Decoding brewing yeast signatures: a MALDI-TOF MS approach to strain identification and beer style correlation

Abstract

Aims: Brewing yeast strain selection and management are critical in beer production, influencing flavor profiles and overall quality. This study investigates the potential of MALDI-TOF MS (Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry) for characterizing and differentiating brewing yeast strains associated with various beer styles. Methods and results: We analyzed 77 commercial yeast strains used to produce ale, lager, cider, mead, and low-alcohol beer, using MALDI-TOF MS in both high (m/z 2000–20 000) and low (m/z 500–4000) mass ranges. Spectra were analyzed using informatics-assisted hierarchical cluster analysis, multidimensional scaling (MDS), and linear discriminant analysis (LDA) to evaluate strain relationships and beer style associations. Results demonstrated that high mass range data formed an excellent basis for species-level identification, while low mass range data was more diverse and represented information that was more strain-specific. Conclusions: Both MDS and hierarchical clustering of combined low- and high-range MALDI-TOF spectra identified relationships between certain strains that correlated with their brewing recommendations. However, the use of LDA presented the clearest correlation of strain relationships with beer styles recommended by the commercial yeast producer.