Liu Junyuan, Qu Yuxin, Wang Han
Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China.
Micromachines (Basel). 2021 Dec 9;12(12):1534. doi: 10.3390/mi12121534.
Methods for the isolation and analysis of extracellular vesicles (EVs) have been extensively explored in the field of life science and in clinical diagnosis in recent years. The separation and efficient recovery of high-purity target EVs from biological samples are important prerequisites in the study of EVs. So far, commonly used methods of EV separation include ultracentrifugation, filtration, solvent precipitation and immunoaffinity capturing. However, these methods suffer from long processing time, EV damage and low enrichment efficiency. The use of acoustophoretic force facilitates the non-contact label-free manipulation of cells based on their size and compressibility but lacks specificity. Additionally, the acoustophoretic force exerted on sub-micron substances is normally weak and insufficient for separation. Here we present a novel immuno-acoustic sorting technology, where biological substances such as EVs, viruses, and biomolecules, can be specifically captured by antibody/receptor coated microparticles through immunoaffinity, and manipulated by an acoustophoretic force exerted on the microparticles. Using immuno-acoustic sorting technology, we successfully separated and purified HER2-positive EVs for further downstream analysis. This method holds great potential in isolating and purifying specific targets such as disease-related EVs from biological fluids and opens new possibilities for the EV-based early diagnosis and prognosis of diseases.
近年来，细胞外囊泡（EVs）的分离和分析方法在生命科学领域和临床诊断中得到了广泛探索。从生物样品中分离并高效回收高纯度目标EVs是EVs研究的重要前提。到目前为止，常用的EVs分离方法包括超速离心、过滤、溶剂沉淀和免疫亲和捕获。然而，这些方法存在处理时间长、EVs受损和富集效率低等问题。声泳力的应用有助于基于细胞大小和可压缩性对细胞进行非接触式无标记操作，但缺乏特异性。此外，施加在亚微米物质上的声泳力通常较弱，不足以用于分离。在此，我们提出了一种新型免疫声分选技术，其中诸如EVs、病毒和生物分子等生物物质可以通过免疫亲和作用被抗体/受体包被的微粒特异性捕获，并通过施加在微粒上的声泳力进行操控。利用免疫声分选技术，我们成功分离并纯化了HER2阳性EVs用于进一步的下游分析。该方法在从生物流体中分离和纯化诸如疾病相关EVs等特定目标方面具有巨大潜力，并为基于EVs的疾病早期诊断和预后开辟了新的可能性。
