Effect of Glyphosate on Fusarium Head Blight in Wheat and Barley Under Different Soil Tillages.

Fusarium head blight (FHB) is a serious disease in the wet conditions of eastern Canada. Tillage practices and herbicide applications have been reported to influence disease intensity. This study aimed to determine the effect of glyphosate on FHB development in wheat and barley and on Fusarium graminearum inoculum production under different soil tillages. The experiment was performed during 2 years (2007 and 2008) at two different sites in Quebec, Canada. Six trials were set in both sites, combining two cereal species (wheat and barley) and three soil tillages: moldboard plow, spring tillage (minimum-till), and direct drilling. For each trial, glyphosate or other herbicides were applied on Roundup Ready soybean the year preceding cereal crops, constituting the main plots. The next year, three wheat and three barley cultivars were sown as subplots. FHB index, Fusarium-damaged kernels (FDK), deoxynivalenol (DON) content, and F. graminearum inoculum production were measured. Glyphosate had no significant effect on FHB index, FDK, or DON content, whatever the trial and the site. F. graminearum inoculum production was enhanced by glyphosate in only 1 of 12 trials. Cultivar effect was highly significant on DON content. The relationship between F. graminearum inoculum from soybean residues and DON content was weak.

Identification of metabolites related to mechanisms of resistance in barley against Fusarium graminearum, based on mass spectrometry.

Fusarium head blight (FHB) is an economically important disease of the family Triticeae, as, apart from yield reduction it also causes quality deterioration by producing mycotoxins. Host resistance is the most promising way to control the disease. Metabolic profiling was applied to identify resistance related (RR) metabolites against Fusarium graminearum in five FHB-resistant genotypes ('Chevron', 'H5277-44', 'H5277-164', 'M92-513' and 'M122') relative to one FHB-susceptible genotype ('Stander'). The disease severity was assessed in greenhouse to group the genotypes based on FHB-resistance. The disease was quantified as the proportion of diseased spikelets (PSD) and the area under the disease progress curve (AUDPC). Spikelets were collected at 72 h post inoculation. Metabolites were extracted into an aqueous solution of methanol and analyzed using a LC-hybrid-MS system. Metabolite abundances were subjected to a resistant versus susceptible pair-wise analysis, using a t test. Resistance related (RR) metabolites, both constitutive (RRC) and induced (RRI), were identified amongst metabolites whose levels were significantly higher in resistant genotype than in susceptible. Among 1,430 RR metabolites, 115 were putatively identified. These RR metabolites belonged to different chemical groups: fatty acids: linolenic acid; phenylpropanoids: p-coumaric, sinapic acid; flavonoids: naringenin, kaempferol glucoside, catechol glucoside. In addition, resistance indicator metabolites, such as deoxynivalenol (DON) and DON-3-O-glucoside (D3G) were also detected. The amount of total DON synthesized converted to D3G (PDC) was the greatest in resistant genotype 'Chevron' (PDC = 0.76). The role of the resistance-related and resistance-indicator metabolites on plant defense, and their use as potential biomarkers to screen barley genotypes for FHB resistance is discussed.

Mass spectrometry based metabolomics to identify potential biomarkers for resistance in barley against fusarium head blight (Fusarium graminearum).

Resistance in Triticeae to fusarium head blight (FHB) is quantitatively inherited. Metabolomics as a tool was used to better understand the mechanisms of resistance and to identify potential FHB resistance biomarker metabolites in barley. Five FHB-resistant two-row barley genotypes (CIho 4196, Zhedar-1, Zhedar-2, Fredrickson, and Harbin-2r) and one FHB-susceptible genotype (CH 9520-30) were each inoculated with either pathogen-suspension or mock-solution. Disease severity, quantified as the proportion of spikelets diseased, varied among genotypes, being the greatest in CH 9520-30. Spikelets were sampled, metabolites extracted with aqueous methanol, and analyzed using an LC-ESI-LTQ-Orbitrap system. A pair wise, resistant vs. susceptible, t-test identified 1774 significant treatment peaks. Canonical discriminant analysis of peak abundance allowed the genotypes to be sorted into three clusters: (i) CH9520-30, (ii) Harbin-2r, (iii) the remaining four genotypes. The t-test was further used to identify resistance-related (RR) and pathogenesis-related (PR) metabolites. The pathogen-produced virulence factor deoxynivalenol (DON), and its detoxification product, DON-3-O-glucoside (D3G) were designated as resistance indicator (RI) metabolites. Metabolites (RR, PR, or RI) occurring in at least two resistant genotypes, showing a two-fold or greater abundance in resistant vs. susceptible lines, and also known to have plant defense functions were selected as potential FHB resistance biomarker metabolites. These included phenylalanine, p-coumaric acid, jasmonate, linolenic acid, total DON produced (TDP), and the proportion of DON converted to D3G (PDC). Total DON was the lowest in CIho 4196, while PDC was the highest in Zhedar-2. The application of RR, PR, and RI metabolites as potential biomarkers to enhance resistance is discussed.

Mass spectrometry-based metabolomics application to identify quantitative resistance-related metabolites in barley against Fusarium head blight.

Quantitative resistance is generally controlled by several genes. More than 100 resistance quantitative trait loci (QTLs) have been identified in wheat and barley against Fusarium head blight (FHB), caused by Gibberella zeae (anamorph: Fusarium graminearum), implying the possible occurrence of several resistance mechanisms. The objective of this study was to apply metabolomics to identify the metabolites in barley that are related to resistance against FHB. Barley genotypes, Chevron and Stander, were inoculated with mock or pathogen during the anthesis stage. The disease severity was assessed as the proportion of spikelets diseased. The genotype Chevron (0.33) was found to have a higher level of quantitative resistance than Stander (0.88). Spikelet samples were harvested at 48 h post-inoculation; metabolites were extracted and analysed using an LC-ESI-LTQ-Orbitrap (Thermo Fisher, Waltham, MA, USA). The output was imported to an XCMS 1.12.1 platform, the peaks were deconvoluted and the adducts were sieved. Of the 1826 peaks retained, a t-test identified 496 metabolites with significant treatment effects. Among these, 194 were resistance-related (RR) constitutive metabolites, whose abundance was higher in resistant mock-inoculated than in susceptible mock-inoculated genotypes. Fifty metabolites were assigned putative names on the basis of accurate mass, fragmentation pattern and number of carbons in the formula. The RR metabolites mainly belonged to phenylpropanoid, flavonoid, fatty acid and terpenoid metabolic pathways. Selected RR metabolites were assayed in vitro for antifungal activity on the basis of fungal biomass production. The application of these RR metabolites as potential biomarkers for screening and the potential of mass spectrometry-based metabolomics for the identification of gene functions are discussed.