Neurofuzzy logic predicts a fine-tuning metabolic reprogramming on elicited Bryophyllum PCSCs guided by salicylic acid

Pascual García-Pérez, Eva Lozano-Milo, Leilei Zhang, Maria Begona Miras Moreno, Mariana Landin, Luigi Lucini, Pedro P. Gallego

Risultato della ricerca: Contributo in rivistaArticolo in rivista

Abstract

Novel approaches to the characterization of medicinal plants as biofactories have lately increased in the field of biotechnology. In this work, a multifaceted approach based on plant tissue culture, metabolomics, and machine learning was applied to decipher and further characterize the biosynthesis of phenolic compounds by eliciting cell suspension cultures from medicinal plants belonging to the Bryophyllum subgenus. The application of untargeted metabolomics provided a total of 460 phenolic compounds. The biosynthesis of 164 of them was significantly modulated by elicitation. The application of neurofuzzy logic as a machine learning tool allowed for deciphering the critical factors involved in the response to elicitation, predicting their influence and interactions on plant cell growth and the biosynthesis of several polyphenols subfamilies. The results indicate that salicylic acid plays a definitive genotype-dependent role in the elicitation of Bryophyllum cell cultures, while methyl jasmonate was revealed as a secondary factor. The knowledge provided by this approach opens a wide perspective on the research of medicinal plants and facilitates their biotechnological exploitation as biofactories in the food, cosmetic and pharmaceutical fields.
Lingua originaleEnglish
pagine (da-a)N/A-N/A
RivistaFrontiers in Plant Science
Volume13
DOI
Stato di pubblicazionePubblicato - 2022

Keywords

  • Kalanchoe
  • Untargeted metabolic profiling
  • medicinal plants
  • metabolic fingerprint
  • plant biotechnology
  • polyphenols

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