Wang Hongcai, Lv Zhongyue, Chen Maosong, Jiang Yiwei, Huang Yinqi, Ren Bingxuan, Ying Xujin, Lin Guanjiang, Xie Guomin, Zheng Wu
Department of Neurosurgery, Ningbo Medical Center Lihuili Hospital, Ningbo University, Ningbo City, Zhejiang Province, 315040, China.
Department of Neurology, Ningbo Medical Center Li Huili Hospital, The Affiliated Li Huili Hospital, Ningbo University, Ningbo City, Zhejiang Province, 315040, China.
Talanta. 2025 May 15;287:127609. doi: 10.1016/j.talanta.2025.127609. Epub 2025 Jan 16.
The considerable abundance and remarkable stability of sEVs provide substantial benefits for diagnosing Alzheimer's disease. Therefore, precise tracking subtypes of small extracellular vesicles (sEVs) is crucial for screening novel diagnostic biomarkers and developing therapeutic technologies. We propose a three-target recognition-mediated proximity ligation assay for the precise identification of sEV subtypes utilizing three specifically designed probes: one for the exosomal surface protein CD63 recognition, one for fixing the biolipid layer, and the third for the identification of distinctive protein associated with a specific subtype of sEVs (L1CAM positive sEVs). The developed sEVs subtype tracing approach integrates proximity ligation of the three probes to specifically bind to surface biomarkers and polymerase chain reaction (PCR) for signal amplification, enabling "AND" logic analysis of three essential components on sEVs. This method can be utilized for both sEVs quantification and subtype tracing. The proposed approach demonstrated a low limit of detection for neuronal sEVs at 2.5 particles/μL, according to this design. In addition, we utilized this technique to measure plasma sEV levels in individuals with Alzheimer's disease and examined its early diagnostic effectiveness. The approach can assess the concentration ratios of neuronal sEVs and cancer-derived sEVs, highlighting its potential for clinical applications. In addition, the approach enables precise tracing and identification of sEVs subtypes, hence facilitating extensive applications in biological science, biomedical engineering, and personalized medicine.
小细胞外囊泡(sEVs)的丰富性和显著稳定性为阿尔茨海默病的诊断带来了诸多益处。因此,精确追踪小细胞外囊泡(sEVs)的亚型对于筛选新型诊断生物标志物和开发治疗技术至关重要。我们提出了一种三靶点识别介导的邻近连接检测法,用于利用三种专门设计的探针精确识别sEV亚型:一种用于识别外泌体表面蛋白CD63,一种用于固定生物脂质层,第三种用于识别与特定sEV亚型(L1CAM阳性sEVs)相关的独特蛋白。所开发的sEV亚型追踪方法将三种探针的邻近连接整合起来,使其特异性结合表面生物标志物,并利用聚合酶链反应(PCR)进行信号放大,从而实现对sEVs上三个关键成分的“与”逻辑分析。该方法可用于sEVs的定量和亚型追踪。根据这一设计,所提出的方法对神经元sEVs的检测下限低至2.5个颗粒/μL。此外,我们利用该技术测量了阿尔茨海默病患者血浆中的sEV水平,并检验了其早期诊断有效性。该方法可以评估神经元sEVs和癌症衍生sEVs的浓度比,凸显了其临床应用潜力。此外,该方法能够精确追踪和识别sEVs亚型,从而便于在生物科学、生物医学工程和个性化医学中广泛应用。