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. 2024 Jun 14;20(1):258.
doi: 10.1186/s12917-024-04116-6.

Development of a CRISPR/Cas12a-based fluorescent detection method of Senecavirus A

Affiliations

Development of a CRISPR/Cas12a-based fluorescent detection method of Senecavirus A

Wei He et al. BMC Vet Res. .

Abstract

Background: Senecavirus A (SVA), identified in 2002, is known to cause porcine idiopathic vesicular disease (PIVD), which presents with symptoms resembling other vesicular diseases. This similarity complicates field diagnosis. Conventional molecular diagnostic techniques are limited by their cost, sensitivity, and requirement for complicated instrumentation. Therefore, developing an effective and accurate diagnostic method is crucial for timely identification and isolation of affected pigs, thereby preventing further disease spread.

Methods: In this study, we developed a highly-specific and ultra-sensitive SVA detection method powered by CRISPR/Cas12a. To enhance the availability in laboratories with varied equipment conditions, microplate reader and ultraviolet light transilluminator were introduced. Moreover, PCR amplification has also been incorporated into this method to improve sensitivity. The specificity and sensitivity of this method were determined following the preparation of the recombinant Cas12a protein and optimization of the CRISPR/Cas12a-based trans-cleavage system.

Results: The method demonstrated no cross-reactivity with ten kinds of viruses of swine. The minimum template concentration required to activate substantial trans-cleavage activity was determined to be 106 copies/µL of SVA templates. However, when PCR amplification was incorporated, the method achieved a detection limit of one copy of SVA templates per reaction. It also exhibited 100% accuracy in simulated sample testing. The complete testing process does not exceed three hours.

Conclusions: Importantly, this method utilizes standard laboratory equipment, making it accessible for use in resource-limited settings and facilitating widespread and ultra-sensitive screening during epidemics. Overall, the development of this method not only broadens the array of tools available for detecting SVA but also holds significant promise for controlling the spread of PIVD.

Keywords: CRISPR/Cas12a; PIVD; Rapid diagnosis; Senecavirus A; Ultra-sensitivity.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Schematic and target sites of crRNAs. (A) Overview of the CRISPR/Cas12a-based SVA fluorescent detection system. (B) Identification of 7 target sites of crRNAs within the SVA 3D gene
Fig. 2
Fig. 2
Optimization of the CRISPR/Cas12a-based SVA fluorescent detection system. (A) Screening of the most effective crRNAs. (B) Determination of the optimal Cas12a to crRNA ratio. (C) Determination of the optimal Cas12a concentration. (D) Identification of the optimal substrate (FAM-BHQ2 ssDNA reporter) concentration. (E) Optimization of the incubation temperature for Cas12a trans-cleavage activity. (F) Determination of the minimum template copies required for significant trans-cleavage activity. Nuclease-free water was used as a negative control (NC). 109 copies/sample of SVA templates (pUC57-SVA-3D) was used to perform trans-cleavage system optimization. Bar graph data represent the mean ± standard deviation (SD) of three experimental replicates (****, p < 0.0001)
Fig. 3
Fig. 3
Specificity and sensitivity of the CRISPR-powered SVA detection method. (A) and (C): specificity of CRISPR-powered SVA detection method targeting 11 common swine viruses using MR or UV sensor system, respectively. (B) and (D): limit of detection of CRISPR-powered SVA detection method for gradient dilution of SVA templates (pUC57-SVA-3D) after PCR amplification. An aliquot containing nuclease-free water was used as a negative control (NC). Bar graph data represent the mean ± standard deviation (SD) of three experimental replicates (****, p < 0.0001)
Fig. 4
Fig. 4
Detection performance of testing methods for 48 simulated samples. (A) Detection performance of the CRISPR-based SVA detection method using the MR sensor system. (B) Comparison of diagnostic results using the CRISPR-powered and qPCR-based SVA detection methods, with green indicating negative and red indicating positive results. (C) Detection performance of the CRISPR-based SVA detection method using the UV sensor system. An aliquot containing PCR products of SVA template or nuclease-free water was analyzed as positive (P) or negative (N), respectively

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