Metabolomics of Withania somnifera (L.) Dunal: Advances and applications

Abstract

Ethnopharmacological relevance: Withania somnifera L. (Solanaceae), commonly known as Ashwagandha or Indian ginseng, is used in Ayurveda (Indian system of traditional medicine) for vitality, cardio-protection and treating other ailments, such as neurological disorders, gout, and skin diseases. Aim of the review: We present a critical overview of the information on the metabolomics of W. somnifera and highlight the significance of the technique for use in quality control of medicinal products. We have also pointed out the use of metabolomics to distinguish varieties and to identify best methods of cultivation, collection, as well as extraction. Material and methods: The relevant information on medicinal value, phytochemical studies, metabolomics of W. somnifera, and their applications were collected from a rigorous electronic search through scientific databases, including Scopus, PubMed, Web of Science and Google Scholar. Structures of selected metabolites were from the PubChem. Results: The pharmacological activities of W. somnifera were well documented. Roots are the most important parts of the plant used in Ayurvedic preparations. Stem and leaves also have a rich content of bioactive phytochemicals like steroidal lactones, alkaloids, and phenolic acids. Metabolomic studies revealed that metabolite profiles of W. somnifera depended on plant parts collected and the developmental stage of the plant, besides the season of sample collection and geographical location. The levels of withanolides were variable, depending on the morpho/chemotypes within the species of W. somnifera. Although studies on W. somnifera were initiated several years ago, the complexity of secondary metabolites was not realized due to the lack of adequate and fool-proof technology for phytochemical fingerprinting. Sophistications in chromatography coupled to mass spectrometry facilitated the discovery of several new metabolites. Mutually complementary techniques like LC-MS, GC-MS, HPTLC, and NMR were employed to obtain a comprehensive metabolomic profile. Subsequent data analyses and searches against spectral databases enabled the annotation of signals and dereplication of metabolites in several numbers without isolating them individually. Conclusions: The present review provides a critical update of metabolomic data and the diverse application of the technique. The identification of parameters for standardization and quality control of herbal products is essential to facilitate mandatory checks for the purity of formulation. Such studies would enable us to identify the best geographical location of plants and the time of collection. We recommend the use of metabolomic analysis of herbal products based on W. somnifera for quality control as well as the discovery of novel bioactive compounds.