In clinical diagnosis and fermentation industries there is a need for a method that allows for the
differentiation of yeast to the strain level (biotyping). The ideal biotyping method should be
accurate, simple, rapid and cost-effective, and capable of testing a large number of yeast
isolates. Matrix assisted laser desorption/ionization time of flight mass spectrometry has
emerged as a powerful biotyping tool for the identification of bacteria and clinical yeast isolates,
mainly Candida. It has been found that the MALDI-TOF MS signals from yeast are harder to
obtain than from bacteria. It has been reported by several research studies that a cell lysis step
is required to obtain a mass spectral signal for clinical Candida strains. To date an optimized
sample preparation protocol has not been devised for the biotyping of S. cerevisiae strains.
Studies on the identification of yeast using MALDI-TOF MS have focused primarily on clinical
Candida yeast isolates but have included very few S. cerevisiae strains. Furthermore these
yeast identification studies using MALDI-TOF MS have only achieved identification to the
species and not strain level. A major limiting attribute of MALDI-TOF MS for the accurate
identification of microbes, is its dependency on a comprehensive mass spectral database.
Bruker Daltonics is a pioneer and leader in providing innovative life science tools based on
mass spectrometry thus the Bruker Daltonics mass spectral database and state-of-the-art
instruments and accompanying software were selected for this study. The Bruker Daltonics
mass spectral database currently holds three thousand seven hundred and forty
microorganisms of which only a mere seven are S. cerevisiae strains.
Initially in this study, a number of parameters of a generic ethanol/formic acid protein
extraction procedure as originally described by Bruker Daltoincs were considered in the
development of a sample preparation protocol that yielded characteristic and highly
reproducible MALDI-TOF mass spectra. The parameters considered included cell number,
alcohol fixation, matrix solution and media. It was found that using the optimized sample
preparation protocol unique and highly reproducible mass spectral profiles were obtained for all
three S. cerevisiae strains. Multivariate analysis confirmed that the differences between all three
S. cerevisiae strains were statistically significant. For quality assurance, the spectra of the three
strains were sent for evaluation by Bruker Daltonics and were deemed suitable for the purpose
of biotyping.
The newly created ethanol/formic acid extraction procedure was used to generate an S.
cerevisiae mass spectral database comprising of forty-five S. cerevisiae strains within a local
context but also of global significance. The accuracy of the mass spectral database was
assessed using blind coded S. cerevisiae strains obtained from the Agricultural Research
Council Infruitec-Nietvoorbij (Institute for Deciduous Fruit, Vines and Wine), Stellenbosch, South
Africa. It was found that S. cerevisiae identification to the species and more importantly strain
level was achievable with relatively good accuracy. To determine the potential application of
MALDI-TOF MS as an accurate method for S. cerevisiae strain identification in industry, blind
coded S. cerevisiae strains were obtained from Natal Cane Products and subjected to MALDITOF
MS analysis. It was found that four of the pure cultures submitted were correctly identified
to the strain level and the three S. cerevisiae strains incorrectly identified may have been
contaminants or the result of incorrect optimization conditions for the fermentation. Thus MALDITOF
MS was shown to be an accurate identification tool, that may also be used to detect
contaminants or incorrect environmental conditions which can result in substantial losses. / Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2011.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ukzn/oai:http://researchspace.ukzn.ac.za:10413/5839 |
| Date | January 2011 |
| Creators | Moothoo-Padayachie, Anushka. |
| Contributors | Kruger, Hendrik Gert., Maguire, Glen Eamonn Mitchel., Govender, Thavendran., Govender, Patrick. |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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