The Combination of Untargeted Metabolomics and Machine Learning Predicts the Biosynthesis of Phenolic Compounds in Bryophyllum Medicinal Plants (Genus Kalanchoe).

ABSTRACT: Phenolic compounds constitute an important family of natural bioactive compounds responsible for the medicinal properties attributed to Bryophyllum plants (genus Kalanchoe, Crassulaceae), but their production by these medicinal plants has not been characterized to date. In this work, a combinatorial approach including plant tissue culture, untargeted metabolomics, and machine learning is proposed to unravel the critical factors behind the biosynthesis of phenolic compounds in these species. The untargeted metabolomics revealed 485 annotated compounds that were produced by three Bryophyllum species cultured in vitro in a genotype and organ-dependent manner. Neurofuzzy logic (NFL) predictive models assessed the significant influence of genotypes and organs and identified

SUBMITTER: Garcia-Perez P 

PROVIDER: S-EPMC8620224 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature