Spectroscopy-based metabolomics for early detection of Citrus Tristeza Virus infection

Metabolomics is a powerful tool for studying various aspects of plant physiology and biology, which regulate plant growth, development, and stress response. To protect themselves from pathogens, plants produce a wide range of secondary metabolites through a network of different biosynthetic pathways. The analysis of metabolomic data allows the identification of groups of metabolites, whose concentration significantly changes already at the first stages of disease. Metabolomics can be utilized as a tool to detect host-pathogen interaction and also to differentiate the type of compounds produced in resistant and susceptible phenotypes.1 Recently, our lab has been involved in a number of projects based on the application of spectroscopy-based metabolomics for the study of plant diseases, including Erwinia amylovora infections in pear2 and Xylella fastidiosa infections in olive crops.3,4 Furthermore, some important clues on the resistance phenomenon against Xylella fastidiosa were obtained by investigating the composition of the xylem sap of plant species characterized by a different phenotype towards Xf subspecies pauca.5 This study focuses on Citrus Tristeza Virus (CTV) infections in citrus trees. CTV is the causal agent of “tristeza”, one of the most destructive viral diseases of citrus. The CTV is phloem-limited and its transmission into new geographic areas occurs by the introduction of infected plants or budwood, with subsequent local dispersal in a semi-persistent mode by several aphid species.6 In this study, a combined approach by nuclear magnetic resonance (NMR) and hyperspectral reflectance (HSR) spectroscopies is used. NMR is the most robust and non-destructive technique for the elucidation of unknown compounds: as it is not selective, it allows for an unbiased view of the chemical composition of the sample. HSR provides a rapid detection tool, requires limited sample preparation, and is a non-invasive technique for plant disease detection. Among the objectives of the present study is the identification of possible biomarkers of CTV infection by NMR and subsequent correlation with specific HSR wavelengths. The latter can be advantageously exploited for the development of sensors for the early detection of CTV infections.