DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
May 10th, 2024
We present a protocol that combines recombinase polymerase amplification with a CRISPR/Cas12a system for trace detection of DNA viruses and builds portable smartphone microscopy with an artificial intelligence-assisted classification for point-of-care DNA virus detection.
Our protocol introduces a rapid and highly sensitive detection system for frog virus 3. Significantly, this method enables point of care detection of DNA viruses, playing a crucial role in preventing the occurrence of pandemic diseases. The primary advantage of this technique lies in its integration of RPA with the CRISPR/Cas12a system, complimented by a portable smartphone-based microscope and AI classification.
This integration significantly enhances detection efficiency and accuracy while simultaneously reducing errors attributed to human factors. To begin, add the four key RPA enzymes in the reaction buffer. Then add the pre-designed primers to the mixture.
Vortex the mixture thoroughly. Add one microliter of the target DNA obtained from frog virus 3 to each RPA reaction, and vortex to mix well. Next, pipette seven microliters of 100 millimolar magnesium chloride to initiate the reaction.
Incubate the mixture at 37 degrees Celsius for 30 minutes to complete the assay. Prepare the Lachnospiraceae bacterium CAS12a protein with CRISPR RNA to form functional complexes. Mix the bacterial protein and 10 X CRISPR/Cas12a reaction buffer.
Now add 500 nanomolar single-stranded DNA reporter probe. Add one microliter of RPA reaction product to the CRISPR/Cas12a CRISPR RNA reaction mixture. Incubate the mixture at 37 degrees Celsius for 30 minutes.
Measure the fluorescent signals with a microplate reader. For detection with a smartphone microscope, first, pipette the prepared reaction mixture onto a retreated glass slide. Then cover it with a coverslip before incubation.
Place the slide on the stage of the smartphone microscope, and adjust the focal length and clarity. Capture an image to measure the fluorescent signals. Use ImageJ to measure the mean gray value of each image and the standard deviation of the mean gray value in a concentration group.
Adopt the deep learning model AlexNet 33 for classification. Now use Python to reshape the input images to 224 by 224 by three channels. Finally, use a pre-trained backbone network with ImageNet dataset to extract image features.
The sixth pair of primers provided the maximum amplification efficiency, and were selected. CRISPR RNA-3 proved to be the most efficient for collateral cleavage. The use of a developed detection system with selected RPA primers and CRISPR RNA resulted in significant differences between 10 aM FV3 and control.
The most important point to remember is the specific CAS 12a detection step. The CRISPR RNA of the reaction can be modified or redesigned to target other DNA viruses based on CAS 12a detection. The proposed method can assist in the preliminary assessment of the target virus's quantity.
Based on this, other methods like qPCR can be employed to obtain a more accurate viral load. This technique provides a preliminary attempt towards portable detection of DNA viruses. As for the frog virus 3 used in this protocol, timely detection can prompt effective protective measures, reducing losses in the breeding industry.
Overview
This study presents a rapid and sensitive detection system for frog virus 3, emphasizing the integration of recombinase polymerase amplification (RPA) with the CRISPR/Cas12a system to enable point-of-care detection of DNA viruses. This innovative method aims to enhance detection accuracy and efficiency, which is crucial in preventing potential pandemic outbreaks.
Key Study Components
Research Area
- Molecular biology
- Pathogen detection
- Point-of-care diagnostics
Background
- The significance of rapid viral detection in preventing pandemics.
- Integration of advanced methodologies like RPA and CRISPR technology.
- The role of portable systems in field-ready diagnostic assessments.
Methods Used
- Recombinase polymerase amplification (RPA)
- CRISPR/Cas12a system
- Smartphone-based microscopy with AI-assisted classification
Main Results
- Significant differentiation between 10 aM FV3 and control samples.
- Enhanced detection accuracy through the use of specific primers and CRISPR RNA.
- Potential for adapting the method for other DNA viruses by modifying CRISPR RNA.
Conclusions
- The study demonstrates an efficient portable detection method for DNA viruses.
- This approach is relevant for timely protective measures in the breeding industry, illustrating its importance in biological research and public health.
Frequently Asked Questions
Executive Industry Relevance
Rapid, portable DNA virus detection systems are critical for early intervention and containment in both research and applied biopharma settings. The integration of RPA-CRISPR/Cas12a with smartphone-based microscopy and deep learning enables sensitive, sequence-specific detection at the point of care, reducing reliance on centralized labs. This approach supports accelerated decision-making and risk mitigation across discovery and translational pipelines.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables rapid interrogation of viral DNA targets for mechanistic de-risking.
- Supports functional validation of detection reagents and CRISPR guide RNAs.
- Facilitates early-stage triage of candidate detection systems for portfolio advancement.
Screening & Assay Development
- Provides a standardized, quantitative readout for assay optimization and validation.
- Enables reproducible, scalable detection workflows suitable for high-throughput screening.
- Supports robust comparison of primer and CRISPR RNA efficiency for assay refinement.
Translational & Preclinical Research
- Aligns with translational biomarker strategies by enabling field-deployable viral detection.
- Supports continuity from discovery to preclinical validation through portable, quantitative outputs.
- Reduces biological risk by enabling timely detection and intervention in relevant models.
Pipeline & Workflow Integration
This system bridges early discovery, assay development, and translational research by providing a portable, quantitative detection platform adaptable to multiple DNA viruses.
- Discovery Biology: Supports hypothesis testing and target validation through sequence-specific detection.
- Screening: Delivers reproducible, quantitative fluorescence outputs for assay standardization.
- Analytics: Integrates deep learning-based classification for objective, high-confidence result interpretation.
- Translational Research: Enables rapid, field-ready detection supporting preclinical and biomarker studies.
- Enterprise Reuse: Offers a modular platform adaptable to new viral targets by redesigning CRISPR RNA guides.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in viral detection.
- Operational Value: Enhances standardization, reproducibility, and scalability of detection workflows.
- Strategic Value: Accelerates go/no-go decisions and reduces late-stage biological risk.
- Portfolio Impact: Supports risk-adjusted prioritization and rapid advancement of detection technologies.
Implementation Considerations
- Requires expertise in molecular biology and CRISPR assay design.
- Needs access to portable imaging devices and computational infrastructure for AI analysis.
- Demands cross-team standardization of assay protocols and data interpretation.
- Adaptable to various DNA viruses by modifying CRISPR RNA sequences.
- Dependent on preliminary validation before deployment in diverse field settings.
Biopharma FAQs
Chapters in this video
0:00
Introduction
0:40
Combining Recombinase Polymerase Amplification (RPA) and CRISPR/Cas12a Systems for the Detection of DNA Viruses
1:20
CRISPR/Cas12a Detection With/Without Smartphone Microscopy (SPM)
2:23
Data Augmentation and Transfer Learning
2:58
Results: AI-Detection of DNA Virus Using RPA-CRISPR/Cas12a-SPM
3:26
Conclusion
