Non-invasive Presymptomatic Detection of Cercospora beticola Infection and Identification of Early Metabolic Responses in Sugar Beet.

Cercospora beticola is an economically significant fungal pathogen of sugar beet, and is the causative pathogen of Cercospora leaf spot. Selected host genotypes with contrasting degree of susceptibility to the disease have been exploited to characterize the patterns of metabolite responses to fungal infection, and to devise a pre-symptomatic, non-invasive method of detecting the presence of the pathogen. Sugar beet genotypes were analyzed for metabolite profiles and hyperspectral signatures. Correlation of data matrices from both approaches facilitated identification of candidates for metabolic markers. Hyperspectral imaging was highly predictive with a classification accuracy of 98.5-99.9% in detecting C. beticola. Metabolite analysis revealed metabolites altered by the host as part of a successful defense response: these were L-DOPA, 12-hydroxyjasmonic acid 12-O-ß-D-glucoside, pantothenic acid, and 5-O-feruloylquinic acid. The accumulation of glucosylvitexin in the resistant cultivar suggests it acts as a constitutively produced protectant. The study establishes a proof-of-concept for an unbiased, presymptomatic and non-invasive detection system for the presence of C. beticola. The test needs to be validated with a larger set of genotypes, to be scalable to the level of a crop improvement program, aiming to speed up the selection for resistant cultivars of sugar beet. Untargeted metabolic profiling is a valuable tool to identify metabolites which correlate with hyperspectral data.

The reproducibility of liquid chromatography separation technology and its potential impact on large scale plant metabolomics experiments.

Unraveling the constituents of biological samples using HPLC is a central core technology in metabolomics experiments. Consistency in retention time across many samples is a critical criterion for judging the quality of a data set, which must be met before further analysis are possible. Here, the performance of two ultra high-performance liquid chromatography (UHPLC) systems has been compared using an established separation protocol optimized for phenylpropanoids, a class of secondary compounds found in plants displaying intermediate polarity. The two systems differed markedly with respect to their reproducibility and pressure stability. The standard deviation of the retention time of representative peaks differs up to 30-folds between the systems. Adjustments made to the gradient profiles succeeded in equalizing their level of performance. However, the modifications made to the separation protocol reduced the quality of the separation, particularly of the more rapidly eluting components, and lengthened the run time.