A metabolomics approach to characterize raw, pasteurized, and ultra-high temperature milk using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry and multivariate data analysis.

We developed a metabolomics workflow using ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry to determine the effect of thermal treatment on milk composition and metabolites based on multivariate data analysis. We analyzed raw, pasteurized, and UHT milk samples. The samples were first centrifuged to remove the fat layer and mixed with methanol to precipitate proteins. Subsequently, the supernatant was analyzed by ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry in electrospray negative mode. Mass spectral data were acquired in MS mode, a technique whereby both precursor and fragment mass spectral are simultaneously acquired by alternating between low and high collision energy (CE) during a single analytical run, to enable metabolite identification. Based on multivariate data analysis, these markers were significantly affected by thermal treatment. Among the 8 potential markers, we identified 7 oxylipids (9-hydroxydecanoic acid, 12-hydroxydodecanoic acid, 2-hydroxymyristic acid, 3-hydroxytetradecanoic acid, 5-hydroxyeicosatetraenoic acid, 3-hydroxyhexadecanoic acid, and 10-hydroxyoctadecanoic acid) and 1 phospholipid (LysoPE, hexadecanoyl-lysophosphatidylethanolamine). The oxylipids seemed to be adequate for distinguishing UHT milk from raw and pasteurized milk. The structures of the 8 potential markers were identified and characterized using informatics software. Our metabolomics workflow provides a fast approach for the identification of various types of milk.