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Applying quantitative metabolomics based on chemical isotope labeling LC-MS for detecting potential milk adulterant in human milk
Analytica Chimica Acta ( IF 6.2 ) Pub Date : 2018-02-01 , DOI: 10.1016/j.aca.2017.11.019
Dorothea Mung , Liang Li

There is an increasing demand for donor human milk to feed infants for various reasons including that a mother may be unable to provide sufficient amounts of milk for their child or the milk is considered unsafe for the baby. Selling and buying human milk via the Internet has gained popularity. However, there is a risk of human milk sold containing other adulterants such as animal or plant milk. Analytical tools for rapid detection of adulterants in human milk are needed. We report a quantitative metabolomics method for detecting potential milk adulterants (soy, almond, cow, goat and infant formula milk) in human milk. It is based on the use of a high-performance chemical isotope labeling (CIL) LC-MS platform to profile the metabolome of an unknown milk sample, followed by multivariate or univariate comparison of the resultant metabolomic profile with that of human milk to determine the differences. Using dansylation LC-MS to profile the amine/phenol submetabolome, we could detect an average of 4129 ± 297 (n = 9) soy metabolites, 3080 ± 470 (n = 9) almond metabolites, 4256 ± 136 (n = 18) cow metabolites, 4318 ± 198 (n = 9) goat metabolites, 4444 ± 563 (n = 9) infant formula metabolites, and 4020 ± 375 (n = 30) human metabolites. This high level of coverage allowed us to readily differentiate the six different types of samples. From the analysis of binary mixtures of human milk containing 5, 10, 25, 50 and 75% other type of milk, we demonstrated that this method could be used to detect the presence of as low as 5% adulterant in human milk. We envisage that this method could be applied to detect contaminant or adulterant in other types of food or drinks.

中文翻译:

应用基于化学同位素标记 LC-MS 的定量代谢组学检测人乳中的潜在牛奶掺假

由于各种原因,包括母亲可能无法为孩子提供足够数量的母乳或母乳被认为对婴儿不安全,对供体母乳喂养婴儿的需求不断增加。通过互联网销售和购买母乳已经很流行。但是,出售的母乳中含有其他掺杂物,例如动物或植物奶,存在风险。需要用于快速检测人乳中掺假物的分析工具。我们报告了一种用于检测人乳中潜在牛奶掺假物(大豆、杏仁、牛、山羊和婴儿配方奶)的定量代谢组学方法。它基于使用高性能化学同位素标记 (CIL) LC-MS 平台来分析未知牛奶样品的代谢组,然后将所得的代谢组学特征与人乳的代谢组学特征进行多变量或单变量比较,以确定差异。使用丹磺酰化 LC-MS 分析胺/苯酚亚代谢组,我们可以检测到平均 4129 ± 297 (n = 9) 种大豆代谢物、3080 ± 470 (n = 9) 种杏仁代谢物、4256 ± 136 (n = 18) 种牛代谢物、4318 ± 198 (n = 9) 山羊代谢物、4444 ± 563 (n = 9) 婴儿配方奶粉代谢物和 4020 ± 375 (n = 30) 人代谢物。这种高覆盖率使我们能够轻松区分六种不同类型的样品。通过对含有 5%、10%、25%、50% 和 75% 其他类型牛奶的人乳二元混合物的分析,我们证明该方法可用于检测人乳中低至 5% 的掺假物。
更新日期:2018-02-01
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