Accurate and Nonpurified Identification of Extracellular Vesicles Using Dual-Binding Recognition Mode

化学 检出限 肉眼 脱氧核酶 细胞外小泡 纳米技术 生物物理学 吞吐量 小泡 色谱法 计算机科学 生物化学 细胞生物学 材料科学 生物 电信 无线
作者
Wenyu Sun,Yu Wang,Zhixue Zhu,Yeru Wang,Manru Zhang,Long Jiang,Su Liu,Jinghua Yu,Jiadong Huang
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:93 (36): 12383-12390 被引量:26
标识
DOI:10.1021/acs.analchem.1c02259
摘要

Circulating extracellular vesicles (EVs) are promising biomarkers for the early diagnosis and prognosis of cancer in a non-invasive manner. However, the rapid and accurate identification of EVs in complex biological samples is technically challenging, which is attributed to the requirement of extensive sample purification and unsatisfactory detection accuracy due to the disturbance of interfering proteins. Herein, a simultaneous binding of double-positive EV membrane protein-based recognition mode (DRM) is proposed. By the combination of DRM-mediated toehold activation and G-quadruplex DNAZyme-catalyzed etching of Au@Ag nanorods (Au@Ag NRs), we have developed an accurate, non-purified, low-cost, and visual strategy for EV identification. The synchronous binding of double-positive proteins on EV membranes is validated by confocal laser scanning microscopy analysis. This approach exhibits excellent specificity and sensitivity toward EVs ranging from 1.0 × 105 to 1.0 × 109 particles/mL with a detection limit of 6.31 × 104 particles/mL. Moreover, we have successfully realized non-purified EV quantification in complex biological media. In addition, target-initiated catalyzed hairpin assembly (CHA) is integrated with G-quadruplex DNAZyme-catalyzed color variation of Au@Ag NRs; thus, low-background EV detection can be achieved by the naked eye. Furthermore, our strategy is easy to adapt to high-throughput formats by using an automatic microplate reader, which could be expected to meet the requirements for high-throughput detection of clinical samples. With its capacities of rapidness, portability, affordability, high throughput, non-purification, and visual detection, this strategy could provide a practical tool for accurate identification of EVs and early diagnosis of cancer.
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