(683d) Detection and Profiling of Neurodegenerative Disease-Related Extracellular Vesicles (EVs) Using Surface Plasmon Resonance Biosensors

Neurodegenerative diseases, such as Parkinson’s disease (PD), pose significant challenges to individual health and well-being, requiring immediate attention for effective management and treatment. A key obstacle in addressing these conditions is that their initial pathological changes are always asymptomatic or non-specific, complicating the diagnosis. Therefore, it is important to develop precise detection methods that can identify these diseases early in their progression before significant neurological damage occurs. Recently, circulating extracellular vesicles (EVs) have emerged as promising biomarkers for neurodegenerative diseases. These nano-scale vesicles carry various biomolecules from their parent cells, including proteins, nucleic acids, and lipids, providing valuable insights into disease progression. These biomolecules can be either surface-bound or encapsulated within the EVs. Key surface biomarkers include tetraspanins (e.g., CD81, CD63 and CD9), essential for EV recognition, along with neural adhesion molecules (e.g., NCAM and L1CAM), which play critical roles in the pathophysiology of neurodegenerative diseases. Within EV cargos, misfolded proteins (e.g., alpha-synuclein for PD) and miRNAs (e.g., miR-19b-3p for PD) also show promise as diagnostic markers. Their capacity to circulate and be detected prior to the manifestation of visible symptoms offers significant advantages for early disease detection.

Here, we introduced a rapid and sensitive surface plasmon resonance (SPR)-based platform designed to detect and profile both EV surface and cargo biomarkers. In the proof-of-concept model, a neuroblastoma cell line (SH-SY5Y) was used to generate EVs. We harvested wildtype EVs directly from the supernatant of the cell culture media. To mimic early and late stages of PD, we produced two variants of disease-related EVs by exposing the cell culture media to neurotoxins 1-methyl-4-phenylpyridinium and 6-hydroxydopamine, respectively. The alterations of biomarker profiles were served as indicators of disease progression. We isolated EVs via ultrafiltration and characterized their sizes and concentrations using nanoparticle tracking analysis and atomic force microscopy. Additionally, we used the Pierce 660 assay coupled with Western Blot to quantify total protein content and profile specific protein expression within these EV populations. To detect EVs, we utilized a custom-built SPR instrument equipped with six sensing channels. The sensor surfaces were coated with a low-fouling self-assembled monolayer comprising of oligo-ethylene glycol alkane thiolates terminated with carboxylic and hydroxy groups and then functionalized with antibodies of EV-recognition tetraspanins CD81 and CD9 as well as disease-specific biomarkers NCAM and alpha-synuclein. The intact EV samples were flown over the functionalized surfaces. The results demonstrated the successful capture of EVs via specific receptors and distinct profiling of different EV subtypes, indicating high sensitivity and specificity in discriminating disease-related EVs from wildtype EVs. We further analyzed the lysed EV samples that were pre-treated with a lysis reagent. The sensor surfaces were functionalized with anti-alpha-synuclein antibodies and single-stranded nucleic acids to detect cargo proteins (alpha-synuclein) and miRNAs (miR-19b-3p), respectively. The results showed that combining the EV cargo protein and miRNA profiles with the EV surface biomarkers provides an effective way to detect and profile PD-related EVs. In summary, the SPR-based approach exhibits a promising platform for the development of comprehensive profiling panels aimed at the early diagnosis and monitoring of neurodegenerative diseases, potentially revolutionizing clinical practice and patient care.