Clustering of chemical profiles of Centella asiatica cultivars, grown in greenhouses, allows grouping of metabolites with similar production trends

Centella asiatica (L.) Urban (also known as “gotu kola”) is a perennial plant, used in traditional medicine for promoting resilience to central nervous system (CNS) disorders. C. asiatica is a tropical medicinal herb from the Apiaceae family and is native to Southeast Asian countries. The chemical composition and contaminant profile of commercial C. asiatica is variable. The goal of this study was to guide the future cultivation of organically grown C. asiatica for obtaining optimized plant materials for pre-clinical studies and clinical trials. Optimized plant materials in this case are defined as producing similar amounts of biologically active components as previously studied material. In this study, C. asiatica cultivars were grown in Central Oregon and their phytochemical compositions were examined. Four different cultivars were grown in climate-controlled greenhouses over three different vegetative propagation periods. Aerial parts of the plant were collected at four different harvest times: 8, 10, 12, and 14 weeks from growth initiation. The phytochemical composition of each cultivar was analyzed by liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS). Global metabolomic profiles allowed cultivar-specific compositional differences to be distinguished and production trends of phytochemical constituents to be analyzed using multinomial Bayesian hierarchical clustering and Self-Organizing Maps. Production trends of known bioactive phytoconstituents are reported here and will inform cultivation and harvest strategies to obtain C. asiatica materials of desired composition for preclinical and clinical studies. The computational methods for analyzing cultivar-specific and time-course dependent metabolomic profiles can be applied to other medicinal plant cultivation efforts to optimize cultivation and harvest practices.