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Effect of Sample Preprocessing and Size-Based Extraction Methods on the Physical and Molecular Profiles of Extracellular Vesicles. | LitMetric

AI Article Synopsis

Article Abstract

Extracellular vesicles (EVs) are nanometric lipid vesicles that shuttle cargo between cells. Their analysis could shed light on health and disease conditions, but EVs must first be preserved, extracted, and often preconcentrated. Here we first compare plasma preservation agents, and second, using both plasma and cell supernatant, four EV extraction methods, including (i) ultracentrifugation (UC), (ii) size-exclusion chromatography (SEC), (iii) centrifugal filtration (LoDF), and (iv) accousto-sorting (AcS). We benchmarked them by characterizing the integrity, size distribution, concentration, purity, and expression profiles for nine proteins of EVs, as well as the overall throughput, time-to-result, and cost. We found that the difference between ethylenediaminetetraacetic acid (EDTA) and citrate anticoagulants varies with the extraction method. In our hands, ultracentrifugation produced a high yield of EVs with low contamination; SEC is low-cost, fast, and easy to implement, but the purity of EVs is lower; LoDF and AcS are both compatible with process automation, small volume requirement, and rapid processing times. When using plasma, LoDF was susceptible to clogging and sample contamination, while AcS featured high purity but a lower yield of extraction. Analysis of protein profiles suggests that the extraction methods extract different subpopulations of EVs. Our study highlights the strengths and weaknesses of sample preprocessing methods, and the variability in concentration, purity, and EV expression profiles of the extracted EVs. Preanalytical parameters such as collection or preprocessing protocols must be considered as part of the entire process in order to address EV diversity and their use as clinically actionable indicators.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10964911PMC
http://dx.doi.org/10.1021/acssensors.3c02070DOI Listing

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