Abstract
Citrus Huanglongbing (HLB) is one of the most destructive citrus diseases worldwide, and is associated with the phloem-limited plant pathogenic bacteria Candidatus Liberibacter species. However, there is a latency period during which newly infected trees do not show symptoms, creating challenges for the early detection of HLB. In order to establish a method for rapid detection and to assess the metabolite differences between healthy and HLB-affected Newhall navel oranges, we used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to study asymptomatic and symptomatic leaf extracts compared with healthy leaves. The results showed that healthy, asymptomatic, and symptomatic leaves were distinguishable using MALDI-TOF-MS combined with multivariable analysis. Discriminant analysis (DA) results showed that the accuracy of discrimination of the training set and the success rate of cross-validation analysis were both 100%. Blind testing revealed that nine validation samples were correctly classified to their corresponding group. In addition, 32 MS peaks of metabolites had significant differences between healthy and different HLB-affected navel orange leaves. Among 32 MS peaks, the relative content of nine substances showed an upward trend, and 19 metabolites showed a downward trend, including a significant decrease in malate and citrate, with an increase in HLB bacterial populations. Malate and citrate were found to be specifically reduced in infected leaves regardless of whether symptoms appeared. Thus, they could be used as potential biomarkers for early detection of HLB, reducing false-negative results caused by uneven distribution of the HLB bacterial pathogen. This novel method can efficiently differentiate HLB-affected samples from the host population and provide new information for early detection of HLB in citrus. The entire process from metabolite extraction to the collection of mass spectra of citrus leaves was a simple operation, with no need for sterile conditions. We believe this strategy has significant implications for rapid and effective HLB screening. Graphical abstract.
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