UNTARGETED METABOLOMICS REVEALS MAIZE METABOLITES INVOLVED IN RESISTANCE AGAINST FUSARIUM INFECTION

Fusarium verticillioides (FV) is the causal agent of Fusarium ear rot (FER) in maize and contaminates the grain with fumonisins, carcinogen mycotoxins. A metabolomic approach was applied in order to reveal the mechanism of host resistance towards this pathogen. Plants of resistant (R) and susceptible (S) genotypes were grown in glasshouse in a randomized block design. The metabolic profiles of untreated, mock-and FV-inoculated maize kernels, sampled at 72 hours after inoculation (hpi), were investigated with liquid chromatography in combination with high resolution mass spectrometry. Five biological replicates were taken for each condition. The use of stable isotopic labelling (SIL) combined to MetExtract algorithm allowed the automatic detection and prediction of carbon atoms of only compounds of biological origin. Features pairs were grouped according to retention time, m/z and combination of both ionization polarities. The most intense ion species was selected for each feature group and 534 feature groups, corresponding to likewise metabolites, were issued. Several databases were screened for the metabolite search of the highest m/z within each feature group restricted by the count of the carbon atoms. At least one database entry was assigned for 119 metabolites. Moreover, 11 metabolites could be identified through the screening of 129 standard compounds, including key amino acids for the secondary metabolism, a flavonoid, N-hydroxynnamic acid amides, intermediates in synthesis of lignin and lignans, plant hormones. Multivariate statistics was used on the whole data set of 534 imputed range-scaled metabolites. In principal component analyses FV- samples were grouped separately from other samples, with PC1 explaining 42.7% of the total metabolic variation, PC2 (discriminates genotypes) 28.9% and PC3 7.5%. Also in Heat Map, FV samples appeared clearly separated from the others, as well as mock-and control samples were grouped together according to the genotype. Different clusters of metabolite could be recognized depending on the abundance levels in the samples. Several Student t test were applied to the data matrix of 534 metabolites, focusing on comparison between the untreated samples (metabolites related to “constitutive resistance”) and comparisons between the mock and FV-inoculated samples (“FV responsive” metabolites). A total of 222 metabolites resulted significantly affected by FV treatment. Annotation revealed that a part was involved in the synthesis of oxygenated fatty acids (oxylipins), in the phenylpropanoid pathway, flavonoids, benzoxizanoid biosynthesis, hydroxycinnamic acid amides and the metabolism of the aromatic amino acids. 90 metabolites resulted significantly different between the untreated samples of the two genotypes, belonging to the pathways of phenylpropanoids, benzoxizanoids, oxylipins, suggesting that there is a different abundance of these metabolites already in the untreated samples and their altered level is kept and enhanced at 72 hpi.