Metabolomics approaches for the discrimination of disease suppressive soils for Rhizoctonia solani AG8 in cereal crops using 1H NMR and LC-MS.

The suppression of soilborne crop pathogens such as Rhizoctonia solani AG8 may offer a sustainable and enduring method for disease control, though soils with these properties are difficult to identify. In this study, we analysed the soil metabolic profiles of suppressive and non-suppressive soils over 2 years of cereal production. We collected bulk and rhizosphere soil at different cropping stages and subjected soil extracts to liquid chromatography-mass spectrometry (LC-MS) and proton nuclear magnetic resonance spectroscopy (1H NMR) analyses. Community analyses of suppressive and non-suppressive soils using principal component analyses and predictive modelling of LC-MS and NMR datasets respectively, revealed distinct biochemical profiles for the two soil types with clustering based on suppressiveness and cropping stage. NMR spectra revealed the suppressive soils to be more abundant in sugar molecules than non-suppressive soils, which were more abundant in lipids and terpenes. LC-MS features that were significantly more abundant in the suppressive soil were identified and assessed as potential biomarkers for disease suppression. The structures of a potential class of LC-MS biomarkers were elucidated using accurate mass data and MS fragmentation spectrum information. The most abundant compound found in association with suppressive soils was confirmed to be a macrocarpal, which is an antimicrobial secondary metabolite. Our study has demonstrated the utility of environmental metabolomics for the study of disease suppressive soils, resulting in the discovery of a macrocarpal biomarker for R. solani AG8 suppressive soil which can be further studied functionally in association with suppression pot trials and microbial isolation studies. Crown