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Establishment and application of the Recombinase-Aided Amplification-Lateral Flow Dipstick detection method for Pantoea ananatis on rice

Pantoea ananatis is a major pathogen that causes the new bacterial blight in rice, and its symptoms very similar to rice bacterial blight. Therefore, there is a dire need for an accurate and rapid method for detecting P. ananatis. In this study, an early and rapid visual detection method for P. anan...

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Detalles Bibliográficos
Autores principales: Aiying, Wang, Ju, Luo, Cilin, Wang, Yuxuan, Hou, Baojun, Yang, Jian, Tang, Shuhua, Liu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10193322/
https://www.ncbi.nlm.nih.gov/pubmed/37363287
http://dx.doi.org/10.1007/s13313-023-00918-8
Descripción
Sumario:Pantoea ananatis is a major pathogen that causes the new bacterial blight in rice, and its symptoms very similar to rice bacterial blight. Therefore, there is a dire need for an accurate and rapid method for detecting P. ananatis. In this study, an early and rapid visual detection method for P. ananatis was established. Using GyrB gene as the target sequence, an innovative recombinase-aided amplification detection system integrated with a lateral flow dipstick (RAA-LFD) was constructed. The optimized RAA-LFD detection method can be initiated at body temperature and does not rely on precise instruments. It does not require DNA extraction and can be used directly with plant tissue fluids. The results can be visualized after 10 minutes of amplification. The specificity and sensitivity tests showed that the RAA-LFD method could detect P. ananatis, whereas other common plant pathogens were not detected, and its detection sensitivity for P. ananatis DNA reached 100 copies/µL. The detection of diseased tissues indicated that this method could accurately detect P. ananatis in artificially inoculated rice tissues in the early stages of infection before symptoms. The RAA-LFD detection system established in this study is simple and fast, with visual results, excellent specificity, and high sensitivity. It is semi-quantitative and should be used for the early detection and rapid field diagnosis of new leaf blight, which provides technical support for the early warning and real-time detection of field samples.