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

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.

Structural diversity, biosynthetic aspects, and LC-HRMS data compilation for the identification of bioactive compounds of Lepidium meyenii.

Lepidium meyenii is widely used as a food supplement because of its medicinal properties and nutritional value. Several studies have described the identification of its metabolites and LC-HRMS analysis is one of the most frequently used analytical tool to assess plant extract metabolome. Nevertheless, proper and reliable metabolite identification is essential for such metabolomics studies. Although HRMS distinguishes even minor changes in the metabolites structures, highly specialized secondary metabolites might not be present on available databases imposing serious obstacles for metabolite identification This review discusses the structural diversity and biosynthetic aspects of 101 compounds previously identified in L. meyenii. More importantly, we have compiled the available information on expected and experimental high-resolution masses of L. meyenii compounds. This will help upcoming metabolomics studies not only of L. meyenii but also other plant species by providing the necessary tools to perform proper and reliable identification of their bioactive compounds.