4.8 Article

A magnetic b ead-me diate d selective adsorption strategy for extracellular vesicle separation and purification

期刊

ACTA BIOMATERIALIA
卷 124, 期 -, 页码 336-347

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.actbio.2021.02.004

关键词

Extracellular vesicles; Exosomes; Isolation; Cell culture; Plasma; Magnetic beads

资金

  1. National Natural Science Foundation of China [31927803]
  2. Shanghai Municipal Education Commission [ZXWF082101]
  3. Shanghai Jiao Tong University [ZH2018ZDA35]
  4. SJTU-YITU Joint lab

向作者/读者索取更多资源

In this study, a simple and easy-to-operate magnetic bead-mediated selective adsorption strategy (MagExo) was proposed for the isolation of EVs. By utilizing hydrophilic polymers to create an adsorption window between EVs and proteins, EVs were selectively adsorbed on the surface of magnetic beads, allowing for high purity EV isolation through simple magnetic separation. MagExo demonstrated a two times higher yield of harvested EVs compared to ultracentrifugation (UC), with comparable purity, and efficiently enriched EVs for downstream applications such as proteomics analysis. The method also showed significantly higher target RNA amounts compared to traditional methods, making it a reliable and efficient approach for EV isolation.
Extracellular vesicles (EVs) are presently attracting increasing interest among clinical and scientific researchers. Although the downstream applications of EVs are recognized to be greatly affected by the quality of the isolated EVs, almost none of the separation methods can simultaneously achieve high yield and high purity of the isolated EVs; this makes the isolation of EVs an essential challenge in EV research. In the present work, we proposed a simple and easy-to-operate method (MagExo) for the separation and purification of EVs based on the phenomenon that EVs can be selectively adsorbed on the surface of magnetic microspheres in the presence of a hydrophilic polymer. The performance of MagExo was comparable to or even better than that of gold standard methods and commercial kits, with two times higher yield and comparable purity of the harvested EVs to that achieved with ultracentrifugation (UC); this could meet the requirements of various EV-associated downstream applications. In addition, MagExo can be easily automated by commercial liquid workstations, thus significantly improving the isolation throughput and paving a new way in clinical diagnosis and treatment. Extracellular vesicles (EVs) are membrane-encapsulated particles with critical biomedical functions, including mediating intercellular communication, assisting tumor metastasis, and carrying protein and microRNA biomarkers. The downstream applications of EVs are greatly influenced by the quality of the isolated EVs. However, almost none of the separation methods can simultaneously achieve both high yield and high purity of the isolated EVs, thus making the isolation of EVs an essential challenge in EV research. Here, we developed a magnetic bead-mediated selective adsorption strategy (MagExo) for easy-to-operate EV isolation. Benefited from the presence of an adsorption window between EVs and proteins under the effect of a hydrophilic polymer, EVs tend to adsorb on the surface of magnetic beads selectively and can be separated from biological fluids with high purity by simple magnetic separation. The proposed method was used for EV isolation from plasma and cell culture media (CCM), with two times higher yield and comparable purity of the harvested EVs to that obtained by ultracentrifugation (UC). Downstream applications in proteomics analysis showed 86.6% (plasma) and 86.5% (CCM) of the analyzed proteins were matched with the ExoCarta database, which indicates MagExo indeed enriches EVs efficiently. Furthermore, we found the target RNA amount of the isolated EVs by MagExo were almost dozens and hundred times higher than the gold standard DG-UC and ultracentrifugation (UC) methods, respectively. All the results show that MagExo is a reliable, easy, and efficient approach to harvest EVs for a wide variety of downstream applications with minimized sample usage.

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