Anneleen Wieme, University College Ghent, Faculty Applied Bioscience Engineering, Laboratory of Brewing and Biochemistry, Ghent, Belgium
Co-author(s): Anita Van Landschoot, University College Ghent, Faculty of Applied Bioscience Engineering, Laboratory of Brewing and Biochemistry, Ghent, Belgium; Peter Vandamme, Ghent University, Faculty of Science, Laboratory of Microbiology, Ghent, Belgi
ABSTRACT: Beer is a beverage with good microbiological stability because it contains almost no oxygen and nutrients for bacterial growth. In addition, low pH, high CO2 content, and the presence of ethanol and antibacterial hop compounds ensure microbial stability. Nevertheless, beer spoilage induced by bacteria is a common problem in the brewing industry and these spoilage bacteria typically cause visible turbidity, acidity, and off-flavors. Currently, these bacteria are detected with culture-dependent methods using selective media or with faster identification methods such as DNA typing, ribotyping, and other PCR-based techniques. These approaches are notoriously laborious, expensive, time-consuming, and, moreover, lack specificity and sensitivity. The present study aims to develop a quick, specific, and inexpensive method to detect and identify beer spoilage bacteria in the brewing industry. To achieve this, an extensive database comprising MALDI-TOF MS profiles of more than 260 established and accurately identified contaminants and beer spoilage strains was built. In addition to these strains, strains of the same species originating from other niches, besides spoiled beer, were also included in order to encompass the phenotypic diversity of the spoilage species. Among others, strains of Lactobacillus brevis (29), L. lindneri (3), “L. brevisimilis” (1), L. buchneri (5), L. coryniformis (1), L. plantarum (8), L. parabuchneri (15), L. paracollinoides (2), L. perolens (10), Pediococcus damnosus (9), Pediococcus inopinatus (10), Pectinatus cerevisiiphilus (1), Pectinatus frisingensis (2), Selenomonas lacticifex (1), Megasphaera cerevisiae (2), and Zymophilus raffinosivorans (2) were included in the database. The resulting set of profiles (±6,500 good quality profiles) allowed the assignment of reproducible species-specific biomarker peaks for all spoilage species. All strains were not only cultured under species-specific conditions (type medium, growth temperature, oxygen requirements, growth time), but also on selective and non-selective media. Different media were used to enable the exclusion of medium-associated peaks from species-specific biomarker peaks. Consequently, identification of novel beer spoilage isolates can be easily and rapidly performed. Nevertheless, the final aim of this research was to detect and identify these bacteria in a spoiled sample with minimal, time-consuming culture steps. Financial support was provided by the Research Fund of the University College Ghent.
Anneleen Wieme graduated in 2009 as a master in industrial sciences biochemistry at the University College Ghent. Currently, she is working at the University College Ghent, and in association with Ghent University she is performing her Ph.D. studies at the Laboratory of Microbiology at the Faculty of Sciences. In the future the results of her Ph.D. thesis, “Exploration of MALDI-TOF MS as a Fast Identification Tool for Beer Spoilage Bacteria,” will help the brewing industry in quickly identifying and controlling bacterial beer spoilage.