Exploring the Application of Surface-enhanced Raman Scattering-based Biosensing of Individual sEVs in Disease Diagnosis and Therapeutics

Summary

Here, we present a protocol to analyze individual small extracellular vesicles (sEVs) using label-free surface-enhanced Raman spectroscopy (SERS), enabling minimally invasive disease diagnostics and assessment of sEVs as therapeutic delivery vehicles.

Abstract

This protocol outlines a comprehensive, label-free platform that integrates surface-enhanced Raman spectroscopy (SERS) with machine learning (ML) to detect and molecularly profile individual small extracellular vesicles (sEVs) for diagnostic and therapeutic applications. The method begins with sEV isolation using either size exclusion chromatography or ultracentrifugation. Isolated vesicles are then analyzed on engineered plasmonic gold nanopyramid 2D array substrates capable of single-vesicle sensitivity. By leveraging intrinsic Raman biochemical fingerprints, the protocol enables high-specificity detection without external labels. Following spectral acquisition, data undergo preprocessing and are analyzed using trained machine learning algorithms (e.g., LDA, SVC) to classify disease states, successfully distinguishing gastric cancer from healthy controls using sEVs from tissue, plasma, and saliva with respective classification accuracies of 90.1%, 70.9%, and 60.7%. Additionally, its therapeutic application is shown by quantifying doxorubicin loading in single sEVs, a measurement enhanced by using graphene-coated substrates as an internal standard. This approach allows for high-throughput analysis that captures population heterogeneity essential for early disease detection and understanding drug loading efficiency at the single-vesicle level.

Introduction

Small extracellular vesicles (sEVs), typically ranging from 30 to 200 nm in diameter, are naturally secreted by cells into biological fluids and carry proteins, lipids, and nucleic acids indicative of their cell of origin^1,2,3. As non-invasive biomarkers present in saliva, urine, and other body fluids⁴, they hold promise for early disease diagnosis, prognosis, and therapeutic monitoring, especially in oncology^5,6,7. However, their clinical translation is....

Protocol

The collection of human specimens was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board (IRB) of UCLA. All donors provided written informed consent prior to their participation in the study.

NOTE: A total of 4 cell lines, AGS (CRL-1739), A549 (CCL-185), NCI-N87 (CRL-5822), Hs 738.St/Int (CRL-7869), all purchased from a commercial vendor, were used in this study. These cell lines were cultured and passaged strictly according to the vendor's instructions and reagents. The conditioned media were collected and stored at -20 °C before being processed. At Samsung Medical Cen....

Results

Successful implementation of the single-vesicle SERS protocol yields distinct Raman spectra from individual sEVs, allowing downstream diagnostic classification and therapeutic drug loading monitoring. Figure 1 depicts the workflow of the diagnostic study for gastric cancer and the drug-loaded sEVs monitoring application using our protocol reported here, respectively.

Discussion

A pivotal aspect of this protocol is the substrate preparation and sEV purification. The performance of label-free SERS depends strongly on producing uniform, high conformal plasmonic substrates with strong enhancement "hot spot". Likewise, high-purity sEV isolation via size-exclusion chromatography is essential to render reliable and reproducible SERS spectra. Impurities such as protein aggregates or lipoproteins not only weaken vesicle signal but can confound downstream machine-learning classification .......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
1x PBS	Thermo Fisher Scientific	J61196.AP
300-mesh copper grid	Electron Microscopy Sciences	EMS200-Cu
4% paraformaldehyde solution	Sigma Aldrich	1004960700
4″ Si wafers	MSE Supplies	WA0810	(100) oriented
A549 cell line	ATCC	CCL-185
AGS cell line	ATCC	CRL-1739
Centrifuge Rotor F-35-6-30, 5430	Eppendorf	22654306
CHA Mark 40	CHA Mark 40	https://chaindustries.com/mark-40-system/	e-beam evaporation
Cr etchant solution	Sigma Aldrich	651826-500ML
Doxorubicin D-4000	LC Laboratories	D-4000_3g
ExoView R100 system and ExoView Human Tetraspanin Kit	NanoView Biosciences	https://www.nowmedicalstudios. com/portfolio/nanoview- biosciences-3d-product-illustrations
FeCl3 solution	Sigma Aldrich	451649
HF solution	Sigma Aldrich	695068-500ML
Hs 738.St/Int cell line	ATCC	CRL-7869
inVia confocal Raman microscope	Renishaw	https://www.renishaw.com/en/ invia-confocal-raman-microscope --6260?srsltid=AfmBOoqbZlyW qv2KDdcXV0UZnp8tdLNgYZ0 GbZvGOWI6z1OKi48rg5-b
KOH solution	Sigma Aldrich	417661
MaxQ 4000 Benchtop Incubating/Refrigerating Shakers	Thermo Scientific	SHKA4000 (4320)
MCO-19AIC incubator	SANYO	8380-30-0035
Millex-GP Filter	MilliporeSigma	SLGPM33RS	0.22 µm
NanoSEM 230 microscope	FEI	SEM-FEI-014
Nanosight NS300	Malvern Panalytical	https://www.malvernpanalytical .com/en/support/product-support /nanosight-range/nanosight-ns300
NCI-N87 cell line	ATCC	CRL-5822
Optima TLX Ultracentrifuge	Beckman Coulter	8043-30-1197
Oxford Plasmalab 80 Plus	Oxford Plasmalab	https://plasma.oxinst.com/ products/rie/plasmapro-800-rie
Polystyrene spheres	Alfa Aesar	AA42711AB	500 nm
qEVoriginal/35 nm	Izon	ICO-35
Single-layer graphene	MSE Supplies	ME0408
T-75 flask	VWR	156800
TF20 High-resolution EM	FEI	https://eicn.cnsi.ucla.edu/project/fei-tf20-tem/
uranyl acetate solution	Electron Microscopy Sciences	22400-1