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Exosomes and EVs Characterization

Extracellular vesicles (EVs) are cell-derived membranous vesicles secreted by cells into the extracellular space, which play a role in cell-to-cell communication. EVs are categorized into 3 groups depending on their size, surface marker, and method of release from the host cell. Recently, EVs have become of interest in the study of multiple disease etiologies and are believed to be potential biomarkers for many diseases. Multiple different methods have been developed to isolate EVs from different samples such as cell culture medium, serum, blood, and urine. Once isolated, EVs can be characterized by technology such as nanotracking analysis, dynamic light scattering, and nano flow cytometry.

Samples

Biomolecules

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Instruments

Malvern Panalytical Expert Light Scattering Zetasizer Advance range
The world’s most widely-used systems for nanoparticle, colloid and biomolecular particle sizing and particle charge measurements

Malvern Panalytical NanoSight Range
The Malvern NanoSight range of instruments provides an easy-to-use, reproducible platform for nanoparticle characterization.

NanoFCM Flow Nanoanalyzer
High sensitivity flow cytometry for nanoparticle analysis. The only real flow product in the world with the ability to analyze single nanoparticles.

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Isolated samples of EVs also often contain a mixture of contaminants consisting of small organelles, lipids, cholesterol, and other undesired microparticles. It is essential to verify the purity of isolated EV samples in order to validate the accuracy of the experimental results derived from the processing of the samples. It is possible that contamination of isolated EVs may lead to abnormal or misleading data, therefore, checking the sample purity is a crucial step in properly analyzing EVs.

Additionally, characterizing the category of EV (Exo, MV, or AB) may be important for the analysis and interpretation of results from EVs. A reason for this is because some compositions (RNA or protein) may exist more in certain categories of EVs than others. For example, it has been previously reported that serum exosomes contain a very small amount of miRNAs per Exo, and therefore are unlikely to possess a biological purpose. Exosomes are much smaller (30–150 nm) and formed by endosomal origin, whereas MVs are much larger (100–1000 nm) and formed by the outward budding of the lipid membrane. Due to this distinction in the quantity of contents, MVs may play a greater role in communicating cell injury and could be a more valuable prospect for future studies.

Another important characteristic of EVs that should be analyzed is the integrity of the isolated microparticle. In order for EVs to have a future potential use particularly in the development of drug delivery, it is critical that EVs maintain their integrity and efficacy after multiple cycles of being frozen and thawed in order to have the ability to be developed into a pharmaceutical product for the future. Isolated EVs from different cells, which preserve both their integrity and effectiveness after many freeze-thaw cycles, are good candidates to be used for drug delivery in the future.

Additionally, EVs can be characterized to determine the cell type from which the EV originated based on the detection of EV surface antigens that are identical to the surface antigens found on its cell of origin. This information is useful for study as we can then determine based on the cell type of origin which tissue type the EV originated from, and therefore which organ is under stress. By backtracking the EV to their site of origin, in the future we can further examine and understand the etiology of diseases, specifically the role of EVs in communicating stress leading to systemic inflammation spreading to organs around the body.

Moreover, the characterization of EVs also allows us to determine the number of EVs released by count. A specific total count of EVs released by cells under stress lets us determine if there is an induction of EVs released to communicate the injury to nearby cells or tissues. This data, along with information about the contents within each EV (RNAs or proteins) may provide further insight into the role EVs play in the communication of cell damage.

Applications

Dynamic Light Scattering (DLS)

DLS measures the size of particles based on their Brownian motion in solution; the basis of Brownian motion is that lighter particles will diffuse faster, and that speed is relative to particle size. This method is used specifically to measure the size distribution of EVs and their zeta potential as well. This technique illuminates particles using a laser; the light scattering by the particles and intensity changes are detected, then further analyzed to determine particle size and distribution within solution. Dynamic light scattering can measure particles smaller than 10 nm or larger than a micron and provides an intensity-based distribution of EVs. DLS provides an average value of relatively uniformly sized particles, and therefore would not be the best technique for a heterogeneous solution of EVs. DLS is able to measure the diameter range of analyzed EVs (1 nm-6 μm) but provides no biochemical data or report about the cell from which the EV originated. Notably, DLS is also much less accurate for heterogeneous mixtures of EVs and provides the most precise data when testing isolated samples of Exos, MVs, or ABs.

 

Nanoparticle Tracking Analysis (NTA)

 Similar to DLS, NTA measures EV concentration and size distribution on the basis of Brownian motion as described before. In NTA, a laser beam is directed into a solution, and the Stokes-Einstein equation is used to measure the mean velocity of the particles, which can then be used to calculate the size of the particles. One major issue with this method is that NTA cannot distinguish an EV from a different particle, meaning any particle that displays similar Brownian motion to EVs will be included in the analysis using NTA. Notable features of NTA are that the particle-by-particle measurement can provide a number-based distribution, NTA can give the percentage of EVs by a number of particles, and NTA often offers a higher resolution than other characterization techniques. Overall, NTA can be used to characterize the size, count, and distribution of EVs ranging from 1 to 1000 nm. Of note, NTA does have reported difficulty in the characterization of heterogeneous samples of EVs and is most suitable for samples of isolated Exos and MVs. NTA is unable to detect and characterize isolated samples of ABs due to its particle size constraint.

 

Nano Flow Cytometry 

Flow cytometric analyses of bead-bound EVs allow for the analysis of specific EV populations of interest using antibodies that precisely recognize EVs from heterogeneous samples. However, this method cannot evaluate the complex profiles of subsets of EVs with multiple labels assessed for each EV. Therefore, a high-resolution flow cytometry method for analyzing and sorting individual EVs and other nanoscale particles is required to improve the single EV analysis. Nano Flow Cytometry combines measurements from high sensitivity multiparametric scattered light and fluorescence to analyze and sort EVs individually. One of the obvious advantages is that Nano Flow Cytometry can separate and distinguish the nano-sized particles from instrument noise and background. Similar to both DLS and NTA, Nano Flow Cytometry is able to provide data on the size, count, and distribution of EVs provided in the sample used. Moreover, this method can also use specific fluorescently labeled antibodies to stain EV surface proteins, and therefore determine the cell type the EV originated from. This notable tool can be extremely valuable for the study of activation markers on both Exos and MVs. With this useful information, researchers can gain insight into EV populations originating from a particular cell type, which may be involved in different disease etiologies. Another noteworthy feature of Nano Flow Cytometry, which distinguishes it from standard flow cytometry, is its ability to differentiate actual EVs from other nanoparticles, contaminants, or artifacts that may have become part of the sample during processing.

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