On the Trail of the German Purity Law: Distinguishing the Metabolic Signatures of Wheat, Corn and Rice in Beer

Abstract

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 (MS2-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 MS2-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.

Archeochemistry reveals the first steps into modern industrial brewing

“…A total of 400 samples of commercially available beers from over 50 different countries were analyzed as a basis for statistical modeling. They are predominantly consistent with those chemically characterized in previous works 57 – 59 . The sample set represents a cross-section of all possible combinations of beer styles, fermentation types, raw materials, color impressions and alcohol contents available to exclude co-varying metadata.…”

“…These characteristics influence the metabolic signature of the respective way of brewing. As reported earlier 57 , 58 , wheat beers showed a network of compositions that can be traced back to secondary metabolites (phytoanticipines) of the wheat plant. The major difference between the molecular fingerprint of lager and craft beers is due to the different way of hopping.…”

“…More than 40 molecular formulae could be detected in one nominal mass with great matches between the historical and modern sample (Supplementary Figure S3 ). The molecular compositions were plotted in van Krevelen diagrams, which have proven to reveal compositional patterns within the metabolite profile of both wine 54 – 56 and beer samples 57 – 59 .…”

“…Yet, in addition to these products of primary metabolism, secondary metabolites that are extracted during the brewing process contribute to the molecular diversity of the final beverage. Utilizing the FTICR-MS analytical approach, the molecular profiles of barley, wheat, corn and rice could be characterized and potential marker substances identified using UPLC-ToF–MS 57 . We used these statistical models to examine the metabolic profile of the beers with regard to the use of the various starch sources that still are very common today.…”

Non-Targeted Metabolomic Analysis of the Kombucha Production Process

“…Indeed, the identity of food products is closely tied to their production process. In the context of fermented beverages, metabolomics was successfully applied to wine or beer, and allowed to determine the impacts of vintage and terroir on the composition of Burgundy red wines, or highlight the role of starch source on the metabolomes of German beers [3,4].…”