Pieczonka Stefan A, Paravicini Sophia, 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.
Front Chem. 2021 Jul 20;9:715372. doi: 10.3389/fchem.2021.715372. eCollection 2021.
Here, we report a non-targeted analytical approach to investigate the influence of different starch sources on the metabolic signature in the final beer product. An extensive sample set of commercial beers brewed with barley, wheat, corn and/or rice were analyzed by both direct infusion Fourier transform ion cyclotron mass spectrometry (DI-FTICR MS, 400 samples) and UPLC-ToF-MS (100 samples). By its unrivaled mass resolution and accuracy, DI-FTICR-MS was able to uncover the compositional space of both polar and non-polar metabolites that can be traced back to the use of different starch sources. Reversed phase UPLC-ToF-MS was used to access information about molecular structures (MS-fragmentation spectra) and isomeric separation, with a focus on less polar compounds. Both analytical approaches were able to achieve a clear statistical differentiation (OPLS-DA) of beer samples and reveal metabolic profiles according to the starch source. A mass difference network analysis, applied to the exact marker masses resolved by FTICR, showed a network of potential secondary metabolites specific to wheat, corn and rice. By MS-similarity networks, database and literature search, we were able to identify metabolites and compound classes significant for the use of the different starch sources. Those were also found in the corresponding brewing raw materials, confirming the potential of our approach for quality control and monitoring. Our results also include the identification of the aspartic acid-conjugate of N-β-D-glucopyranosyl-indole-3-acetic acid as a potential marker for the use of rice in the brewing industry regarding quality control and food inspection purposes.
在此，我们报告一种非靶向分析方法，用于研究不同淀粉来源对最终啤酒产品代谢特征的影响。通过直接进样傅里叶变换离子回旋共振质谱（DI-FTICR MS，400个样品）和超高效液相色谱-飞行时间质谱（UPLC-ToF-MS，100个样品）对一组用大麦、小麦、玉米和/或大米酿造的商业啤酒进行了广泛分析。凭借其无与伦比的质量分辨率和准确性，DI-FTICR-MS能够揭示可追溯到不同淀粉来源使用情况的极性和非极性代谢物的组成空间。反相UPLC-ToF-MS用于获取有关分子结构（MS裂解谱）和异构体分离的信息，重点关注极性较小的化合物。两种分析方法都能够实现啤酒样品的清晰统计区分（OPLS-DA），并根据淀粉来源揭示代谢谱。对FTICR解析的精确标记质量应用质量差异网络分析，显示了一个特定于小麦、玉米和大米的潜在次生代谢物网络。通过MS相似性网络、数据库和文献搜索，我们能够鉴定出对不同淀粉来源的使用具有重要意义的代谢物和化合物类别。这些也在相应的酿造原料中被发现，证实了我们的方法在质量控制和监测方面的潜力。我们的结果还包括鉴定N-β-D-吡喃葡萄糖基-吲哚-3-乙酸的天冬氨酸共轭物，作为酿造工业中大米使用的潜在标记物，用于质量控制和食品检验目的。
