Department of Chemistry, University of Alberta , Edmonton, Alberta T6G 2G2, Canada.
Anal Chem. 2017 Apr 18;89(8):4435-4443. doi: 10.1021/acs.analchem.6b03737. Epub 2017 Mar 28.
Milk is a complex sample containing a variety of proteins, lipids, and metabolites. Studying the milk metabolome represents an important application of metabolomics in the general area of nutritional research. However, comprehensive and quantitative analysis of milk metabolites is a challenging task due to the wide range of variations in chemical/physical properties and concentrations of these metabolites. We report an analytical workflow for in-depth profiling of the milk metabolome based on chemical isotope labeling (CIL) and liquid chromatography mass spectrometry (LC-MS) with a focus of using dansylation labeling to target the amine/phenol submetabolome. An optimal sample preparation method, including the use of methanol at a 3:1 ratio of solvent to milk for protein precipitation and dichloromethane for lipid removal, was developed to detect and quantify as many metabolites as possible. This workflow was found to be generally applicable to profile milk metabolomes of different species (cow, goat, and human) and types. Results from experimental replicate analysis (n = 5) of 1:1, 2:1, and 1:2 C-/C-labeled cow milk samples showed that 95.7%, 94.3%, and 93.2% of peak pairs, respectively, had ratio values within ±50% accuracy range and 90.7%, 92.6%, and 90.8% peak pairs had RSD values of less than 20%. In the metabolomic analysis of 36 samples from different categories of cow milk (brands, batches, and fat percentages) with experimental triplicates, a total of 7104 peak pairs or metabolites could be detected with an average of 4573 ± 505 (n = 108) pairs detected per LC-MS run. Among them, 3820 peak pairs were commonly detected in over 80% of the samples with 70 metabolites positively identified by mass and retention time matches to the dansyl standard library and 2988 pairs with their masses matched to the human metabolome libraries. This unprecedentedly high coverage of the amine/phenol submetabolome illustrates the complexity of the milk metabolome. Since milk and milk products are consumed in large quantities on a daily basis, the intake of these milk metabolites even at low concentrations can be cumulatively high. The high-coverage analysis of the milk metabolome using CIL LC-MS should be very useful in future research involving the study of the effects of these metabolites on human health. It should also be useful in the dairy industry in areas such as improving milk production, developing new processing technologies, developing improved nutritional products, quality control, and milk product authentication.
牛奶是一种复杂的样本,含有多种蛋白质、脂质和代谢物。研究牛奶代谢组学是代谢组学在营养研究领域的一个重要应用。然而,由于这些代谢物的化学/物理性质和浓度范围广泛,全面和定量地分析牛奶代谢物是一项具有挑战性的任务。我们报告了一种基于化学同位素标记(CIL)和液相色谱-质谱(LC-MS)的深入分析牛奶代谢组学的分析工作流程,重点是使用丹磺酰基标记来针对胺/酚亚代谢组。开发了一种最佳的样品制备方法,包括使用甲醇与牛奶的溶剂比为 3:1 进行蛋白质沉淀和使用二氯甲烷去除脂质,以尽可能多地检测和定量代谢物。该工作流程被发现通常适用于分析不同物种(奶牛、山羊和人类)和类型的牛奶代谢组。对 1:1、2:1 和 1:2 C-/C 标记的奶牛牛奶样品进行实验重复分析(n = 5)的结果表明,分别有 95.7%、94.3%和 93.2%的峰对的比值在±50%的准确度范围内,90.7%、92.6%和 90.8%的峰对的 RSD 值小于 20%。在对来自不同类别(品牌、批次和脂肪百分比)的 36 个奶牛牛奶样本的代谢组学分析中,每个 LC-MS 运行平均可检测到 4573±505(n = 108)对峰对或代谢物,共可检测到 7104 对峰对或代谢物。其中,3820 对峰对在超过 80%的样本中共同检测到,70 种代谢物通过与丹磺酰标准库的质量和保留时间匹配得到阳性鉴定,2988 对峰对的质量与人类代谢组库匹配。这种前所未有的对胺/酚亚代谢组的高覆盖率说明了牛奶代谢组的复杂性。由于牛奶及其制品每天都大量食用,即使在低浓度下摄入这些牛奶代谢物也可能会累积。使用 CIL LC-MS 对牛奶代谢组进行高覆盖率分析,对于未来研究这些代谢物对人类健康的影响应该非常有用。它还应该在乳品行业的各个领域有用,例如提高牛奶产量、开发新的加工技术、开发改进的营养产品、质量控制和牛奶产品认证。