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Updated: May 12, 2025

Techniques for the Analysis of Extracellular Vesicles Using Flow Cytometry
Published on: March 17, 2015
A New Strategy to Modify Glass for Capture and Detection of Small Extracellular Vesicles
Cao Hoang Long Ngo1, Su Su Thae Hnit1, Amin Hassanzadeh-Barforoushi1
1School of Natural Sciences, Macquarie University, Macquarie Park, New South Wales 2109, Australia.
Abstract:
Small extracellular vesicles (sEVs) are nanoscale lipid bilayer vesicles secreted from all types of cells to the extracellular environment. They inherit membrane proteins from their parent cells, making them one of the key biomaterials or biomarkers for disease diagnosis. Microfluidics is emerging as a promising platform for sEV capture, with many methods relying on the modification to a glass substrate for efficient capture. In this study, we propose a new, one-step surface modification method, using silane─poly(ethylene glycol) (PEG) - 1,2-distearoyl-sn-glycero-3-phosphoethanolamine (DSPE), named as silane-PEG-DSPE, to capture sEVs on glass. In this design, silane group attaches to hydroxylated glass surface via covalent bond between Si-(OEt)3 and hydroxyl (OH) group. DSPE then binds to sEVs with distearyl chains firmly anchoring to the vesicle lipid membrane. We determined the optimal conditions for silane-PEG-DSPE modification and tested the efficiency of silane-PEG-DSPE in capturing sEVs by fluorescent imaging. Additionally, surface-enhanced Raman scattering (SERS) demonstrated that the EpCAM-positive sEVs were presented on the glass surface. This suggests that the platform is applicable for sEV detection using various methods, including fluorescent imaging and SERS. Furthermore, we have demonstrated that SERS can detect sEVs from breast cancer (BC) patient plasma with high specificity and sensitivity (as low as 1.6 × 107 particles/mL). Additionally, our analysis reveals a significantly higher expression of EpCAM in BC-derived sEVs compared with those obtained from healthy individuals. Thus, we postulate that the proposed method will find broad applications in the future, particularly as an effective tool in cancer diagnosis.

