AUTHOR=Wang Xiang , Wang Lai-Fa , Cao Ye-Fan , Yuan Yan-Zhi , Hu Jian , Chen Zu-Hai , Zhu Fei , Wang Xi-Zhuo TITLE=Bursaphelenchus xylophilus detection and analysis system based on CRISPR – Cas12 JOURNAL=Frontiers in Plant Science VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2022.1075838 DOI=10.3389/fpls.2022.1075838 ISSN=1664-462X ABSTRACT=

Pine wilt disease is caused by the pine wood nematode (Bursaphelenchus xylophilus) and leads to wilting and death of pines. It is one of the most damaging diseases of pines worldwide. Therefore, accurate and rapid detection methods are of great importance for the control of B. xylophilus. Traditional detection methods have some problems, such as being time-consuming and requiring expensive instruments. In this study, the loop-mediated isothermal amplification (LAMP) and clustered regularly interspaced short palindromic repeats (CRISPR) were used to establish a set of intelligent detection and analysis system for B. xylophilus, called LAMP-CRISPR/Cas12a analysis, which integrated field sampling, rapid detection and intelligent control analysis. The process can be completed within 1 hour, from sample pretreatment and detection to data analysis. Compared with the single LAMP method, the LAMP-CRISPR/Cas12a assay uses species-specific fluorescence cleavage to detect target amplicons. This process confirms the amplicon identity, thereby avoiding false-positive results from non-specific amplicons, and the large amounts of irrelevant background DNA do not interfere with the reaction. The LAMP-CRISPR/Cas12a assay was applied to 46 pine wood samples and the samples carrying B. xylophilus nematodes were successfully identified. To meet the needs of different environments, we designed three methods to interpret the data: 1) naked eye interpretation; 2) lateral flow biosensor assay; and 3) integrated molecular analysis system to standardize and intellectualize the detection process. Application of the B. xylophilus detection and analysis system will reduce the professional and technical requirements for the operating environment and operators and help to ensure the accuracy of the detection results, which is important in grass-root B. xylophilus detection institutions.