Santeri Kankaanpää, Markus Nurmi, Markus Lampimäki, Heidi Leskinen, Anni Nieminen, Anatoliy Samoylenko, Seppo J. Vainio, Sari Mäkinen, Lauri Ahonen, Juha Kangasluoma, Tuukka Petäjä, Sirja Viitala
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We demonstrated a novel size assessment of vesicles using a particle mobility analyzer that matched the sizing using electron microscopy in contrast to commonly utilized nanoparticle tracking analysis. Based on the standards of the International Society for Extracellular Vesicles and the quick checklist of EV-Track.org for EV isolation, we emphasize the need for complete characterization and validation of the isolation protocol with all EV-related work to ensure the accuracy of results and allow further analytics and experiments.</p>","PeriodicalId":73747,"journal":{"name":"Journal of extracellular biology","volume":"3 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jex2.149","citationCount":"0","resultStr":"{\"title\":\"Comparative analysis of the effects of different purification methods on the yield and purity of cow milk extracellular vesicles\",\"authors\":\"Santeri Kankaanpää, Markus Nurmi, Markus Lampimäki, Heidi Leskinen, Anni Nieminen, Anatoliy Samoylenko, Seppo J. 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引用次数: 0
摘要
随着人们对细胞外囊泡 (EV) 的兴趣日益浓厚,细胞外囊泡的分离技术也在迅速发展。然而,常用的方案可能不适合更具挑战性的样品基质,并有可能产生次优结果。了解和评估所用分离程序的隐患,在一定程度上有助于进行 EV 分析。牛奶中的 EVs 因其含量丰富、可大规模获得、跨物种生物利用度高以及可用作药物载体而备受关注。然而,牛奶 EVs 的特征与牛奶中其他成分的特征重叠。这就给单独分离和研究 EVs 带来了困难。分离方法也缺乏共识。在这项研究中,我们展示了从牛奶中分离大量 EVs 的各种基于差速离心的方法之间的差异。样品通过梯度离心和尺寸排阻色谱法(SEC)进一步纯化,并对差异进行分析。质量测量在多个独立平台上进行。使用颗粒分析、电子显微镜和 RNA 分析来全面描述分离样品的特征,并确定 EV 分离方案的局限性和可能的污染源。观察到囊泡浓度与蛋白质的比率以及 RNA 与蛋白质的比率随着样品的纯化而增加,这表明在直接差速离心方案中,囊泡与主要的牛奶蛋白质共同分离。我们展示了使用粒子迁移率分析仪对囊泡进行大小评估的新方法,与常用的纳米粒子跟踪分析法相比,该方法与电子显微镜的大小评估相匹配。根据国际细胞外囊泡协会的标准和 EV-Track.org 的 EV 分离快速清单,我们强调需要对所有 EV 相关工作的分离方案进行完整的表征和验证,以确保结果的准确性,并允许进一步的分析和实验。
Comparative analysis of the effects of different purification methods on the yield and purity of cow milk extracellular vesicles
Isolation of extracellular vesicles (EV) has been developing rapidly in parallel with the interest in EVs. However, commonly utilized protocols may not suit more challenging sample matrixes and could potentially yield suboptimal results. Knowing and assessing the pitfalls of isolation procedure to be used, should be involved to some extent for EV analytics. EVs in cow milk are of great interest due to their abundancy and large-scale availability as well as their cross-species bioavailability and possible use as drug carriers. However, the characteristics of milk EVs overlap with those of other milk components. This makes it difficult to isolate and study EVs individually. There exists also a lack of consensus for isolation methods. In this study, we demonstrated the differences between various differential centrifugation-based approaches for isolation of large quantities of EVs from cow milk. Samples were further purified with gradient centrifugation and size exclusion chromatography (SEC) and differences were analyzed. Quality measurements were conducted on multiple independent platforms. Particle analysis, electron microscopy and RNA analysis were used, to comprehensively characterize the isolated samples and to identify the limitations and possible sources of contamination in the EV isolation protocols. Vesicle concentration to protein ratio and RNA to protein ratios were observed to increase as samples were purified, suggesting co-isolation with major milk proteins in direct differential centrifugation protocols. We demonstrated a novel size assessment of vesicles using a particle mobility analyzer that matched the sizing using electron microscopy in contrast to commonly utilized nanoparticle tracking analysis. Based on the standards of the International Society for Extracellular Vesicles and the quick checklist of EV-Track.org for EV isolation, we emphasize the need for complete characterization and validation of the isolation protocol with all EV-related work to ensure the accuracy of results and allow further analytics and experiments.