TY - JOUR
T1 - Exploring the bioaccessibility of polyphenols and glucosinolates from Brassicaceae microgreens by combining metabolomics profiling and computational chemometrics
AU - García-Pérez, Pascual
AU - Tomas, Merve
AU - Rivera-Pérez, Araceli
AU - Patrone, Vania
AU - Giuberti, Gianluca
AU - Capanoglu, Esra
AU - Lucini, Luigi
PY - 2024
Y1 - 2024
N2 - Microgreens constitute natural -based foods with health -promoting properties mediated by the accumulation of glucosinolates (GLs) and phenolic compounds (PCs), although their bioaccessibility may limit their nutritional potential. This work subjected eight Brassicaceae microgreens to in vitro gastrointestinal digestion and large intestine fermentation before the metabolomics profiling of PCs and GLs. The application of multivariate statistics effectively discriminated among species and their interaction with in vitro digestion phases. The flavonoids associated with arugula and the aliphatic GLs related to red cabbage and cauliflower were identified as discriminant markers among microgreen species. The multi-omics integration along in vitro digestion and fermentation predicted bioaccessible markers, featuring potential candidates that may eventually be responsible for these functional foods' nutritional properties. This combined analytical and computational framework provided a promising platform to predict the nutritional metabolome-wide outcome of functional food consumption, as in the case of microgreens.
AB - Microgreens constitute natural -based foods with health -promoting properties mediated by the accumulation of glucosinolates (GLs) and phenolic compounds (PCs), although their bioaccessibility may limit their nutritional potential. This work subjected eight Brassicaceae microgreens to in vitro gastrointestinal digestion and large intestine fermentation before the metabolomics profiling of PCs and GLs. The application of multivariate statistics effectively discriminated among species and their interaction with in vitro digestion phases. The flavonoids associated with arugula and the aliphatic GLs related to red cabbage and cauliflower were identified as discriminant markers among microgreen species. The multi-omics integration along in vitro digestion and fermentation predicted bioaccessible markers, featuring potential candidates that may eventually be responsible for these functional foods' nutritional properties. This combined analytical and computational framework provided a promising platform to predict the nutritional metabolome-wide outcome of functional food consumption, as in the case of microgreens.
KW - Bioactive compounds
KW - Cruciferous vegetables
KW - Machine learning
KW - Multivariate statistics
KW - Nutraceuticals
KW - Bioactive compounds
KW - Cruciferous vegetables
KW - Machine learning
KW - Multivariate statistics
KW - Nutraceuticals
UR - https://publicatt.unicatt.it/handle/10807/297424
UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85192951032&origin=inward
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85192951032&origin=inward
U2 - 10.1016/j.foodchem.2024.139565
DO - 10.1016/j.foodchem.2024.139565
M3 - Article
SN - 0308-8146
VL - 452
SP - N/A-N/A
JO - Food Chemistry
JF - Food Chemistry
IS - N/A
ER -