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Brassica microgreens shape gut microbiota and functional metabolite profiles in a species-related manner: A multi-omics approach following in vitro gastrointestinal digestion and large intestine fermentation

  • Istanbul Technical University

Research output: Contribution to journalArticle

Abstract

Brassicaceae microgreens constitute a novel and promising source of bioactive compounds, such as polyphenols and glucosinolates. In this work, an integrative computational approach was performed to decipher the interaction between bioaccessible microgreen metabolites and human gut bacteria. To this end, in vitro gastrointestinal digestion and large intestine fermentation were performed on eight different microgreens, which were further subjected to a dual high-throughput approach that combined fecal metagenomics and untargeted metabolomics. Data reveal a significant correlation between Parabacteroides merdae and two isothiocyanates in arugula fermentates, suggesting a high bioaccessibility of these bioactive compounds. Meanwhile, two species of Roseburia were correlated with pseudooxynicotine, an anti-inflammatory catabolite of nicotine in Brassica oleracea fermentates (such as broccoli, Brussels sprouts, and red cabbage), coupled with an increase in short-chain fatty acid production. These findings confer evidence on the nutritional impact of microgreens consumption, revealing the most bioaccessible metabolites with associated health-promoting properties together with their participation in the shaping of gut microbial populations, possibly leading to prebiotic effects.
Original languageEnglish
Pages (from-to)N/A-N/A
JournalMicrobiological Research
Volume298
Issue numberN/A
DOIs
Publication statusPublished - 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Microbiology

Keywords

  • Bioactive compounds
  • Cruciferous vegetables
  • Gut microbiota
  • Machine learning
  • Metabolomics
  • Metagenomics

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