通过将RPA-CRISPR/Cas12a-SPM与深度学习集成来检测青病毒3
Zhengyang Lei1,2, Lijin Lian1,2, Likun Zhang1,2
1Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China.
ACS omega
|September 18, 2023
概括
一个新的青病毒3 (FV3) 护理点检测系统使用复合酶聚合酶放大 (RPA) 和CRISPR/Cas12a技术. 这种快速,灵敏的方法与智能手机显微镜和人工智能相结合,可以实现高精度的DNA病毒检测.
科学领域:
- 分子生物学分子生物学
- 生物技术是生物技术.
- 生物信息学是一种生物信息学.
背景情况:
- 青病毒3 (FV3) 对两动物种群和水生生态系统构成重大威胁.
- 准确和快速的FV3检测方法对于疾病监测和管理至关重要.
- 现有的诊断工具往往需要专门的设备和训练有素的人员,这限制了它们在现场环境中的使用.
研究的目的:
- 为FV3.3开发一个快速,灵敏和护理点 (POC) 检测系统.
- 将复合酶聚合酶放大 (RPA) 与CRISPR/Cas12a技术相结合,以提高检测能力.
- 利用智能手机显微镜和人工智能进行自动化数据分析和分类.
主要方法:
- 联合复合酶聚合酶放大 (RPA) 与CRISPR/Cas12a用于核酸检测.
- 优化了RPA原料和CRISPRRNAs (crRNAs),以实现高灵敏度.
- 实现智能手机显微镜用于视觉读取和深度学习模型进行分类.
- 使用动物样本和不同度的FV3.3验证了该系统.
主要成果:
- 通过使用RPA-CRISPR/Cas12a,达到低至100mA (60.2副本/μL) 的检测极限 (LoD).
- 在40分钟内使用智能手机显微镜证明POC负载值为10 aM.
- 在四个阳性动物样本中成功检测到FV3,定量PCR (qPCR) Cq值在13到32之间.
- 深度学习模型在二进制分类方面达到100%的准确性,在FV3度的多类分类方面达到98.75%的准确性.
结论:
- 开发的RPA-CRISPR/Cas12a系统为FV3检测提供了一个快速,灵敏和无设备的方法.
- 智能手机集成和人工智能辅助分析使得有效的POC诊断成为可能.
- 这项技术在实地监测和管理动物DNA病毒感染方面具有巨大的潜力.
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