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探索人乳动态变化:乳蛋白质组、肽组和代谢组的个体间差异。

Exploring Human Milk Dynamics: Interindividual Variation in Milk Proteome, Peptidome, and Metabolome.

机构信息

Food Quality and Design Group, Wageningen University & Research, Bornse Weilanden 9, 6708 WG Wageningen, The Netherlands.

Laboratory of Biochemistry, Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands.

出版信息

J Proteome Res. 2022 Apr 1;21(4):1002-1016. doi: 10.1021/acs.jproteome.1c00879. Epub 2022 Feb 1.

Abstract

Human milk is a dynamic biofluid, and its detailed composition receives increasing attention. While most studies focus on changes over time or differences between maternal characteristics, interindividual variation receives little attention. Nevertheless, a comprehensive insight into this can help interpret human milk studies and help human milk banks provide targeted milk for recipients. This study aimed to map interindividual variation in the human milk proteome, peptidome, and metabolome and to investigate possible explanations for this variation. A set of 286 milk samples was collected from 29 mothers in the third month postpartum. Samples were pooled per mother, and proteins, peptides, and metabolites were analyzed. A substantial coefficient of variation (>100%) was observed for 4.6% and 36.2% of the proteins and peptides, respectively. In addition, using weighted correlation network analysis (WGCNA), 5 protein and 11 peptide clusters were obtained, showing distinct characteristics. With this, several associations were found between the different data sets and with specific sample characteristics. This study provides insight into the dynamics of human milk protein, peptide, and metabolite composition. In addition, it will support future studies that evaluate the effect size of a parameter of interest by enabling a comparison with natural variability.

摘要

人乳是一种动态的生物流体,其详细组成越来越受到关注。虽然大多数研究都集中在随时间的变化或母体特征之间的差异上,但个体间的差异却很少受到关注。然而,全面了解这一点有助于解释人乳研究,并帮助人乳库为接受者提供有针对性的乳汁。本研究旨在绘制人乳蛋白质组、肽组和代谢组的个体间变异图谱,并探讨这种变异的可能解释。从 29 位产后第三个月的母亲中收集了 286 份牛奶样本。按母亲对样本进行了混合,分析了蛋白质、肽和代谢物。分别有 4.6%和 36.2%的蛋白质和肽的变异系数(>100%)较大。此外,使用加权相关网络分析(WGCNA),得到了 5 个蛋白质和 11 个肽簇,显示出不同的特征。通过这种方法,发现了不同数据集之间以及与特定样本特征之间的一些关联。本研究深入了解了人乳蛋白质、肽和代谢物组成的动态变化。此外,它将通过允许与自然变异进行比较,支持评估感兴趣参数的效应大小的未来研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1fc8/8981310/ce9298c5092e/pr1c00879_0001.jpg

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