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Updated: Sep 7, 2026

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
Published on: May 10, 2024
Rapid Point-of-Care Lateral Flow Assay for Differentiation of Capripoxviruses Using RPA-CRISPR-Cas12a
Gundallahalli Bayyappa Manjunatha Reddy1, Vignesh Manivasagam1, Megha V Naragund1
1ICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI) Yelahanka, Bengaluru, Karnataka, India.
Abstract:
The Capripoxviruses (CaPVs) are highly contagious viruses that includes sheeppox virus, goatpox virus, and lumpy skin disease virus infecting sheep, goats, and cattle respectively resulting in significant morbidity and mortality. This study presents a diagnostic tool based on recombinase polymerase amplification (RPA) assisted with CRISPR-Cas12a platform coupled with a lateral flow assay (LFA) that facilitate timely detection and differentiation of Capripox viruses, and support effective surveillance programs. The assay operates through the cleavage of a dual labelled oligonucleotide reporter molecule (Biotin-Fam), generating a detectable signal. The results can be interpreted either using a fluorescence-based detection system or through a lateral flow assay (LFA), where gold nanoparticles conjugated with anti-FAM antibodies enable visual signal detection. Under optimized assay conditions (50nM LbCas12a and 1µM reporter probe with a reaction time of 25min), the CRISPR-Cas12a platform along with RPA (39°C for 20min) substantially enhanced analytical sensitivity, enabling reliable detection of as few as 10 copies/µL of viral DNA. The specificity of the assay was rigorously evaluated using individual targets, mixed-template samples, and 90 clinical specimens, demonstrating complete species-specific discrimination without any detectable cross-reactivity. Collectively, the developed single-gene RPA-CRISPR-Cas12a lateral flow assay (LFA) represents a rapid, highly sensitive, and specific point-of-care diagnostic platform, providing visual readout by the naked eye and offering significant potential for decentralized veterinary diagnostics and field-based disease surveillance.

