CRISPR/Cas13a-based rapid detection method for porcine deltacoronavirus

Autor: Ran Luo, Zhimeng Cheng, Haoyu Wang, Qiyue Yang, Yongping Zeng, Yijun Yang, Yuankun Chen, Wenting Li, Xiao Liu
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Frontiers in Microbiology, Vol 15 (2024)
Druh dokumentu: article
ISSN: 1664-302X
DOI: 10.3389/fmicb.2024.1429486
Popis: BackgroundPorcine deltacoronavirus (PDCoV) is a newly discovered porcine intestinal pathogenic coronavirus with a single-stranded positive-sense RNA genome and an envelope. PDCoV infects pigs of different ages and causes acute diarrhea and vomiting in newborn piglets. In severe cases, infection leads to dehydration, exhaustion, and death in sick piglets, entailing great economic losses on pig farms. The clinical symptoms of PDCoV infection are very similar to those of other porcine enteroviruses. Although it is difficult to distinguish these viral infections without testing, monitoring PDCoV is very important because it can spread in populations. The most commonly used methods for the detection of PDCoV is qPCR, which is time-consuming and require skilled personnel and equipment. Many farms cannot meet the conditions required for detection. Therefore, it is necessary to establish a faster and more convenient method for detecting PDCoV.AimsTo establish a rapid and convenient detection method for PDCoV by combining RPA (Recombinase Polymerase Isothermal Amplification) with CRISPR/Cas13a.MethodsSpecific RPA primers and crRNA for PDCoV were designed, and the nucleic acids in the samples were amplified with RPA. Fluorescent CRISPR/Cas13a detection was performed. We evaluated the sensitivity and specificity of the RPA–CRISPR/Cas13a assay using qPCR as the control method.ResultsCRISPR/Cas13a-assisted detection was completed within 90 min. The minimum detection limit of PDCoV was 5.7 × 101 copies/μL. A specificity analysis showed that the assay did not cross-react with three other porcine enteroviruses.ConclusionThe RPA–CRISPR/Cas13a method has the advantages of high sensitivity, strong specificity, fast response, and readily accessible results, and can be used for the detection of PDCoV.
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