Improved Label-Free Identification of Individual Exosome-like Vesicles with Au@Ag Nanoparticles as SERS Substrate

Abstract

Exosome-like vesicles (ELVs) are nanovectors released by cells that are endowed with a variety of molecules, including proteins, nucleic acids, and chemicals that reflect the molecular signature of the producing cell. Given their presence in many biofluids, they form an easily accessible biomarker for early disease detection. Previously we demonstrated the possibility of identifying individual ELVs by analyzing their molecular signatures with surface-enhanced Raman scattering (SERS) after functionalization of ELVs with 4-(dimethylamino)­pyridine (DMAP)-stabilized gold nanoparticles (AuNP). Although this strategy was capable of distinguishing ELVs from different cellular origins, the quality of the SERS spectra was suboptimal due to high background coming from the DMAP stabilizing molecules at the AuNP surface. In this study we demonstrate that it is possible to eliminate interfering SERS signals from stabilizing molecules at the AuNP surface by overgrowing in situ the ELV-attached AuNPs with a silver layer so as to form a core–shell nanoparticle (Au@AgNPs) directly at the ELV surface. As such it represents the first known strategy to generate clear SERS spectral fingerprints of delicate biological structures without interference of linker molecules that are needed to ensure colloidal stability of the plasmonic NP and to allow them to associate to the ELV surface. This new strategy using core–shell plasmonic NPs as SERS substrate showed higher near-field enhancements than previous approaches, which resulted in SERS spectra with improved signal-to-noise ratio. This allowed us to discriminate individual vesicles derived from B16F10 melanoma cells and red blood cells (RBC) with an unprecedented sensitivity and specificity >90%. Importantly, thanks to the higher near field enhancement the acquisition time could be reduced by 20-fold in comparison to previously reported strategies, paving the way toward high-throughput label-free single ELV identification.

Towards analyzing the potential of exosomes to deliver microRNA therapeutics

“…Growing experimental evidence proposes that exosomes could be utilized as potential prognostic and diagnostic biomarkers, or engineered as innovative drug delivery systems as they appear to have multiple advantages over conventional delivery systems (Fraire et al, 2019). A lot of strategies have been developed in the context of using exosomes as biomarkers for early disease detection.…”

Superhydrophobic bowl-like SERS substrates patterned from CMOS sensors for extracellular vesicle characterization

“…The Raman spectra exhibit the specific peaks of EVs known to arise from their primary chemical constituents: protein, lipids, and nucleic acids. Specifically, peaks located at 830, 1038 and 1443 cm À1 are attributed to the vibrations from lipids, 17,31,42 the peaks arising at 820, 920 and 1211 cm À1 are coming from proteins, 10,31,43 while the 786 and 852 cm À1 bands originate from nucleic acid and tyrosine ring breathing modes of the DNA/RNA bases. 31,44,45 Using the described SERS substrate, we recorded SERS signals from EVs (Fig.…”

“…[7][8][9] Therefore, it is a reliable label-free method able to provide the spectral data of molecules. 10,11 An innovative approach is to combine the properties of a good SERS platform with the capabilities of a superhydrophobic substrate. A superhydrophobic substrate presents a surface that consists of unique micrometric patterns able to trap tiny air pockets underneath the liquid droplet to induce a large contact angle.…”

Nanoparticle-based biosensors for detection of extracellular vesicles in liquid biopsies

“…205 The same group subsequently improved the system by applying an extra silver layer in situ to remove interfering signals generated by the AuNP coating. 206 The Au@AgNPs core-shell system resulted in SERS signals with improved signal-to-noise ratio, and consequently, more vibrational modes could be identified. Furthermore, the improved system decreased the acquisition time by a factor of 20.…”