Confirming size-exclusion chromatography as a clinically relevant extracellular vesicles separation method from 1mL plasma through a comprehensive comparison of methods

Author:

Robinson Stephen DavidORCID,Samuels MarkORCID,Jones WilliamORCID,Stewart NicolasORCID,Eravci MuratORCID,Mazarakis Nektarios KORCID,Gilbert DuncanORCID,Critchley GilesORCID,Giamas GeorgiosORCID

Abstract

Abstract Background Extracellular vesicles (EVs) are amongst the most promising candidates for developing blood-based biomarkers. However, patient sample availability is a key barrier to translational research whilst most biobanks store samples of 1.5mL volume or less. To date, there is no consensus on the most suitable method of EV separation and current techniques frequently require large volumes of biofluids, complicated technology, technical expertise, or significant operating costs, which prevents their widespread adoption by less EV-focussed laboratories. Therefore, there is a need for an easy and reproducible method that separates representative EVs from clinically relevant 1mL volumes of plasma prior to subsequent biomarker identification. Methods In this study, EVs were separated from a clinically relevant 1mL volume of human plasma using four different separation techniques: size exclusion chromatography (SEC), differential ultracentrifugation, precipitation, and immunoaffinity magnetic bead capture. The EVs were characterised using several orthogonal techniques (protein quantification, nanoparticle tracking analysis, transmission electron microscopy, Western blot, single particle interferometric reflectance imaging sensing, and mass spectrometry-based proteomics) to comprehensively compare the separated samples. Results We provide examples of anticipated results highlighting that SEC-processed samples have greater protein quantification yield, greater particle yield of the expected size for EVs, and sufficient EV purity, which facilitates effective EV cargo assessment by proteomics. Moreover, we confirm significant overlap with known EV-related proteins within the Vesiclepedia database. Additionally, using single particle interferometric reflectance imaging sensing (Leprechaun®), we identify that SEC has the most representative surface tetraspanin distribution of the separated EV population compared to unprocessed plasma. Discussion Given that SEC requires minimal expertise, no complicated technology and can separate EVs within 90 min, this comparison reinforces SEC as a clinically relevant EV separation method from 1mL of plasma making it suitable for widespread implementation.

Funder

University Hospitals Sussex NHS Foundation Trust Medical Doctoral Fellowship

Publisher

Springer Science and Business Media LLC

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