Discrimination of Mentha species grown in different geographical areas of Algeria using 1H-NMR-based metabolomics

Abstract

¹H-NMR-based metabolomics have been applied to identify potential NMR-markers and biomarkers capable of distinguishing, qualifying and classifying three Mentha species:- Mentha pulegium L., Mentha × rotundifolia (L.) Huds., Mentha spicata L., and their ecotypes. Samples of the 3 species were collected in seven different locations in Algeria, with the aim to establish a quality control protocol based on the use of NMR fingerprint profiles of polar extracts. NMR data indicate that the identification of the Mentha genus can be confirmed by the presence of the doublet proton signals with identical coupling constants at δ 7.49 (d, 15.9 Hz) and δ 6.29 (d, 15.9 Hz); these correspond to the protons of the double-bond conjugated to the ester group of rosmarinic acid, a bioactive compound found in all three species. Differences in NMR proton chemical shifts and/or signal intensities were clearly demonstrated on the orthogonal projections to latent structures discriminating analysis (OPLS-DA). Several potential biomarkers discriminating the three Mentha species were originated using S-plots, loading score plots, NMR data analysis and literature search. These discriminating signals point to glycosylated flavonols, oxygenated terpenoids and hydrocarbon terpenoids to distinguish M. pulegium, M. × rotundifolia and M. spicata, respectively. Within the same species, Principal Component Analysis (PCA) scores clearly discriminated the metabolite content according to regions in which the plants were grown. The 6 zones in which Mentha pulegium samples were harvested were clearly separated along either or both PC1 and PC2; by contrast, the harvesting locations were divided into two groups along PC1 for both M. × rotundifolia and M. spicata. The total antioxidant activity of the Mentha species was impacted by the abiotic factors of the different regions.

Keywords: Mentha pulegium; Mentha spicata; Mentha × rotundifolia; Multivariate statistical analysis; NMR-based metabolomics; Rosmarinic acid.