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

文献类型： 外文期刊

第一作者： Zhang, Y. D.

作者： Zhang, Y. D.;Li, P.;Zheng, N.;Wen, F.;Li, S. L.;Zhao, S. G.;Wang, J. Q.;Zhang, Y. D.;Li, P.;Zheng, N.;Wen, F.;Li, S. L.;Zhao, S. G.;Wang, J. Q.;Jia, Z. W.;Meruva, N.;Ladak, A.;Cleland, G.

作者机构：

关键词： metabolomics; milk; pasteurized; ultra-high temperature; ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry

期刊名称：JOURNAL OF DAIRY SCIENCE （ 影响因子：4.034； 五年影响因子：4.354 ）

ISSN： 0022-0302

年卷期： 2018 年 101 卷 11 期

页码：

收录情况： SCI

摘要： 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 MSE 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.

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