Profiling Metabolites in the Beer Matrix

The ancient craft of brewing beer is more than 5000 years old. As it has evolved, so have the methods of analysis employed to perfect the qualities of the brew. New research that allows for analysis and profiling of metabolites in the beer matrix is providing solutions for perfecting and maintaining beer quality. Stefan A. Pieconzonka and Philippe Schmitt-Kopplin have profiled diverse beer samples by rapid flow-injection analysis (FIA) Fourier transform ion cyclotron mass spectrometry (FTICR–MS). Here, they discuss their approach to this analysis, along with the significance of the Maillard Reaction (MR) in beer quality and analysis.

In a recent paper, you and your team profiled a set of 120 diverse beer samples by rapid flow-injection analysis Fourier transform ion cyclotron mass spectrometry (1). Why is it important to uncover and assign compositional information to what your paper describes as “thousands of yet-unknown metabolites in the beer matrix?”

Our analytical approach in this paper resolves the molecular composition and complexity of the samples in a holistic way. It gathers information of precise mass and thus sum formula that can be used to describe the intrinsic chemical compositional nature of the samples. Recognizing that 70–85% of the resolved mass signals do not have a database entry, it becomes clear that the majority of information about foods and beverages is complex and not yet unraveled. Our paper show this in a holistic analytical approach while visualizing, as well, this “dark metabolome” of unknowns.

On the other hand, the compositional information can be utilized to detect molecular patterns of interest and go deeper in structural analysis and data mining. That might be food authenticity, correlating patterns with flavor and aroma, food quality, or the description and guidance of processes. In times where “big data” frequently finds its way into everyday lives, big analytical datasets that hide deep information mirror this development.

What challenges did you encounter while profiling the compositional space of these diverse beer samples?

First, we were surprised how complex the beer matrix is. The huge molecular diversity of beer is based on various compositional factors such as the (oligo) saccharide composition, fermentation signature, Maillard reaction products, several plant-derived secondary metabolites (hops, barley, wheat, and so on). It creates an analytical spectrum of high complexity and molecular composition.

What role do small molecules (<1000 Da) for the beer metabolome play in raw material and final beer quality attributes, such as taste, aroma, yeast fermentation, foam stability, and beer aging?

Small molecules highly influence all of these aspects and are (besides proteins) major driving force of beer quality. Traditional analytical food chemistry approaches focus on what is directly linked to such quality parameters: The search for and analysis of targeted aroma compounds, taste compounds, and so on. In many cases, processes that lead to these final products or alter quality are very complex when seeing the beer as a complex mixture of (tens of) thousands of organics in an aqueous solution.

Following the big questions related to beer aging, beer stability, and flavor development, it may be advisable to have a systems approach and to consider the beer system in its whole chemistry rather than to quantify only few known targets. Underlying principles of synergistic effects, precursors, and complex reactomes can be unraveled. Whole processes can be described and guided eventually.

In another recent paper, the Maillard reaction (MR) in beer was explored using Fourier-transform ion cyclotron mass spectrometry (FTICR-MS (2). Can you describe the MR and explain its significance in beer quality and analysis?

The Maillard reaction (MR, named after Louis Maillard, who worked on thermoprocesses in the early 19th century) is commonly known as the reaction of reducible sugars with amino acids or amines or as non-enzymatic browning. It is not a single reaction as other “name-reactions,” but the term unites a whole complex reaction network with several steps and repetitive intrinsic patterns. It happens mainly at higher temperatures, meaning during malting and the brewing or boiling process. But the MR also changes the composition of the beer during storage (longer reaction times at lower temperatures), leading to unwanted off-flavors or lesser beer stability.

The Maillard reaction is also the main origin for roasty, malty, caramel, or chocolate flavors of darker beers and significantly contributes to the overall impression of the beer flavor and organoleptic.

The classical way to target the MR is to target known “marker” products. Our approach is first to describe the whole reaction network to identify novel targets and processes to be followed involving all compositions and reactions that might relate them.

How can FT-ICR-MS benefit non-targeted metabolic profiling in beer analysis?

With regard to the MR, it is clearly the holistic metabolite profiling that brings the benefits because it is not possible to describe such a complex and diverse reaction sequence by just looking at a few already-described molecular parameters. A different way to target the MR is to describe it as a molecular social network with over 2,800 different compositional individuals (which will translate to an even wider range of isomers) to find molecular interactions that are characteristic for the whole system. This enables to get insights in the compositional changes as part of the brewing process coming with it and thus to have insights into molecular fingerprints that lead to the better beer quality (shelf-life, taste, aroma). Because more than 40% of all resolved signals in beer derive from the MR, it highlights its importance in beer composition.

One of your most recent papers references the German Beer Purity Law and describes how you and your team were able to distinguish the metabolic signatures of different starch sources, such as wheat, corn, and rice in beer using two different complementary mass spectrometric methods: direct infusion Fourier transform ion cyclotron mass spectrometry (DI-FTICR-MS) for 400 samples; and ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC–ToF-MS) for 100 samples (3). What were the advantages of using these two different MS techniques?

This project, besides other aspects, shows opportunities for food authenticity control. Such metabolomic approaches contributes to food quality (safety, utility, nutritional, sensory, and ecological quality) and authenticity. The demand for advanced analytical techniques in the field of food analysis has grown in parallel to highly industrialized food production and consumers’ concerns about food safety and authenticity. The trend towards non-targeted analytical approaches already is visible. An integrated system of non-targeted and high-resolving analytics is far more difficult to avoid, even when sophisticated fraud attempts aim to avoid detection with knowledge of testing programs. This is what we could provide by the FTICR-MS approach, giving a whole metabolite pattern that indicate samples’ attributes (for example corn and rice adjuncts).

On the other hand, such a sophisticated analytical approach is not yet available to food authorities (and still will not be in 10–15 years). Thus, besides showing its potential, it is important to translate the non-targeted approaches into classical marker substances that are reachable for every analytical laboratory. Knowing molecular networks from the FTICR-MS approach and adding UPLC-ToF-MS information we can specifically target the combination of molecules that – out of the holistic entity – are marker molecules for the grains, and so forth, by chemometric approaches. Ultra performance liquid chromatography-time-of-flight mass spectrometry also allows access to deeper information about the molecule’s structure (fragmentation patterns) and identification of the molecule that can then be used in other laboratories as well.

Are there other applications where employing DI-FTICR-MS with UPLC–ToF-MS would be appropriate and reveal new information? Where would you like to see these two methods further applied?

Without revealing our future projects too much, our focus will be on the role of molecular complexity and diversity during the brewing process. Beer-aging mechanisms are of interest because they enable us to have a base of knowledge that we use in archeochemical analysis of residues and historical brews.

We are also interested in a more detailed description of raw materials and their processing.

Essentially, the MR is our focus precisely because of its many bioactive compounds with their impact on human health.

What future projects lie ahead for you and your team in the exploration of chemical complexity in different foods and beverages?

We have several years of comprehensive analytical experience with various beverages and distillates. But our current milestones involve this technological know-how more towards the general fermented and thermally processed food metabolome and its impact on the gut microbiome as related to human and animal health. Our interest is the molecular coverage of the “food/gut microbiome/health continuum,” and within these aspects, functional metabolomics and bioactivity profiles are of the highest importance in terms of microbial modulators or prebiotics.


  1. S.A. Pieczonka, M. Lucio, M. Rychlik, and P.S. Schmitt-Kopplin, njp Science of Food 4(11) (2020).
  2. S.A. Pieczonka, D. Hemmler, F. Moritz, M. Lucio, M. Zarnkow, F. Jacob, M. Ryclik, P. Schmitt-Kopplin, Food Chem 361 130112(2010).
  3. S.A. Pieczonka, S. Paravicini, M. Rychlik, and P. Schmitt-Kopplin, Front Chem 9 (2021).

Philippe Schmitt-Kopplin is a Professor at the Technical University of Munich (TUM) in Freising/Weihenstephan, as head of the Comprehensive Foodomics Platform at the Chair of Analytical Food Chemistry and is director of the research unit Analytical Biogeochemistry (BGC) at the Helmholtz Zentrum München (HMGU), Germany. His research focus is on the Food/Microbiome/Health continuum using the chemical diversity analysis to study generic biotic and abiotic processes in biology and in health. His tools are a combination of (ultra)high resolution (µ)separation sciences, spectroscopy, and spectrometry for targeted and non-targeted chemical analysis.

Stefan A. Pieczonka is a Food Chemist and doctorate student and research associate at the Technical University of Munich (TUM) in Freising/Weihenstephan, Germany. He works on the comprehensive analysis of the metabolome of beer. His expertise includes the holistic analytical description of foods/beverages, of the chemical changes during its processing, search for characteristic molecular patterns or biomarkers, and the chemometric integration of (complementary) analytical data.