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J Am Chem Soc. 2019 Mar 6;141(9):3817-3821. doi: 10.1021/jacs.9b00007. Epub 2019 Feb 22.

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

Liu C1,2, Zhao J1,2, Tian F1, Chang J1, Zhang W1,2, Sun J1,2.

Author information

1
CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience , National Center for Nanoscience and Technology , Beijing 100190 , China.
2
University of Chinese Academy of Sciences , Beijing 100049 , China.

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-DNA- and 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.

PMID:
30789261
DOI:
10.1021/jacs.9b00007

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