λ‑DNA- and Aptamer-Mediated Sorting and Analysis of Extracellular Vesicles

λDNA和适配体介导的细胞外囊泡的分类和分析

主讲人：赵月月

American Chemical Society丨Published:2019 Feb 22丨 Issue Date: 2019 Mar 6 丨 Pages: 141(9):3817-3821 丨DOI:https://doi.org/10.1021/jacs.9b00007

Abstract：

Extracellular vesicles (EVs) are heavily implicated in diverse pathological processes. Due to their small size, distinct biogenesis, and heterogeneous marker expression, isolation and detection of single EV subpopulations are difficult. Here, we develop a λ-DNAand aptamer-mediated approach allowing for simultaneous size-selective separation and surface protein analysis of individual EVs. Using a machine learning algorithm to EV signature based on their size and marker expression, we demonstrate that the isolated microvesicles are more efficient than exosomes and apoptotic bodies in discriminating breast cell lines and Stage II breast cancer patients with varied immunohistochemical expression of HER2. Our method provides an important tool to assess the EV heterogeneity at the single EV level with potential value in clinical diagnostics.

摘要：

细胞外囊泡(EV)与多种病理过程密切相关。由于其体积小、独特的生物发生和异质标记表达，单一EV亚群的分离和检测是困难的。在这里，我们开发了一种λ-DNA和适配体介导的方法，允许同时对单个EV进行大小选择分离和表面蛋白分析。利用机器学习算法对基于EV大小和标记表达的EV特征，我们证明了分离的微囊泡在鉴别乳腺细胞系和不同免疫组化表达HER2的II期乳腺癌患者方面比外泌体和凋亡小体更有效。我们的方法为评估单一EV水平的EV异质性提供了一个重要的工具，在临床诊断中具有潜在的价值。