Untargeted Metabolomics Reveals Raw Material Geographic Origin as a Key Factor Shaping the Quality of Ginger-Derived Exosome-like Nanovesicles

TL;DR

This study shows that the geographic origin of ginger affects the quality of ginger-derived nanovesicles, using metabolomics and machine learning to identify key quality markers.

Contribution

The study introduces a quality control framework for food-derived nanomaterials by linking geographic origin to chemical and functional properties.

Findings

Significant variations in GELN properties and bioactivities were observed based on geographic origin.

190 differential compounds and 6 potential quality markers were identified using metabolomics and machine learning.

Key metabolic pathways like microbial metabolism and galactose metabolism were linked to GELN quality.

Abstract

A major challenge for food-derived bio-nanomaterials is achieving consistent and predictable functional properties to ensure their quality. Ginger-derived exosome-like nanovesicles (GELNs) serve as an ideal model for this challenge, yet the impact of ginger geographical origin on GELNs remains unknown. This study aims to establish a quality control framework for food-derived bio-nanomaterials. GELNs were comprehensively analyzed. Untargeted metabolomics identified differential metabolites, which were then screened for correlation with antioxidant capacity. Machine learning was employed to pinpoint potential quality markers, and Kyoto Encyclopedia of Genes and Genomes enrichment analysis highlighted key metabolic pathways. Significant variations in physicochemical properties and bioactivities were observed. We identified 190 differential compounds and established a panel of 6 potential quality markers. Enrichment analysis revealed eight key pathways, with “microbial metabolism in diverse environments” and “galactose metabolism” being most prominent. The quality marker mollicellin I (derived from Chaetomium brasiliense) provided empirical support linking GELNs quality to geography-specific microbiota. Our findings provide evidence that the geographic origin of raw materials is a primary determinant of GELNs quality, based on a systematic analysis of their chemical and functional properties. We develop a transferable quality control framework, laying the groundwork for producing superior natural food-derived nanomaterials.

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