Fire blight, caused by Erwinia amylovora, is an economically devastating disease affecting apple and pear orchards, and reliable detection is critical for effective management. However, field detection is challenging due to inhibitory compounds and the time-consuming nature of nucleic acid extraction, which limits the speed and accessibility of current diagnostic methods. Here, we present a CRISPR-Cas13a-based diagnostic platform designed for rapid, amplification-free, and extraction- free detection directly from plant material. In regions such as Korea where E. pyrifoliae is endemic, high genomic similarity between the two Erwinia species complicates accurate discrimination and poses a significant challenge for disease management. We identified E. amylovora-specific (EA-specific) single nucleotide polymorphisms and designed a panel of CRISPR RNAs (crRNAs) across multiple housekeeping genes and the 16S rRNA V3 region. Systematic screening with both synthetic RNA and mRNA revealed new crRNAs that maintained species specificity and sensitivity, achieving detection within minutes. To enable field-compatible sample processing, we developed and optimized a robust alkaline lysis workflow based on sequential NaOH lysis and HCl neutralization, which effectively released RNA from bacterial cells and remained compatible with crude Malus domestica leaf lysates. Under these extraction-free conditions, the assay achieved rapid, EA-specific detection of 1 × 106 CFUs/reaction within 15 minutes without nucleic acid purification or thermal cycling in the presence of plant material. This study establishes a practical framework for CRISPR-Cas13a diagnostics in plant pathology and provides a low-infrastructure strategy that can improve the speed and accuracy of fire blight surveillance and broader agricultural biosecurity efforts.
Cho et al. (Fri,) studied this question.
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