The authors utilized ultrasensitive single-molecule array (Simoa) assays to quantify three key EV transmembrane proteins-CD9, CD63, and CD81- while measuring albumin levels as a marker of free protein contamination. By applying this approach to plasma and cerebrospinal fluid (CSF), they systematically compared commonly used isolation methods, including ultracentrifugation, precipitation, and size exclusion chromatography (SEC). The results highlight SEC as a superior method for maintaining both yield and purity, particularly when optimized with custom column parameters. This study provides a valuable, reproducible strategy for improving EV isolation, aiding biomarker discovery and translational research in EV-based diagnostics.

The researchers developed a digital ELISA assay targeting ApoB-100, a key lipoprotein marker, and integrated it with existing assays for albumin and EV-associated tetraspanins. They systematically evaluated various size exclusion chromatography (SEC) resins and developed a novel approach, Tri-Mode Chromatography (TMC), to enhance EV purity while maintaining yield. The study highlights the advantages of TMC in reducing co-isolated contaminants and improving the reliability of EV-based biomarker discovery, particularly for proteomics applications.

Given the difficulty of distinguishing EV-associated proteins from free plasma proteins, the researchers developed a method combining optimized size-exclusion chromatography (SEC) for EV isolation with a protease protection assay and ultrasensitive digital ELISA (Simoa) measurements. Their analysis revealed that only a small fraction of total plasma α-synuclein is contained within EVs, but its phosphorylated form (pSer129), a marker of PD pathology, is enriched within EVs compared to free plasma protein. Applying this method to patient samples, they observed subtle but significant differences in EV α-synuclein and pSer129 levels between PD, Lewy body dementia (LBD), and control groups. This work establishes a robust framework for studying EV-contained neurodegenerative biomarkers and highlights the potential of EV-based diagnostics for neurodegenerative diseases.

Researchers developed a framework that integrates gene expression data with EV proteomics to identify transmembrane proteins unique to neurons. They optimized high-purity EV isolation by combining multiple purification techniques, including size exclusion chromatography (SEC), density gradient centrifugation (DGC), and Mixed Mode Resin (MMR) Slurry, to effectively remove free proteins and lipoprotein contaminants while preserving EV integrity. Through proteomic analysis, they identified NRXN3 as a robust neuron-specific EV marker and validated its presence using ultrasensitive immunoassays. By optimizing immuno-isolation protocols, the study provides a foundation for isolating neuron-derived EVs, enabling their use in biomarker discovery for neurological diseases. This methodology offers a scalable strategy for isolating cell type-specific EVs, expanding potential applications in liquid biopsy and neurodegenerative disease diagnostics.