Literature DB >> 24929682

Identification of beer-spoilage bacteria using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

Anneleen D Wieme1, Freek Spitaels2, Maarten Aerts2, Katrien De Bruyne3, Anita Van Landschoot4, Peter Vandamme5.   

Abstract

Applicability of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for identification of beer-spoilage bacteria was examined. To achieve this, an extensive identification database was constructed comprising more than 4200 mass spectra, including biological and technical replicates derived from 273 acetic acid bacteria (AAB) and lactic acid bacteria (LAB), covering a total of 52 species, grown on at least three growth media. Sequence analysis of protein coding genes was used to verify aberrant MALDI-TOF MS identification results and confirmed the earlier misidentification of 34 AAB and LAB strains. In total, 348 isolates were collected from culture media inoculated with 14 spoiled beer and brewery samples. Peak-based numerical analysis of MALDI-TOF MS spectra allowed a straightforward species identification of 327 (94.0%) isolates. The remaining isolates clustered separately and were assigned through sequence analysis of protein coding genes either to species not known as beer-spoilage bacteria, and thus not present in the database, or to novel AAB species. An alternative, classifier-based approach for the identification of spoilage bacteria was evaluated by combining the identification results obtained through peak-based cluster analysis and sequence analysis of protein coding genes as a standard. In total, 263 out of 348 isolates (75.6%) were correctly identified at species level and 24 isolates (6.9%) were misidentified. In addition, the identification results of 50 isolates (14.4%) were considered unreliable, and 11 isolates (3.2%) could not be identified. The present study demonstrated that MALDI-TOF MS is well-suited for the rapid, high-throughput and accurate identification of bacteria isolated from spoiled beer and brewery samples, which makes the technique appropriate for routine microbial quality control in the brewing industry.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Beer-spoilage bacteria; Classifier-based analysis; Identification; MALDI-TOF MS; MLSA; Peak-based cluster analysis

Mesh:

Year:  2014        PMID: 24929682     DOI: 10.1016/j.ijfoodmicro.2014.05.003

Source DB:  PubMed          Journal:  Int J Food Microbiol        ISSN: 0168-1605            Impact factor:   5.277


  7 in total

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Journal:  J Am Soc Mass Spectrom       Date:  2018-08-13       Impact factor: 3.109

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Authors:  Ann-Sophie Schott; Jürgen Behr; Jennifer Quinn; Rudi F Vogel
Journal:  PLoS One       Date:  2016-10-26       Impact factor: 3.240

3.  Whole-Genome Sequence Analysis of Bombella intestini LMG 28161T, a Novel Acetic Acid Bacterium Isolated from the Crop of a Red-Tailed Bumble Bee, Bombus lapidarius.

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Journal:  PLoS One       Date:  2016-11-16       Impact factor: 3.240

4.  MALDI-TOF MS typing enables the classification of brewing yeasts of the genus Saccharomyces to major beer styles.

Authors:  Alexander Lauterbach; Julia C Usbeck; Jürgen Behr; Rudi F Vogel
Journal:  PLoS One       Date:  2017-08-09       Impact factor: 3.240

5.  Bacterial species identification using MALDI-TOF mass spectrometry and machine learning techniques: A large-scale benchmarking study.

Authors:  Thomas Mortier; Anneleen D Wieme; Peter Vandamme; Willem Waegeman
Journal:  Comput Struct Biotechnol J       Date:  2021-11-09       Impact factor: 7.271

6.  Burkholderia perseverans sp. nov., a bacterium isolated from the Restinga ecosystem, is a producer of volatile and diffusible compounds that inhibit plant pathogens.

Authors:  Jackeline Pereira Andrade; Harisson Guimarães de Souza; Larissa Carvalho Ferreira; Margo Cnockaert; Evelien De Canck; Anneleen D Wieme; Charlotte Peeters; Eduardo Gross; Jorge Teodoro De Souza; Phellippe Arthur Santos Marbach; Aristóteles Góes-Neto; Peter Vandamme
Journal:  Braz J Microbiol       Date:  2021-07-21       Impact factor: 2.214

7.  Identification and Classification for the Lactobacillus casei Group.

Authors:  Chien-Hsun Huang; Shiao-Wen Li; Lina Huang; Koichi Watanabe
Journal:  Front Microbiol       Date:  2018-08-22       Impact factor: 5.640

  7 in total

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