PDF(Pubmed)
Abstract：
Extracellular vesicles (EVs) in biofluids are highly heterogeneous entities in terms of their origins and physicochemical properties. Considering the application of EVs in diagnostic and therapeutic fields, it is of extreme importance to establish differentiating methods by which focused EV subclasses are operationally defined. Several differentiation protocols have been proposed; however, they have mainly focused on smaller types of EVs, and the heterogeneous nature of large EVs has not yet been fully explored. In this report, to classify large EVs into subgroups based on their physicochemical properties, we have developed a protocol, named EV differentiation by sedimentation patterns (ESP), in which entities in the crude large EV fraction are first moved through a density gradient of iodixanol with small centrifugation forces, and then the migration patterns of molecules through the gradients are analysed using a non-hierarchical data clustering algorithm. Based on this method, proteins in the large EV fractions of oral fluids clustered into three groups: proteins shared with small EV cargos and enriched in immuno-related proteins (Group 1), proteins involved in energy metabolism and protein synthesis (Group 2), and proteins required for vesicle trafficking (Group 3). These observations indicate that the physiochemical properties of EVs, which are defined through low-speed gradient centrifugation, are well associated with their functions within cells. This protocol enables the detailed subclassification of EV populations that are difficult to differentiate using conventional separation methods.
摘要：
生物流体中的细胞外囊泡(EV)在其起源和物理化学性质方面是高度异质的实体。考虑到电动汽车在诊断和治疗领域的应用，建立区分方法是非常重要的，通过该方法可以在操作上定义集中的EV子类。已经提出了几种区分方案；然而，他们主要关注小型电动汽车，大型电动汽车的异质性尚未得到充分探索。在这份报告中,为了根据大型电动汽车的物理化学特性将其分为亚组，我们开发了一个协议，通过沉积模式(ESP)命名为EV分异，其中粗大EV馏分中的实体首先以小的离心力通过碘克沙醇的密度梯度移动，然后使用非分层数据聚类算法分析分子通过梯度的迁移模式。基于这种方法，口腔液中的大EV部分中的蛋白质分为三组：与小EV货物共享并富含免疫相关蛋白质（第1组），参与能量代谢和蛋白质合成的蛋白质（第2组），和囊泡运输所需的蛋白质（第3组）。这些观察结果表明，电动汽车的理化特性，通过低速梯度离心定义，与它们在细胞内的功能密切相关。该方案能够对使用常规分离方法难以区分的EV群体进行详细的子分类。
