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Decoding the metabolic interplay between indigenous Lactiplantibacillus and Arabica coffee (Coffea arabica L.): Species identification to synergistic metabolomic landscapes

  • Achmad Dinoto*
  • , Anisa Lutfia
  • , Yuliar
  • , Daris Syefilla Ramadhani
  • , Yoga Dwi Jatmiko
  • , Heddy Julistiono
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This study explored the modulation of the functional metabolome of Arabica coffee (Coffea arabica L.) using Lactiplantibacillus indigenous starters. Two bacterial strains, Lactiplantibacillus fabifermentans MMP2 of coffee fermentation liquid (mosto) origin and Lactiplantibacillus plantarum YSR3 of coffee cherry origin, were identified through 16S rRNA gene sequencing. LC-HRMS-based metabolomics revealed that the chemical landscape of green coffee beans is significantly influenced by the specific microbial species employed. Fermentation of coffee cherry with L. fabifermentans strain MMP2 yielded the highest metabolite complexity in green bean, uniquely characterized by steroid enrichment and acetylcholine synthesis—a potent neuroactive marker previously unreported for this species. Conversely, L. plantarum strain YSR3 favored purine-base accumulation. Coculture of L. fabifermentans strain MMP2 and L. plantarum strain YSR3 induces synergistic effects by accumulating phenolic esters and α,α-trehalose, an internationally recognized quality indicator. These findings underscore the pivotal role of species-specific selection in tailoring the chemical architecture and bioactive potential of coffee. Our results provide a strategic framework for developing premium functional beverages through precision fermentation using local microbial resources.

Original languageEnglish
Pages (from-to)868-879
Number of pages12
JournalSouth African Journal of Botany
Volume196
DOIs
Publication statusPublished - Sept 2026

Keywords

  • 16S rRNA
  • Arabica coffee
  • Lactiplantibacillus fabifermentans
  • Lactiplantibacillus plantarum
  • LC-HRMS
  • Metabolomics

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