Ye Ram Cho
Department of Systems Biology, Division of Life Sciences, and Institute for Life Science and Biotechnology, Yonsei University
Seoul, Seoul-t'ukpyolsi, Republic of Korea
Boyoung Lee
Department of Systems Biology, Division of Life Sciences, and Institute for Life Science and Biotechnology, Yonsei University
Seoul, Seoul-t'ukpyolsi, Republic of Korea
Ju Yeon Song
Department of Systems Biology, Division of Life Sciences, and Institute for Life Science and Biotechnology, Yonsei University
Seoul, Seoul-t'ukpyolsi, Republic of Korea
Jihyun F. Kim
Department of Systems Biology, Division of Life Sciences, and Institute for Life Science and Biotechnology, Yonsei University
Seoul, Seoul-t'ukpyolsi, Republic of Korea
Fire blight, caused by the phytopathogen Erwinia amylovora, is a destructive disease that inflicts significant economic losses on the apple and pear industries each year. Despite advances in understanding the pathogen, including whole-genome sequencing of isolates, controlling fire blight remains challenging due to limited treatment options and symptom overlap with other pome pathogens like Erwinia pyrifoliae. To address this, we developed a CRISPR/Cas13a-based detection system to specifically identify E. amylovora and distinguish it from E. pyrifoliae. Through comparative genome analysis and extensive screening of CRISPR RNAs and recombinase polymerase amplification primers, the system achieved highly sensitive detection—identifying as little as ten fmol of mRNA, ten bacterial cells, and even geographically distinct isolates. Its utility as a point-of-care diagnostic tool was further enhanced with a lateral flow assay for rapid and simple field deployment. Beyond early detection and eradication, this system can also identify live bacteria through mRNA detection and track disease progression by distinguishing region-specific isolates, offering a valuable tool for fire blight monitoring and management.