Literature DB >> 28511108

Wine yeasts identification by MALDI-TOF MS: Optimization of the preanalytical steps and development of an extensible open-source platform for processing and analysis of an in-house MS database.

Cristina Gutiérrez1, M Ángeles Gómez-Flechoso2, Ignacio Belda3, Javier Ruiz3, Nour Kayali1, Luis Polo1, Antonio Santos4.   

Abstract

Saccharomyces cerevisiae is the most important yeast species for the production of wine and other beverages. In addition, nowadays, researchers and winemakers are aware of the influence of non-Saccharomyces in wine aroma complexity. Due to the high microbial diversity associated to several agro-food processes, such as winemaking, developing fast and accurate methods for microbial identification is demanded. In this context, MALDI-TOF MS mass fingerprint provides reliable tool for fast biotyping and classification of microorganisms. However, there is no versatile and standardized method for fungi currently available. In this study, an optimized sample preparation protocol was devised for the biotyping of yeasts of oenological origin. Taking into account that commercially available reference databases comprise almost exclusively clinical microorganisms, most of them bacteria, in the present study a database of yeasts isolated from vineyards and wineries was created, and its accuracy was tested using industrial and laboratory yeast strains. In addition, the implementation of a program for MALDI-TOF MS spectra analysis has been developed as an extensible open-source platform for MALDI data processing and analysis with statistical techniques that has arisen from our previous experience working with MALDI data. The software integrates two R packages for raw MALDI data preprocessing: Continuous Wavelet Transform (CWT)-based algorithm and MassSpecWavelet. One of the advantages of the CWT is that it can be directly applied to a raw spectrum, without prior baseline correction. Mass fingerprints of 109 S. cerevisiae strains and 107 non-Saccharomyces isolates were generated by MALDI-TOF MS upon optimized sample preparation and instrument settings and analyzed for strain, species, and genus-level differentiation. As a reference method, for S. cerevisiae differentiation at strain level, the analysis of the polymorphism in the inter-delta region was chosen. The data revealed that MALDI-TOF MS can be used for the rapid and accurate identification of S. cerevisiae and non-Saccharomyces isolates at genus and species level. However, S. cerevisiae differentiation at strain level was not successfully achieved, and the differentiation among Metschnikowia species was also difficult.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  MALDI-TOF MS; Non-Saccharomyces; Saccharomyces cerevisiae; Wine yeasts; Yeast identification

Mesh:

Year:  2017        PMID: 28511108     DOI: 10.1016/j.ijfoodmicro.2017.05.003

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


  4 in total

1.  Identification of Clostridium spp. derived from a sheep and cattle slaughterhouse by matrix-assisted laser desorption and ionization-time of flight mass spectrometry (MALDI-TOF MS) and 16S rDNA sequencing.

Authors:  Farzaneh Bakhtiary; Hamid Reza Sayevand; Marlene Remely; Berit Hippe; Alexander Indra; Hedayat Hosseini; Alexander G Haslberger
Journal:  J Food Sci Technol       Date:  2018-06-22       Impact factor: 2.701

2.  Introducing a Cell-Free Approach for the Identification of Brewing Yeast (Saccharomyces cerevisiae) Strains Using MALDI-TOF MS.

Authors:  Elsa Gorre; Cathy Muste; Kevin G Owens
Journal:  J Am Soc Mass Spectrom       Date:  2018-08-07       Impact factor: 3.109

3.  Revealing the Yeast Diversity of the Flor Biofilm Microbiota in Sherry Wines Through Internal Transcribed Spacer-Metabarcoding and Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry.

Authors:  Juan Carbonero-Pacheco; Jaime Moreno-García; Juan Moreno; Teresa García-Martínez; Juan Carlos Mauricio
Journal:  Front Microbiol       Date:  2022-02-09       Impact factor: 5.640

4.  Predictive Potential of MALDI-TOF Analyses for Wine and Brewing Yeast.

Authors:  Junwen Zhang; Jeffrey E Plowman; Bin Tian; Stefan Clerens; Stephen L W On
Journal:  Microorganisms       Date:  2022-01-24
  4 in total

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