数字农科院2.0

A multi-channel CRISPR-based method for rapid, sensitive detection of four diseases of Brassica rapa in the field

文献类型： 外文期刊

作者： Liu, Xiaojing;Su, Tongbing;Xin, Xiaoyun;Li, Peirong;Wang, Weihong;Song, Cancan;Zhao, Xiuyun;Zhang, Deshuang;Yu, Yangjun;Wang, Jiao;Li, Ning;Wang, Miao;Zhang, Fenglan;Yu, Shuancang

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期刊名称： HORTICULTURE RESEARCH

ISSN： 2662-6810

年卷期： 2025 年 12 卷 3 期

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收录情况： SCIE（2025版） ; ; CSCD（2025-2026年度） ; ; 科技核心（2024版） ; ; 农林核心（2024版）

摘要： Pathogens significantly restrict the production of Brassica rapa (B. rapa L. ssp. Pekinensis), with climate change and evolving planting patterns exacerbating disease prevalence. Multichannel rapid diagnostic methods in the field can facilitate the early detection and control of diseases in B. rapa. Here, we established a multichannel lateral flow biosensor (LFB) combined with a CRISPR/Cas12a cleavage assay for the simultaneous detection of four B. rapa diseases. Key innovations of this study include: (1) High specificity and sensitivity, down to pathogen concentrations of 1.5 pg/mu l-due to the optimization of crRNA secondary structure: the more stable the crRNA, the higher its detection sensitivity. (2) Optimized visual detection parameters. We identified ideal concentration ratios for the visual fluorescence detection system: 50 nM Cas12a, 50 nM crRNA, and 500 nM ssDNA fluorescent probe. Furthermore, the optimal concentrations of components on the LFB detection system were 3 mu l SA-GNPs, 500 nM ssDNA test strip probe, 0.5 mg/ml biotin-BSA as the test line, and 1 mg/ml anti-FITC as the control line. (3) Field-Ready Cas-AIRPA Platform. We developed the on-site Cas-AIRPA platform for the simultaneous detection of B. rapa pathogens by combining rapid nucleic acid extraction and a four-channel lateral flow biosensor (4-LFB), which quickly provides disease-related information through a specific 2D barcode. Analysis of B. rapa samples in the field confirmed the suitability of the Cas-AIRPA platform for rapid (similar to 25 min) and simultaneous on-site detection of four diseases of B. rapa. This platform can also be adapted to detect other plant diseases in the field.

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