Pieczonka Stefan A, Lucio Marianna, Rychlik Michael, Schmitt-Kopplin Philippe
Chair of Analytical Food Chemistry, Technical University of Munich, Freising, Germany.
Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg, Germany.
NPJ Sci Food. 2020 Aug 20;4:11. doi: 10.1038/s41538-020-00070-3. eCollection 2020.
The compositional space of a set of 120 diverse beer samples was profiled by rapid flow-injection analysis (FIA) Fourier transform ion cyclotron mass spectrometry (FTICR-MS). By the unrivaled mass resolution, it was possible to uncover and assign compositional information to thousands of yet unknown metabolites in the beer matrix. The application of several statistical models enabled the assignment of different molecular pattern to certain beer attributes such as the beer type, the way of adding hops and the grain used. The dedicated van Krevelen diagrams and mass difference networks displayed the structural connectivity of the annotated sum formulae. Thereby it was possible to provide a base of knowledge of the beer metabolome far above database-dependent annotations. Typical metabolic signatures for beer types, which reflect differences in ingredients and ways of brewing, could be extracted. Besides, the complexity of isomeric compounds, initially profiled as single mass values in fast FIA-FTICR-MS, was resolved by selective UHPLC-ToF-MS analysis. Thereby structural hypotheses based on FTICR's sum formulae could be confirmed. Benzoxazinoid hexosides deriving from the wheat's secondary metabolism were uncovered as suitable marker substances for the use of whole wheat grains, in contrast to merely wheat starch or barley. Furthermore, it was possible to describe Hydroxymethoxybenzoxazinone(HMBOA)-hexosesulfate as a hitherto unknown phytoanticipin derivative in wheat containing beers. These findings raise the potential of ultrahigh resolution mass spectrometry for rapid quality control and inspection purposes as well as deep metabolic profiling, profound search for distinct hidden metabolites and classification of archeological beer samples.
通过快速流动注射分析（FIA）傅里叶变换离子回旋共振质谱（FTICR-MS）对一组120种不同啤酒样品的成分空间进行了分析。凭借无与伦比的质量分辨率，能够揭示啤酒基质中数千种未知代谢物的成分信息并进行归属。应用多种统计模型能够将不同的分子模式与某些啤酒属性相关联，如啤酒类型、添加啤酒花的方式和使用的谷物。专用的范克雷维伦图和质量差异网络展示了注释分子式的结构连通性。从而有可能提供远超基于数据库注释的啤酒代谢组知识基础。可以提取反映成分和酿造方式差异的啤酒类型的典型代谢特征。此外，通过选择性超高效液相色谱-飞行时间质谱（UHPLC-ToF-MS）分析，解决了最初在快速FIA-FTICR-MS中作为单一质量值进行分析的同分异构体化合物的复杂性。由此基于FTICR分子式的结构假设得以证实。与仅使用小麦淀粉或大麦相比，从小麦次生代谢中衍生出的苯并恶嗪类己糖苷被发现是使用全麦谷物的合适标志物。此外，有可能将羟甲基苯并恶嗪酮（HMBOA）-己糖硫酸盐描述为含小麦啤酒中一种迄今未知的植物抗毒素衍生物。这些发现提高了超高分辨率质谱在快速质量控制和检测目的以及深度代谢谱分析、寻找独特隐藏代谢物和考古啤酒样品分类方面的潜力。
