DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Area of Science:

• Molecular Biology
• Biotechnology
• Virology

Background:

• DNA viruses pose significant public health threats.
• Rapid and sensitive detection methods are crucial for timely diagnosis and control.
• Existing methods often require specialized equipment and trained personnel, limiting point-of-care applications.

Purpose of the Study:

• To develop a fast, sensitive, and sequence-specific DNA virus detection system for point-of-care (POC) use.
• To integrate recombinase polymerase amplification (RPA) with the CRISPR/Cas12a system for enhanced detection capabilities.
• To incorporate smartphone microscopy and artificial intelligence (AI) for automated analysis and classification.

Main Methods:

• Utilized recombinase polymerase amplification (RPA) for target DNA amplification.
• Employed the CRISPR/Cas12a system for sequence-specific recognition and collateral cleavage of a DNA reporter.
• Integrated portable smartphone microscopy (SPM) for fluorescent imaging and deep learning models for AI-assisted classification.

Main Results:

• Achieved trace detection of DNA viruses with a limit of detection (LoD) as low as 10 aM for Frog virus 3 (FV3).
• The entire detection process, including amplification and analysis, was completed within 40 minutes.
• Demonstrated high accuracy in binary classification of positive and negative samples using AI-assisted analysis.
• The system proved effective without the need for skilled operators or bulky laboratory instruments.

Conclusions:

• The developed RPA-CRISPR/Cas12a-SPM system offers a portable, sensitive, and rapid solution for DNA virus detection at the point-of-care.
• The integration of AI enhances diagnostic accuracy and accessibility.
• This technology holds significant potential for preventing the spread of DNA viruses in diverse settings.