Assessment of discriminatory power of three different fingerprinting methods based on killer toxin sensitivity for the differentiation of Saccharomyces cerevisiae strains

Aims: A panel composed of 44 taxonomically certified strains of Saccharomyces cerevisiae of different origin was used to evaluate the discriminatory power of three different fingerprinting methods based on sensitivity towards 24 killer toxins. Methods and Results: Binary data matrix (BDM), triplet data matrix (TDM) and numerical data matrix (NDM) were used as fingerprinting methods. NDM possessed the highest discriminatory power, assessed through the Simpson's, and Hunter and Gaston's indices for the measurement of diversity. The upper limits of fingerprinting ability expressed by the three above methods have been also discussed. Conclusions: NDNI determined a significant increase of discriminatory power than the use of BDM or TDM, in terms of an effective amplification of their fingerprinting efficacy. Significance and Impact of the Study: The NDM fingerprinting method could find application in control laboratories for the discrimination of yeast strains of industrial importance or covered by patent.