Literature DB >> 24549193

Differentiation of Lactobacillus brevis strains using Matrix-Assisted-Laser-Desorption-Ionization-Time-of-Flight Mass Spectrometry with respect to their beer spoilage potential.

Carola C Kern1, Rudi F Vogel1, Jürgen Behr2.   

Abstract

Lactobacillus (L.) brevis is one of the most frequently encountered bacteria in beer-spoilage incidents. As the species Lactobacillus brevis comprises strains showing varying ability to grow in beer, ranging from growth in low hopped wheat to highly hopped pilsner beer, differentiation and classification of L. brevis with regard to their beer-spoiling ability is of vital interest for the brewing industry. Matrix-Assisted-Laser-Desorption-Ionization-Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) has been shown as a powerful tool for species and sub-species differentiation of bacterial isolates and is increasingly used for strain-level differentiation. Seventeen L. brevis strains, representative of different spoilage types, were characterized according to their tolerance to iso-alpha-acids and their growth in wheat-, lager- and pilsner beer. MALDI-TOF MS spectra were acquired to perform strain-level identification, cluster analysis and biomarker detection. Strain-level identification was achieved in 90% out of 204 spectra. Misidentification occurred nearly exclusively among strains belonging to the same spoilage type. Though spectra of strongly beer-spoiling strains showed remarkable similarity, no decisive single markers were detected to be present in all strains of one group. However, MALDI-TOF MS spectra can be reliably assigned to the corresponding strain and thus allow to track single strains and connect them to their physiological properties.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Beer spoilage; Lactobacillus brevis; MALDI-TOF MS

Mesh:

Year:  2013        PMID: 24549193     DOI: 10.1016/j.fm.2013.11.015

Source DB:  PubMed          Journal:  Food Microbiol        ISSN: 0740-0020            Impact factor:   5.516


  7 in total

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  7 in total

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