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Updated: Aug 9, 2026

Extraction of Extracellular Vesicles from Whole Tissue
Published on: February 7, 2019
Using Functionalized Liposomes to Harvest Extracellular Vesicles of Similar Characteristics in Dermal Interstitial
Tingjun Cheng1, Benson K Kosgei1, Geofrey F Soko1,2
1Jiangzhong Cancer Research Center & Jiangxi Engineering Research Center for Translational Cancer Technology, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi 330004, China.
Abstract:
Extracellular vesicles (EVs) are used by living cells for the purpose of biological information trafficking from parental-to-recipient cells and vice versa. This back-and-forth communication is enabled by two distinct kinds of biomolecules that constitute the cargo of an EV: proteins and nucleic acids. The proteomic-cum-genetic information is mediated by the physiological state of a cell (healthy or otherwise) as much as modulated by the biogenesis pathway of the EV. Therefore, in mirroring the huge diversities of human communications, the proteins and nucleic acids involved in cell communications possess seemingly near limitless diversities, and it is this characteristic that makes EVs so highly heterogeneous. Currently, there is no simple and reliable tool for the selective capture of heterogeneous EVs and the delivery of their undamaged cargo for research in extracellular protein mapping and spatial proteomics studies. Our work is a preliminary attempt to address this issue. We demonstrated our approach by using antibody functionalized liposomes to capture EVs from tumor and healthy cell-lines. To characterize their performance, we presented fluorescence and nanoparticle tracking analysis (NTA) results, TEM images, and Western blotting analysis for EV proteins. We also extracted dermal interstitial fluid (ISF) from healthy individuals and used our functionalized synthetic vesicle (FSV) method to capture EVs from their proteins. We constructed three proteomic sets [EV vs ISF, (FSV+EV) vs ISF, and (FSV+EV) vs EV] from the EV proteins and the free proteins harvested from ISF and compared their differentially expressed proteins (DEPs). The performance of our proposed method is assessed via an analysis of 1095 proteins, together with volcano plots, heatmap, GO annotation, and enriched KEGG pathways and organelle localization results of 213 DEPs.
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