Sensitive detection of small extracellular vesicles using a gold nanostar-based SERS assay

Abstract

Small extracellular vesicles (sEVs) are lipid bilayer-bound vesicles that carry critical biomarkers for disease detection. However, the inherent heterogeneity and complexity of sEV molecular characteristics pose significant challenges for accurate and comprehensive molecular profiling. Traditional analytical methods, including immunoblotting, enzyme-linked immunosorbent assay (ELISA), and flow cytometry, exhibit several limitations, such as being time-consuming, requiring large sample volumes, and demonstrating relatively low sensitivity. Therefore, there is an urgent need to develop a highly sensitive and specific assay for the reliable detection of sEVs. Surface-enhanced Raman scattering (SERS) assays have emerged as a promising approach for sEV detection, offering advantages including high sensitivity and specificity. In the proposed SERS assay, SERS nanotags – comprising nanoparticles coated with Raman-active molecules and conjugated with antibodies – are employed to label surface-bound molecules on sEVs. This approach facilitates the generation of a high-intensity signal from molecules present in low abundance. Recently, anisotropic nanoparticles, such as star-shaped nanostructures, have garnered interest due to their ability to significantly amplify generated SERS signals for ultra-sensitive biomarker detection. In this study, we explore the application of gold nanostars (AuNSs) as SERS nanotags for the detection of sEVs. In principle, AuNS-based SERS nanotags were used to label the EpCAM protein, which can be found on the surface of cancer cell derived sEVs, and then sEV labelled SERS nanotags were captured by CD9-conjugated magnetic beads to form an immunocomplex, which exhibits a SERS signal. Our results demonstrate that the proposed SERS assay utilizing AuNSs provides high specificity and sensitivity, with a detection limit as low as 2.47 × 10³ particles per μL. Furthermore, the assay was tested with spiked plasma samples (cancer cell-derived sEVs spiked into healthy plasma), showing that its specificity remains unaffected by the presence of plasma. These findings suggest that the SERS assay incorporating AuNSs holds significant promise as an effective and reliable detection method for potential clinical applications.