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Updated: Sep 28, 2025

Two-Step Reverse Transcription Droplet Digital PCR Protocols for SARS-CoV-2 Detection and Quantification
Published on: March 31, 2021
One-Step RT-qPCR for Viral RNA Detection Using Digital Analysis
Hyuna Park1, Wonjong Jung2, Hyeongseok Jang2
1Department of Environmental Engineering, College of Engineering, Ajou University, Suwon-si, South Korea.
A new thermolysis method enables rapid virus detection without RNA extraction. This technique, integrated with one-chip digital PCR, allows for faster, large-scale viral analysis to combat infections.
Area of Science:
- Virology
- Molecular Biology
- Biotechnology
Background:
- Rapid virus detection is crucial for preventing widespread infections.
- Current methods like RT-qPCR are time-consuming due to separate RNA extraction and cDNA synthesis steps.
- This limitation hinders rapid diagnosis and large-scale analysis needed for effective viral containment.
Purpose of the Study:
- To develop a simple and rapid thermolysis method for virus detection.
- To eliminate the need for viral RNA extraction and purification.
- To integrate this method with digital PCR for streamlined analysis.
Main Methods:
- A novel thermolysis protocol was developed to directly process viral samples.
- The protocol was integrated into a one-chip digital PCR (OCdPCR) system enabling thermolysis, RT, and digital PCR in a single unit.
- Optimization was performed using tobacco mosaic virus, followed by analysis of cucumber mosaic virus.
Main Results:
- Optimized thermolysis conditions were identified as 85°C for 5 minutes with a template concentration of 0.01 μg/nL.
- The integrated OCdPCR system successfully performed thermolysis, RT, and digital PCR in a single 30-minute reaction.
- The method achieved a quantification of 1,130.2 copies/µL for viral particles.
Conclusions:
- The developed thermolysis method significantly reduces the time required for viral RNA analysis.
- Integration with OCdPCR offers a streamlined workflow for rapid and precise viral quantification.
- This approach holds promise for future large-scale viral surveillance and diagnostics.
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