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Aim: Extracellular vesicles (EVs) have gained significant attention for their diagnostic and therapeutic potential in various diseases, including liver disorders. This study focuses on optimizing the isolation and characterization of small EVs from plasma and serum samples in patients with liver diseases, aiming to advance our understanding and potential clinical applications of EVs. Methods: Blood samples were collected from patients with end-stage liver disease (ESLD) enlisted in the TransplantLines Cohort and Biobank Study, and healthy donors. We employed differential ultracentrifugation (DUC) to evaluate three distinct protocols: a 3-step DUC, a washing step omitted samples without washing (WW), and a contaminant-depleted plasma (CDP) protocol. RNA isolation methodologies were compared, involving the use of TRI-reagent or the commercial AllPrep DNA/RNA kit. Further insights into EV composition were obtained through proteomic analyses, comparing samples subjected to traditional cell lysis (L) with those processed without lysis (NL). Results: We successfully isolated EVs from both plasma and serum samples as confirmed by the presence of specific EV markers, including CD9, CD63, CD81, and tumor susceptibility gene 101 (TSG-101). While some contaminants remained, such as albumin and lipoproteins, the protocol selected to continue EVs analysis was the 3-step protocol. Transmission electron microscopy (TEM) and nanotracking analysis (NTA) further confirmed EVs presence. RNA extraction was achieved using TRI-reagent, but not with the commercial kit highlighting the importance of selecting an appropriate method for RNA isolation. Finally, proteomics analysis showed that lysed samples were significantly more enriched in proteins compared to non-lysed samples, although protein variability was still present in both groups. Conclusions: Optimizing EV isolation techniques is essential for harnessing their potential in liver disease diagnosis and therapy. Further refinement of purification methods, a deep characterization of our cohort and understanding the variability and cargo within EVs will be crucial for future biomarker discovery and therapeutic applications in liver-related diseases.
Martínez-Aguilar et al. (Sun,) studied this question.
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