Cuperlovic-Culf Miroslava

Cuperlovic-Culf Miroslava

Title: Metabolomics analysis of the effect of changed CO2 concentration on the wheats response to Fusarium Head Blight.

Cuperlovic-Culf Miroslava

National Research Council Canada, Canada

Biography

Miroslava Cuperlovic-Culf is a Senior Research Officer and leader of Scientific Data Mining team at National Research Council of Canada. She has a Ph.D. in BioPhysical Chemistry from University of California, USA and Postdoctoral training in Biophysics from University of British Columbia, Canada. Miroslava has worked for a number of years in the application of metabolomics and transcriptomics in life sciences. She has authored a book in the application of NMR Metabolomics as well as many articles and book chapters. With several collaborators in Canada and USA she is working on the application of metabolomics and metabolism modeling for the development of improved wheat varieties. She lives and works in Ottawa, Canada.

Abstract

Diseases of agricultural crops caused by fungi have devastating economic and health effects. Fusarium head blight (FHB) is one of the most damaging diseases of wheat and other small grain cereals. FHB contamination of wheat has been steadily increasing over the last decade leading to an increase in the associated risk of mycotoxin contamination in food and feed. Climate change and associated rise in CO2 levels are hypothetical causes of this rise but their effects on Fusarium graminearum and the spread of FHB are still unknown. In this study the defense response of wheat plants grown at ambient (400 ppm) and elevated (800 ppm) CO2 was evaluated and compared. Plant and fungal metabolites play a major role in defense and virulence with significant differences in metabolic response in resistant and susceptible plants. 1D and 2D 1H NMR spectroscopy performed in this work have provided detailed metabolite information leading to possible metabolic markers discriminating metabolic changes in wheat subtypes with different resistance and at changing CO2 levels. Methodology previously established in our group for metabolite quantification from NMR data that automatically aligns spectra of standards and samples prior to quantification utilizing multivariate linear regression optimization of spectra of assigned metabolites to samples’ 1D spectra is described and used. Fusarium infection-induced metabolic changes in different conditions will be discussed in the context of metabolic network and resistance.