Effect of sample preprocessing and extraction methods on the physical and molecular profiles of extracellular vesicles

bioRxiv (Cold Spring Harbor Laboratory)(2023)

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摘要
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 pre-concentrated. Here we firstly compare plasma preservation agents, and secondly, 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 integrity, size-distribution, concentration, purity and the expression profiles for nine proteins of EVs, as well as overall throughput, time-to-result and cost. We found that the difference between EDTA and citrate anticoagulants vary 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, the LoDF was susceptible to clogging and sample contamination, while the AcS featured high purity but a lower yield of extraction. Analysis of protein profiles suggest that extraction methods extract different sub-population of EVs. Our study highlights the strength and weakness of sample preprocessing methods, and the variability in concentration, purity, and EV expression profiles of the extracted EVs. Pre-analytical parameters such as collection or pre-processing protocols must be considered as part of the entire process in order to address EV diversity and their use as clinically actionable indicators. ### Competing Interest Statement The authors have declared no competing interest.
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关键词
extracellular vesicles,extraction methods,molecular profiles,sample preprocessing
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