This method allowed tentative characterization of metabolites from Usnea spp. Results The quantification study showed the excellent linearity of the usnic acid at 0.25–1 µg/band with a correlation coefficient r 2>0.99, and LOD, LOQ was found to be 51.7 and 156.6 ng/band, respectively. Further, UPLC-QTof-MSE analysis of crude extract led identification of lichen substances through their exact molecular masses and MS/MS fragmentation studies. Conclusions The present study summarizes HPTLC method for quantification of usnic acid in three different Usnea spp. Along with two herbal formulations containing Usnea spp. as the ingredient and developed method was validated as per the ICH guidelines and further UPLC-QTof-MSE analysis provides characterization of the sixteen different secondary metabolites based on their mass fragmentation studies. Highlights Rapid HPTLC method for quantification of usnic acid in three different Usnea spp. along with two herbal formulations and metabolite profiling using UPLC-QTof-MSE.