Using Spores for Fusarium spp. Classification by MALDI-Based Intact Cell/Spore Mass Spectrometry

Using Spores for Fusarium spp. Classification by MALDI-Based Intact Cell/Spore Mass Spectrometry

Martina Marchetti-Deschmann¹*, Wolfgang Winkler¹, Hongjuan Dong¹, Hans Lohninger¹, Christian P. Kubicek² and Günter Allmaier¹¹Institute of Chemical Technologies and Analytics, Vienna University of Technology, Getreidemarkt 9/164, AT-1060 Vienna, Austria
²Institute of Chemical Engineering, Vienna University of Technology, Getreidemarkt 9/166, AT-1060 Vienna, Austria

Article history:
Received March 31, 2012
Accepted July 26, 2012

Key words:
intact cell/spore mass spectrometry, fungi, Fusarium, species classification

Summary:
Fusarium is a widespread genus of filamentous fungi and a member of the soil microbial community. Certain subspecies are health threatening because of their mycotoxin production that affects the human and animal food chain. Thus, for early and effective pest control, species identification is of particular interest; however, differentiation on the subspecies level is challenging and time-consuming for this fungus. In the present study, we show the possibilities of intact cell mass spectrometry for spore analysis of 22 different Fusarium strains belonging to six Fusarium subspecies. We found that species differentiation is possible if mass spectrometric analyses are performed under well-defined conditions with fixed parameters. A critical point for analysis is a proper sample preparation of spores, which increases the quality of mass spectra with respect to signal intensity and m/z value variations. It was concluded that data acquistion has to be performed automatically; otherwise, user-specific variations are introduced generating data which cannot fit the existing datasets. Data that show clearly that matrix-assisted laser desorption ionization-based intact cell/intact spore mass spectrometry (IC/ISMS) can be applied to differentiate closely related Fusarium spp. are presented. Results show a potential to build a database on Fusarium species for accurate species identification, for fast response in the case of infections in the cornfield. We furthermore demonstrate the high precision of our approach in classification of intact Fusarium species according to the location of their collection.

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