A UHPLC-HRMS based metabolomics and chemoinformatics approach to chemically distinguish 'super foods' from a variety of plant-based foods

Food Chem. 2020 May 30:313:126071. doi: 10.1016/j.foodchem.2019.126071. Epub 2019 Dec 24.

Abstract

The aim of this study was to investigate if the declared benefits associated with superfoods are related to a specific molecular composition. For this purpose, untargeted metabolomics and molecular networking were used to obtain an overview of all features, focusing on compounds with anti-inflammatory, antioxidant or antimicrobial properties. 565 plant-based food samples were analyzed using UHPLC-HRMS and advanced data analysis tools. The molecular networking of the whole dataset allowed identification of a greater diversity of molecules, in particular, prenol lipids, isoflavonoids and isoquinolines in superfoods, when compared with non-superfood species belonging to the same botanical family. Furthermore, in silico tools were used to expand our chemical knowledge of compounds observed in superfood samples.

Keywords: Food; LC–MS/MS; Metabolomics; Superfood; Untargeted MS.

MeSH terms

  • Anti-Infective Agents / chemistry
  • Anti-Inflammatory Agents / chemistry
  • Antioxidants / chemistry
  • Chromatography, High Pressure Liquid
  • Food Analysis*
  • Mass Spectrometry
  • Metabolomics / methods*
  • Plants / chemistry*
  • Plants / metabolism
  • Principal Component Analysis

Substances

  • Anti-Infective Agents
  • Anti-Inflammatory Agents
  • Antioxidants