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Abstract
Tomato crops suffer attacks of various pathogens that cause large production losses. Late blight caused by Phytophthora infestans is a devastating disease in tomatoes because of its difficultly to control. Here, we applied metabolomics based on liquid chromatography–mass spectrometry (LC-MS) and metabolic profiling by matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) in combination with multivariate data analysis in the early detection of late blight on asymptomatic tomato plants and to discriminate infection times of 4, 12, 24, 36, 48, 60, 72 and 96 h after inoculation (hpi). MALDI-MS and LC-MS profiles of metabolites combined with multivariate data analysis are able to detect early-late blight-infected tomato plants, and metabolomics based on LC-MS discriminates infection times in asymptomatic plants. We found the metabolite tomatidine as an important biomarker of infection, saponins as early infection metabolite markers and isocoumarin as early and late asymptomatic infection marker along the post infection time. MALDI-MS and LC-MS analysis can therefore be used as a rapid and effective method for the early detection of late blight-infected tomato plants, offering a suitable tool to guide the correct management and application of sanitary defense approaches. LC-MS analysis also appears to be a suitable tool for identifying major metabolites of asymptomatic late blight-infected tomato plants.
Highlights
Tomato (Solanum lycopersicum) is one of the most widespread vegetables worldwide, with more than 160 million tons produced in 2013 alone [1]
In the liquid chromatography–mass spectrometry (LC-MS) untargeted metabolomics analysis, the ion chromatograms obtained in the ESI positive and negative ion modes showed no apparent differences between the infected and non-infected samples, but the
In the first step of the statistical processing, the principal component analysis (PCA), a technique used for dimensionality reduction of multivariate data whilst preserving most of the variance [40], was applied to LC-MS metabolic profiles data in order to find cluster of samples
Summary
Tomato (Solanum lycopersicum) is one of the most widespread vegetables worldwide, with more than 160 million tons produced in 2013 alone [1]. Mainly as fresh fruits or processed products, due to their nutritional and beneficial properties to human health [2,3,4]. These crops, suffer attacks of various pathogens such, as viruses, bacteria, fungi and nematodes, causing substantial production losses. Late blight, caused by the phytopathogenic oomycete Phytophthora infestans, is one of the most devastating tomato diseases, demanding high chemical input for disease control worldwide [5,6,7,8]. The expenses due to tomato late blight and control measures are estimated to exceed $5 billion annually worldwide [10]. The development of resistant cultivars is an important alternative for pathogen management and control, but as yet there are no highly resistant cultivars
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