High throughput Surface Epitope Immunoaffinity Isolation of Extracellular Vesicles and Downstream Analysis

Abstract

Extracellular vesicles (EVs), including exosomes, have significant potential for diagnostic and therapeutic applications. The lack of standardized methods for efficient and high throughput isolation and analysis of EVs, however, has limited their widespread use in clinical practice. Surface epitope immunoaffinity (SEI) isolation utilises affinity ligands, including antibodies, aptamers, or lectins, that target specific surface proteins present on EVs. Paramagnetic bead-SEI isolation represents a fit-for-purpose solution for the reproducible, high throughput isolation of EVs from biofluids and downstream analysis of RNA, protein and lipid biomarkers that is compatible with clinical laboratory workflows. This study evaluates a new surface epitope immunoaffinity isolation method for enriching subpopulations of EVs. EVs were isolated from human plasma using a bead-based SEI method designed for on-bead and downstream analysis of EV-associated RNA and protein biomarkers. Western blot analysis confirmed the presence of EV markers in the captured nanoparticles. Mass spectrometry analysis of the SEI lysate identified over 1500 proteins, with the top 100 including known EV-associated proteins. miRNA sequencing followed by RT-qPCR analysis identified EV-associated miRNA transcripts. Using SEI, EVs were isolated using automated high throughput particle moving instruments, demonstrating equal or higher protein and miRNA yield and recovery compared to manual processing. SEI is a rapid, efficient, and high throughput method for isolating enriched populations of EVs; effectively reducing contamination and enabling the isolation of a specific subpopulation of EVs. In this study, high throughput EV isolation and RNA extraction have been successfully implemented. This technology holds great promise for advancing the field of EV research and facilitating their application for biomarker discovery and clinical research.