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

Abstract

BackgroundSenecavirus 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.MethodsIn 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.ResultsThe 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.ConclusionsImportantly, 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.