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Identification of beer spoilage microorganisms using the MALDI Biotyper platform

  • Genomics, transcriptomics, proteomics
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Abstract

Beer spoilage microorganisms present a major risk for the brewing industry and can lead to cost-intensive recall of contaminated products and damage to brand reputation. The applicability of molecular profiling using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) in combination with Biotyper software was investigated for the identification of beer spoilage microorganisms from routine brewery quality control samples. Reference mass spectrum profiles for three of the most common bacterial beer spoilage microorganisms (Lactobacillus lindneri, Lactobacillus brevis and Pediococcus damnosus), four commercially available brewing yeast strains (top- and bottom-fermenting) and Dekkera/Brettanomyces bruxellensis wild yeast were established, incorporated into the Biotyper reference library and validated by successful identification after inoculation into beer. Each bacterial species could be accurately identified and distinguished from one another and from over 5600 other microorganisms present in the Biotyper database. In addition, wild yeast contaminations were rapidly detected and distinguished from top- and bottom-fermenting brewing strains. The applicability and integration of mass spectrometry profiling using the Biotyper platform into existing brewery quality assurance practices within industry were assessed by analysing routine microbiology control samples from a local brewery, where contaminating microorganisms could be reliably identified. Brewery-isolated microorganisms not present in the Biotyper database were further analysed for identification using LC-MS/MS methods. This renders the Biotyper platform a promising candidate for biological quality control testing within the brewing industry as a more rapid, high-throughput and cost-effective technology that can be tailored for the detection of brewery-specific spoilage organisms from the local environment.

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Acknowledgments

The authors would further like to thank David Jones, Janie Zimmermann, Leon Dimitriou, Gurpreet Brar and the biological quality control team of Coopers Brewery Ltd. for their kind preparation and provision of samples from brewery production processes. This work was funded by the Photonics Catalyst Programme, PCP project code 014.

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Authors and Affiliations

  1. Adelaide Proteomics Centre, The University of Adelaide, Adelaide, Australia

    Michelle Elizabeth Turvey, Florian Weiland & Peter Hoffmann

  2. Institute for Photonics and Advanced Sensing, The University of Adelaide, Adelaide, Australia

    Michelle Elizabeth Turvey, Florian Weiland & Peter Hoffmann

  3. Coopers Brewery Ltd, Adelaide, Australia

    Jon Meneses & Nick Sterenberg

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  1. Michelle Elizabeth Turvey
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  2. Florian Weiland
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  3. Jon Meneses
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  5. Peter Hoffmann
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Correspondence to Peter Hoffmann.

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Michelle Elizabeth Turvey and Florian Weiland contributed equally to this work.

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Turvey, M.E., Weiland, F., Meneses, J. et al. Identification of beer spoilage microorganisms using the MALDI Biotyper platform. Appl Microbiol Biotechnol 100, 2761–2773 (2016). https://doi.org/10.1007/s00253-016-7344-8

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