Dynamic bidirectional diffusion-controlled multi-enzyme system for one-pot viral detection

计算机科学 算法 实时计算 信号处理 计算生物学 钥匙(锁) 信噪比(成像) 生物系统 噪音(视频) 探测理论
作者
Jing Zhang,Xuening Shi,Yukun Ding,Jingying Zheng,Hang Li,Hongran Zhao,Tong Zhang,Qiuyu Xing,Chao Zhao,Shuo Yao,Juan Wang
出处
期刊:Journal of Advanced Research [Elsevier BV]
标识
DOI:10.1016/j.jare.2026.07.019
摘要

INTRODUCTION: Integrating isothermal amplification with CRISPR-based detection in a single reaction vessel holds significant promise for rapid and sensitive point-of-care virus diagnostics. However, conventional one-pot methods often suffer from mutual inhibition between amplification and CRISPR-Cas reactions, which compromises detection performance and limits their practical application. OBJECTIVES: This study aims to overcome the inhibitory interactions between isothermal amplification and CRISPR-based detection by developing an integrated reaction system that enables efficient multi-enzyme coordination within a single tube. METHODS: We designed a dynamic bidirectional diffusion-controlled RPA/CRISPR-Cas12a multi-enzyme system based on a dual-phase separation strategy. In this system, glycerol was used to modulate viscosity and accelerate the RPA reaction, while sucrose was introduced to create a density gradient that enables spatial separation. This configuration effectively coordinates the activities of multiple enzymes within one reaction vessel. Furthermore, a 3D-printed nucleic acid extraction device was integrated to simplify sample preparation and enhance overall detection efficiency. RESULTS: The developed system achieved single-copy sensitivity and completed detection within 30 min, exhibiting over 100-fold higher sensitivity than conventional one-pot assays. The method was further validated by detecting Norovirus in both clinical and food samples, confirming its robustness and accuracy. CONCLUSION: The proposed dual-phase RPA/CRISPR-Cas12a system provides a simple, rapid, and highly sensitive platform for nucleic acid detection. Its operational simplicity, compatibility with low-resource settings, and potential for home-based diagnostics highlight its strong applicability for decentralized virus detection.
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