A Standardized Nontargeted Metabolomics Analytical Method for Qualitatively Comparing Apples to Apples

Food composition has been traditionally defined by 35-160 chemical components with established nutritional significance for human health. Modern omics technologies have revealed that the chemical complexity of food is far greater, offering the potential to deepen our understanding of food composition to more precisely inform data-driven solutions across food systems. However, challenges in generating comparable omics data have limited the utility of omics technologies at the scale required to expand food composition databases. Herein, we present a standardized nontargeted LC-MS metabolomics method, supported by a novel internal retention time standard (IRTS) mixture of compounds non-endogenous to food that enables robust chromatographic alignment of data across laboratories. Our results demonstrate qualitative consensus of features across laboratories and/or instrumentation. This approach establishes the foundation for comparable, nontargeted omics analysis to support the next generation of food composition data.