Methods for the physical characterization and quantification of extracellular vesicles in biological samples.

BACKGROUND: Our body fluids contain a multitude of cell-derived vesicles, secreted by most cell types, commonly referred to as extracellular vesicles. They have attracted considerable attention for their function as intercellular communication vehicles in a broad range of physiological processes and pathological conditions. Extracellular vesicles and especially the smallest type, exosomes, have also generated a lot of excitement in view of their potential as disease biomarkers or as carriers for drug delivery. In this context, state-of-the-art techniques capable of comprehensively characterizing vesicles in biological fluids are urgently needed. SCOPE OF REVIEW: This review presents the arsenal of techniques available for quantification and characterization of physical properties of extracellular vesicles, summarizes their working principles, discusses their advantages and limitations and further illustrates their implementation in extracellular vesicle research. MAJOR CONCLUSIONS: The small size and physicochemical heterogeneity of extracellular vesicles make their physical characterization and quantification an extremely challenging task. Currently, structure, size, buoyant density, optical properties and zeta potential have most commonly been studied. The concentration of vesicles in suspension can be expressed in terms of biomolecular or particle content depending on the method at hand. In addition, common quantification methods may either provide a direct quantitative measurement of vesicle concentration or solely allow for relative comparison between samples. GENERAL SIGNIFICANCE: The combination of complementary methods capable of detecting, characterizing and quantifying extracellular vesicles at a single particle level promises to provide new exciting insights into their modes of action and to reveal the existence of vesicle subpopulations fulfilling key biological tasks.

Dual-Wavelength Surface Plasmon Resonance for Determining the Size and Concentration of Sub-Populations of Extracellular Vesicles.

Accurate concentration determination of subpopulations of extracellular vesicles (EVs), such as exosomes, is of importance both in the context of understanding their fundamental biological role and of potentially using them as disease biomarkers. In principle, this can be achieved by measuring the rate of diffusion-limited mass uptake to a sensor surface modified with a receptor designed to only bind the subpopulation of interest. However, a significant error is introduced if the targeted EV subpopulation has a size, and thus hydrodynamic diffusion coefficient, that differs from the mean size and diffusion coefficient of the whole EV population and/or if the EVs become deformed upon binding to the surface. We here demonstrate a new approach to determine the mean size (or effective film thickness) of bound nanoparticles, in general, and EV subpopulation carrying a marker of interest, in particular. The method is based on operating surface plasmon resonance simultaneously at two wavelengths with different sensing depths and using the ratio of the corresponding responses to extract the particle size on the surface. By estimating in this way the degree of deformation of adsorbed EVs, we markedly improved their bulk concentration determination and showed that EVs carrying the exosomal marker CD63 correspond to not more than around 10% of the EV sample.

A simple model for the resonance shift of localized plasmons due to dielectric particle adhesion.

Ultrasensitive detectors based on localized surface plasmon resonance refractive index sensing are capable of detecting very low numbers of molecules for biochemical analysis. It is well known that the sensitivity of such sensors crucially depends on the spatial distribution of the electromagnetic field around the metal surface. However, the precise connection between local field enhancement and resonance shift is seldom discussed. Using a quasistatic approximation, we developed a model that relates the sensitivity of a nanoplasmonic resonator to the local field in which the analyte is placed. The model, corroborated by finite-difference time-domain simulations, may be used to estimate the magnitude of the shift as a function of the properties of the sensed object - permittivity and volume - and its location on the surface of the resonator. It requires only a computation of the resonant field induced by the metal structure and is therefore suitable for numerical optimization of nanoplasmonic sensors.