Development of Visual Detection of African Swine Fever Virus Using CRISPR/AapCas12b Lateral Flow Strip Based on Viral Major Capsid Protein Gene B646L

African swine fever (ASF), induced by the African swine fever virus (ASFV), is an acute hemorrhagic disease characterized by high fever, systemic hemorrhages, and elevated mortality. Current diagnostic techniques including PCR and ELISA present limitations in field applications due to requirements for specialized equipment and prolonged processing duration. Therefore, rapid and accurate detection of ASFV has become a key link in ASF prevention and control. This study established a rapid and precise visual diagnostic approach by integrating the CRISPR/AapCas12b system with lateral flow strip (LFS) technology, specifically targeting the <i>B646L</i> gene encoding the major capsid protein p72. The CRISPR/AapCas12b-LFS platform achieved a sensitivity threshold of 6 copies/µL for <i>B646L</i> gene detection, completing analysis within an hour. Validation study confirmed exceptional specificity against common porcine pathogens including PRRSV, CSFV, PRV, PPV4, and PCV3. The developed assay demonstrated complete concordance with real-time PCR results when analyzing 34 clinical specimens including three heart samples, three liver samples, three spleen samples, three lung samples, three kidney samples, three lymph node samples, five serum samples, five blood samples, and five oral swab samples for ASFV detection. Overall, this method is sensitive, specific, and practicable onsite for ASFV detection, showing a great application potential for monitoring ASFV in the field.

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Publication Details

Journal
Animals
Published
2025-11-12
DOI
https://doi.org/10.3390/ani15223274
Primary Topic
Animal Disease Management and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

Development of Visual Detection of African Swine Fever Virus Using CRISPR/AapCas12b Lateral Flow Strip Based on Viral Major Capsid Protein Gene B646L

Nanhua Chen, Z. S. Xu, Yu‐Sun Chang, Wanglong Zheng et al.
Animals
Animal Disease Management and Epidemiology
article

Development of Visual Detection of African Swine Fever Virus Using CRISPR/AapCas12b Lateral Flow Strip Based on Viral Major Capsid Protein Gene B646L

Nanhua Chen, Z. S. Xu, Yu‐Sun Chang, Wanglong Zheng, Jianfa Bai, Jianzhong Zhu, Can Lin, Wenyu Hao, Xilong Kang, Wangli Zheng
article en

Abstract

African swine fever (ASF), induced by the African swine fever virus (ASFV), is an acute hemorrhagic disease characterized by high fever, systemic hemorrhages, and elevated mortality. Current diagnostic techniques including PCR and ELISA present limitations in field applications due to requirements for specialized equipment and prolonged processing duration. Therefore, rapid and accurate detection of ASFV has become a key link in ASF prevention and control. This study established a rapid and precise visual diagnostic approach by integrating the CRISPR/AapCas12b system with lateral flow strip (LFS) technology, specifically targeting the <i>B646L</i> gene encoding the major capsid protein p72. The CRISPR/AapCas12b-LFS platform achieved a sensitivity threshold of 6 copies/µL for <i>B646L</i> gene detection, completing analysis within an hour. Validation study confirmed exceptional specificity against common porcine pathogens including PRRSV, CSFV, PRV, PPV4, and PCV3. The developed assay demonstrated complete concordance with real-time PCR results when analyzing 34 clinical specimens including three heart samples, three liver samples, three spleen samples, three lung samples, three kidney samples, three lymph node samples, five serum samples, five blood samples, and five oral swab samples for ASFV detection. Overall, this method is sensitive, specific, and practicable onsite for ASFV detection, showing a great application potential for monitoring ASFV in the field.

AnimalsVol. 15(22)
Kansas State University (US), Yangzhou University (CN)
Priority Academic Program Development of Jiangsu Higher Education Institutions
Openalex Percentile: Top 55%
Animal Disease Management and Epidemiology
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