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基于非接触电导检测的PCR液滴检测芯片的研究

Study on PCR Droplet Detection Chip Based on Contactless Conductivity Detection
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摘要 数字PCR是继实时定量PCR之后新兴发展起来的一种绝对定量分析技术,广泛应用于疾病早期检测诊断和微生物检测分析等领域。然而,在数字PCR的微反应器检测环节,常规的光学检测方法需要复杂的光学设备,应用环境有限,成本高。因此研究了一种基于非接触电导检测的PCR液滴检测芯片,用电导检测取代传统的光学检测,有效降低了数字PCR结果读出系统的成本。通过优化电极结构与排布,采用三电极平行3D电极结构,减小了相对误差,提高了灵敏度,实现了无标记的PCR反应液滴阴性阳性比例检测。在DNA模板浓度为0.5×10^4~3×10^4 copies/μL内实现了良好的相关性(r^2=0.998),检测通量可达100个/秒。 Digital PCR is a newly developed absolute quantitative analysis technique after real-time quantitative PCR,which is widely used in early detection and diagnosis of diseases and microbial detection.However,in the detection of digital PCR microreactors,conventional optical detection methods require complex optical equipments while the application environment is restricted and the cost is high.Therefore,a kind of PCR droplet detection chip based on contactless conductivity detection was developed by replacing the traditional optical detection with conductivity detection,which could effectively reduce the cost of the digital PCR result readout system.By optimizing the electrode structure and arrangement,a 3D electrode structure composed of three parallel electrodes is adopted to reduce the relative error and improve the sensitivity,and the detection on ratio of negative to positive PCR reaction droplets is achieved.The detecting throughput of the chip reaches up to 100 pcs per second,with a good relativity(r^2=0.998)in the DNA template concentration range of 0.5×10^4-3×10^4 copies/μL.
作者 廖承悦 彭伙 高则航 齐同 周洪波 赵建龙 LIAO Cheng-yue;PENG Huo;GAO Ze-hang;QI Tong;ZHOU Hong-bo;ZHAO Jian-long(State Key Laboratory of Transducer Technology,Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Science,Shanghai200050,China;University of Chinese Academy of Sciences,Beijing100049,China;ShanghaiTech University,Shanghai201210,China)
出处 《分析测试学报》 CAS CSCD 北大核心 2020年第5期561-568,共8页 Journal of Instrumental Analysis
基金 国家自然科学基金资助项目(61571428)。
关键词 数字PCR 液滴 无标记 非接触电导检测 digital PCR droplets label-free contactless conductivity detection
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