Differentiation between Cistus L. (Sub-) Species (Cistaceae) Using NMR Metabolic Fingerprinting - Moosmang, Simon; Sturm, Sonja; Novak, Johannes; Lukas, Brigitte; Stuppner, Hermann (Planta Medica, 2020)
The genus Cistus is taxonomically complex, as taxonomic classification of individual species based on morphological criteria is often difficult and ambiguous. However, specific species contain valuable natural products, especially terpenoids and polyphenols, which exert various biological effects and might therefore be used for treatment of a broad array of disorders. Hence, a fast and reliable method for clear identification of different Cistus (sub-) species is required. Approaches for analysis of secondary metabolite profiles, e.g., with NMR, might remedy the challenging classification of Cistus (sub-) species and help to identify specific markers for differentiation between them. In the present study, 678 samples from wild-growing Cistus populations, including 7 species and 6 subspecies/varieties thereof, were collected in 3 years from populations in 11 countries all over the Mediterranean basin. Samples were extracted with buffered aqueous methanol and analysed with NMR. From the resulting 1D-1H-NOESY and J-Res profile spectra, marker signals or spectral regions for the individual (sub-) species were identified with multivariate statistical tools. By examining the NMR profiles of these extracts, we were able to identify discriminators and specific markers for the investigated Cistus (sub-) species. Various influencing factors, like (sub-) species, wild harvestings of different populations from several countries, numerous collection sites, different years, and cultivation in greenhouses have been considered in this work. As the here identified markers are independent from these influencing factors, the results can be considered a robust model and might be used for future differentiation between Cistus (sub-) species.
Keywords: Cistus L.; Cistaceae; NMR-secondary metabolites; metabolic fingerprinting; chemotaxonomic classification