Optimization of experimental and modelling parameters for the differentiation of beverage spoiling yeasts by Matrix-Assisted-Laser-Desorption/Ionization-Time-of-Flight Mass Spectrometry (MALDI-TOF MS) in response to varying growth conditions.

Abstract:

:The growth of spoiling yeasts in beverages results in reduced quality, economic and image losses. Therefore, biochemical and DNA-based identification methods have been developed but are mostly time-consuming and laborious. Matrix-Assisted-Laser-Desorption/Ionization-Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) could deliver discriminative peptide mass fingerprints within minutes and could thus be a rapid and reliable tool for identification and differentiation. However, routine analysis of yeasts by MALDI-TOF MS is yet impaired by low reproducibility and effects of different physiological states of organisms on the reliability of the identification method are still controversial. The aim of this study was to optimize sample preparation and measurement parameterization using three spoilage yeasts (Saccharomyces cerevisiae var. diastaticus, Wickerhamomyces anomalus and Debaryomyces hansenii). The influence of environmental or physiological parameters including oxygen availability, different nutrients, cell density and growth phase were analysed and revealed small differences in mass fingerprints. Yeasts grown in the presence or absence of oxygen were precisely differentiated along these differences in mass fingerprints and a crude classification of growth phase was possible. Cell concentration did not affect the spectra distinctly, neither qualitatively nor quantitatively, and an influence of available nutrients could not be measured in each case. However, core mass peaks remained constant under all tested conditions enabling reliable identification.

journal_name

Food Microbiol

journal_title

Food microbiology

authors

Usbeck JC,Kern CC,Vogel RF,Behr J

doi

10.1016/j.fm.2013.07.004

subject

Has Abstract

pub_date

2013-12-01 00:00:00

pages

379-87

issue

2

eissn

0740-0020

issn

1095-9998

pii

S0740-0020(13)00143-3

journal_volume

36

pub_type

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