Regenerable electrochemical biosensor for exosomes detection based on the dual-recognition proximity binding-induced DNA walker

DNA 生物传感器 对偶(语法数字) 微泡 电化学 化学 生物物理学 组合化学 纳米技术 计算生物学 生物化学 材料科学 生物 电极 小RNA 基因 物理化学 艺术 文学类
作者
Yuehua Guo,Shihua Liu,Hui‐Li Yang,Po Wang,Qiumei Feng
出处
期刊:Sensors and Actuators B-chemical [Elsevier BV]
卷期号:349: 130765-130765 被引量:29
标识
DOI:10.1016/j.snb.2021.130765
摘要

Exosomes are secreted in the early stage of cancer at low levels that are difficult to detect due to the complex interferents of the sample matrix. Improved cancer detection requires the development of an accurate, reliable, and reusable method to assay exosomes. Here, a regenerable electrochemical biosensor was developed for exosomes detection based on the dual-recognition proximity binding-induced DNA walker and on-off-on strategy. First, we designed two proximity probes, which composed of a Pb2+-dependent DNAzyme tail sequence and identifying units (cholesterol and aptamer). By integrating two proximity probes with target exosomes, a dual-recognition proximity binding-induced DNA walker was achieved to convert one exosome to abundant intermediate DNA strands. Second, the conformational change of hairpin DNA (H) was observed with the hybridization of intermediate DNA, resulting in the increment of the distance between electroactive tag and electrode surface (“off” state of the sensor). These signal changes allowed the quantitative measurement of exosomes. Exonuclease treatment resulted in the hydrolysis of the intermediate DNA and the original hairpin structure, restoring this sensor to the “on” state. With the accurate identification of dual-recognition, the perfect signal amplification of DNA walker and the satisfactory reproducibility of an on-off-on strategy, quantitative detection of exosomes was realized in a wide range from 5.0 × 104 to 1 × 108 particles/mL, with a detection limit of 1.6 × 104 particles/mL. Overall, this approach illustrated a promising potential for exosomes distinguishment of cancer cells from normal cells, even in the complex sample matrix.
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