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隐藏在颜色背后的奥秘:啤酒美拉德反应网络的分子水平分析。

Hidden in its color: A molecular-level analysis of the beer's Maillard reaction network.

机构信息

Chair of Analytical Food Chemistry, Technical University of Munich, Maximus-von-Imhof Forum 2, 85354 Freising, Germany; Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany.

Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstaedter Landstraße 1, 85764 Neuherberg, Germany.

出版信息

Food Chem. 2021 Nov 1;361:130112. doi: 10.1016/j.foodchem.2021.130112. Epub 2021 May 15.

Abstract

We here report a comprehensive non-targeted analytical approach to describe the Maillard reaction in beer. By Fourier-transform ion cyclotron mass spectrometry (FT-ICR-MS), we were able to assign thousands of unambiguous molecular formulae to the mass signals and thus directly proceed to the compositional space of 250 analyzed beer samples. Statistical data analyses of the annotated compositions showed that the Maillard reaction is one of the driving forces of beer's molecular diversity leading to key compositional changes in the beer metabolome. Different visualization methods allowed us to map the systematic nature of Maillard reaction derived compounds. The typical molecular pattern, validated by an experimental Maillard reaction model system, pervades over 2,800 (40%) of the resolved small molecules. The major compositional changes were investigated by mass difference network analysis. We were able to reveal general reaction sequences that could be assigned to successive Maillard intermediate phase reactions by shortest path analysis.

摘要

我们在这里报告了一种全面的非靶向分析方法来描述啤酒中的美拉德反应。通过傅里叶变换离子回旋共振质谱(FT-ICR-MS),我们能够将成千上万的明确分子公式分配给质量信号,从而直接进入 250 个分析啤酒样品的组成空间。对注释成分的统计数据分析表明,美拉德反应是啤酒分子多样性的驱动力之一,导致啤酒代谢组中的关键组成变化。不同的可视化方法允许我们绘制美拉德反应衍生化合物的系统性质。通过实验美拉德反应模型系统验证的典型分子模式,遍及 2800 多个(40%)已解析小分子。通过质量差异网络分析研究了主要的组成变化。我们能够通过最短路径分析揭示可归因于连续美拉德中间相反应的一般反应序列。

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