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Updated: Jan 14, 2026

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
Published on: May 10, 2024
Zoonotic disease detection at the point-of-care: the best of RPA and CRISPR-Cas
Simão Monteiro Belo Dos Santos1, Charlotte Van Tricht1, Jeroen Lammertyn1
1KU Leuven, Department of Biosystems - Biosensors Group, Willem de Croylaan 42, B-3001, Leuven, Belgium.
Abstract:
Biosensors are increasingly crucial in detecting biomarkers for emerging zoonotic diseases at the point-of-care (POC). This imminence was recently highlighted by the deficient response during the SARS-CoV-2 pandemic. While polymerase chain reaction (PCR) is the common nucleic acid (NA) testing method for zoonotic diseases in laboratory settings, it is impractical for the POC settings due to the equipment-related cost, lack of portability and user-friendliness. Recent advances in NA amplification introduced isothermal methods, such as recombinase polymerase amplification (RPA), which is known for its low temperature (37-42 °C), short incubation time (5-20 min) and suitability for integration in miniaturized, portable, low-cost, highly sensitive diagnostic platforms. However, RPA susceptibility to false positive results steered to its combination with CRISPR-Cas12/13, leading to the rise of SHERLOCK and DETECTR. This review first explores RPA-CRISPR-Cas bioassay development as either two- or one-step. This is followed by a discussion on the integration of canonical RPA, or its combination with CRISPR-Cas, into different diagnostic platforms towards NA amplification at the POC (e.g., mobile laboratories, centrifugal, or pump-free platforms). Finally, the advantages, limitations, and outlook for POC-based diagnostics of zoonotic diseases with RPA(-CRISPR-Cas) are discussed, highlighting the need for innovative technologies to address global health challenges. While promising, many of these approaches still require further research to achieve streamlined, single-step reactions and seamless integration into diagnostic platforms. Moreover, despite two decades of RPA(-CRISPR-Cas) development, technology readiness is limited, still missing validated platforms, integrated sample preparation, and AI-powered results analysis enabling real time epidemiological monitoring.
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