Differentiation of large extracellular vesicles in oral fluid: Combined protocol of small force centrifugation and sedimentation pattern analysis.

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.

Specimen-specific drift of densities defines distinct subclasses of extracellular vesicles from human whole saliva.

Extracellular vesicles (EVs) in body fluids constitute heterogenous populations, which mirror their diverse parental cells as well as distinct EV-generation pathways. Various methodologies have been proposed to differentiate EVs in order to deepen the current understanding of EV biology. Equilibrium density-gradient centrifugation has often been used to separate EVs based on their buoyant densities; however, the standard conditions used for the method do not necessarily allow all EVs to move to their equilibrium density positions, which complicates the categorization of EVs. Here, by prolonging ultracentrifugation time to 96 h and fractionating EVs both by floating up or spinning down directions, we allowed 111 EV-associated protein markers from the whole saliva of three healthy volunteers to attain equilibrium. Interestingly, the determined buoyant densities of the markers drifted in a specimen-specific manner, and drift patterns differentiated EVs into at least two subclasses. One class carried classical exosomal markers, such as CD63 and CD81, and the other was characterized by the molecules involved in membrane remodeling or vesicle trafficking. Distinct patterns of density drift may represent the differences in generation pathways of EVs.