Analytical opportunities and challenges for data handling with chemometrics strategies from LC-MS based food metabolomics

Abstract

BackgroundLiquid chromatography-mass spectrometry-based metabolomics allows us to measure thousands of small metabolites from food matrixes, focused on understanding in depth food science including food authenticity, safety and nutrition. However, metabolomics research generates exceptionality complex datasets and the processing and interpretation of these datasets has been a key challenge. Recently, chemometrics approaches have shown potential in data analysis within food metabolomics and has demonstrated its extensive ability to overcome the complex challenges. Scope and approachThis review presents a typical workflow of LC-MS based foodomics, from sample preparation to biological interpretation of data processing outcomes, especially focusing on data handing strategies in LC-MS based foodomics and typical bioinformatics tools. The applicability of chemometrics with LC-MS based metabolomics approaches in the food domain has been demonstrated with recent applications in food authenticity, safety and nutrition as well as revealing the superiority of different chemometric methods. Key findings and conclusionsChemometrics, having the analytical power from statistical and computer science, have been powerful tools not only for efficient processing of complex data, but also for acquiring high quality data and comprehensive information. Combined with LC-MS based metabolomics, this formidable platform enables comprehensive characterization of food metabolites fingerprinting in food authenticity, highly sensitive and accurate measurement of contaminants or drug residues in food safety as well as the in-depth investigation of the functionality of remarkable metabolites after dietary intervention in food nutrition. As chemometrics develops in leaps and bounds, the applications of food metabolomics will be further broadened in foodomics research.