Combination of a multiplatform metabolite profiling approach and chemometrics as a powerful strategy to identify bioactive metabolites in Lepidium meyenii (Peruvian maca).

ABSTRACT

Lepidium meyenii is an edible plant that has been used as a nutritional supplement worldwide due to its medicinal properties. However, most of the studies have focused on the pharmacological activities of the extracts rather than their chemical composition. Herein, we used a combination of a multiplatform metabolite profiling approach and chemometrics to identify bioactive metabolites in L. meyenii. Extracts obtained with ethyl acetate and ethanol showed the promising antioxidant, anti-glioma and antibacterial activities. Sixty metabolites were identified by HPLC-MS, whereas fifteen were identified by GC-MS. Partial least squares discriminant analysis (PLS-DA), hierarchical cluster analysis (HCA), and Variable Importance in Projection (VIP) successfully discriminated extracts obtained in different organic solvents from in natura dry roots and commercial product samples of L. meyenii. Additionally, correlation analysis allowed us to pinpoint potential candidates responsible for each biological activity tested for the extracts, which could be extrapolate for other food-related species.