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

Abstract

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.

A critical review on metabolomic analysis of milk and milk products

“…UPLC coupled with QTOF‐MS has been used to analyse the low concentration of metabolites present in milk (Zhang et al . 2018). UPLC‐QTOF‐MS integrated with data analysis has been used to determine the heating effect on milk (Zhang et al .…”

“…These biomarkers, especially oxylipids, effectively differentiate UHT milk from raw and pasteurised milk and exhibit significant differences in their presence in raw, pasteurised and UHT milk, identified by targeted UPLC‐MS/MS methods (Zhang et al . 2018).…”

“…Jang et al (2018) reported the use of chemical isotope labelling-based LC-MS metabolomic techniques to quantify a relatively large amount of metabolites. UPLC coupled with QTOF-MS has been used to analyse the low concentration of metabolites present in milk (Zhang et al 2018). UPLC-QTOF-MS integrated with data analysis has been used to determine the heating effect on milk (Zhang et al 2018).…”

“…UPLC coupled with QTOF-MS has been used to analyse the low concentration of metabolites present in milk (Zhang et al 2018). UPLC-QTOF-MS integrated with data analysis has been used to determine the heating effect on milk (Zhang et al 2018). The advantages of UPLC-QTOF-MS are high acquisition speed, high resolution for identification and confirmation of mass spectroscopic data, detectability of low-abundance species in complex samples and quantitative accuracy (Nassar et al 2017).…”

“…A wide range of metabolites including seven oxylipids and one phospholipid have been identified as biomarkers and determined in fresh, pasteurized and UHT milk by high-resolution mass spectrometry (HRMS) (Zhang et al 2018). These biomarkers, especially oxylipids, effectively differentiate UHT milk from raw and pasteurised milk and exhibit significant differences in their presence in raw, pasteurised and UHT milk, identified by targeted UPLC-MS/ MS methods (Zhang et al 2018).…”