A robust quantitative approach using SPME-GC-MS, identified the volatilome of the biocontrol agent, Aureobasidium pullulans

Sashika Yalage Don, Christopher Steel, Joanna Gambetta, Leigh Schmidtke

Research output: Other contribution to conferenceAbstractpeer-review


Microbial antagonists have been explored as ecofriendly disease management alternatives to synthetic fungicides. Production of antimicrobial volatile organic compounds (VOCs) has become popular due to their biodegradability and activity regardless of a physical contact of the targeted host. Quantitative identification of VOCs is important,as it provides the basis to formulate artificial volatile cocktails,strain selection and growth condition studies to improve VOCs production by biocontrol agents.To our knowledge, a robust automated technique for quantitative analysis of microbial VOCs has not been reported. Aureobasidium pullulans is a yeast-like fungus and a potential biocontrol agent. Initial experiments of our study demonstrated a supressed growth of Botrytis cinerea and Alternaria alternata by A. pullulans VOCs. In this context, we propose a novel approach for the quantitative analysis of A. pullulans VOCs by automated solid phase­ microextraction-gas chromatography-mass spectrometry (SPME-GC-MS), in an antagonist-pathogen interactive system. A. pullulans and either B. cinerea or A. alternata were grown on two separate PDA layers in a headspace vial. To facilitate accurate quantitation, an internal standard (2-methyl-4-pentanol in methanol) was introduced,through the septum of the screw cap, on to a paper disc glued on a strip of aluminium foil hanging on the wall, before GC-MS analysis. Multivariate Curve Resolution-Alternating Least Squares deconvolution of SPME-GC-MS spectra, enabled the identification of thirteen VOCs from A. pullulans. Acetone,2-heptanone,ethyl butyrate,3-methylbutyl acetate and 2-methylpropyl acetate were identified as new VOCs from A. pullulans. The variables importance in projection scores and selectivity ratio of partial least squares discriminant analysis models identified four compounds; ethanol,2-methyl-1-propanol, 3-methyl-1-butanol and
2-phenyl ethanol, as important VOCs that discriminate between A. pullulans and pathogens.These four compounds were quantified and ethanol was the highest abundant VOC in A. pullulans headspace. Our findings introduce a novel,robust, quantitative approach for microbial VOCs analyses in biocontrol studies.
Original languageEnglish
Number of pages1
Publication statusPublished - 2019
EventAustralasian Plant Pathology Society Conference - Melbourne Convention and Exhibition Centre, Melbourne, Australia
Duration: 26 Nov 201928 Nov 2019
https://researchoutput.csu.edu.au/admin/files/43820252/APP_2019_Program_Book_WEB_003_.pdf (Conference program)


ConferenceAustralasian Plant Pathology Society Conference
Abbreviated titleStrong Foundations, Future Innovations
Internet address


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