Less Lipoproteins, Higher Purity: Why You Should Consider Platelet EVs over Plasma EVs

Introduction

Blood plasma EVs studies are hindered significantly by lipoproteins co-existing with them, forming >99% of blood plasma constituents [2,3]. With similar characteristics to EVs, the abundance of lipoproteins challenges the labeling and detection blood plasma EVs [4]. Contrarily, since the vast majority of plasma EV population is released from platelets, platelet-derived EVs form a superior source for theranostic approaches without contamination issues from lipoprotein populations.

Combining nanoparticle tracking analysis (NTA) and dual angle light scattering, DAISY (Holtra AB) reports not only size and concentration but also single particle refractive index [5]. This allows fast and straightforward differentiation of particle types within a mixture. This makes DAISY a powerful tool to better understand complex nanoparticles, such as blood-derived EVs [6].

In this study, we demonstrate how HansaBioMed platelet EV standards show superior purity to their plasma-derived counterparts and how DAISY overcomes a significant bottleneck in blood EV analysis.

Materials and Methods

All EV samples were provided by HansaBioMed Life Sciences in lyophilized form. HEK293-EVs (Cell Derived EVs, SKU: HBM-HEK293-100/2) were purified by tangential flow filtration (TFF) in followed by size exclusion chromatography (SEC), whereas plasma EVs are purified only with SEC. Platelet derived EVs (SKU: HBM-PET-100/2) were purified using ion exchange chromatography (IEX) and TFF.

EVs were re-suspended in 0.1μm filtered PBS according to HansaBioMed’s instructions. All EV samples were subsequently diluted to an approximate concentration of 1 x 10E+9 particles/ml for DAISY analysis. VLDL (LP1, Sigma-Aldrich) was diluted to 0.5 μg/ml, to a concentration of ~10E+9 particles/ml.

For analysis with DAISY instrument (Holtra AB), 10 μl of dilute sample was injected into the microfluidic chip. A constant flow rate of ~90 μm/second was established and 50 seconds of video was acquired for each sample. Data were acquired and analyzed with HoloViz software (Holtra AB).

Results

The majority of existing analytical methods for determining EV size and concentration are unable to distinguish between EVs and co-purifying contaminants such as lipoproteins. This is due to the overlapping size distribution of small EVs and VLDL (Fig 2.A). Despite their overlapping size distribution, DAISY analysis is able to segregate EVs and VLDL based on the relationship between particle size and refractive index (Fig2.B).

By classifying and quantifying particles based on their size and refractive index, DAISY is able to accurately determine the proportion of EV in a sample (Fig.3). A standard curve was constructed by carrying out DAISY analysis of cell derived EV and VLDL mixed in known proportions (Fig.3A&B). The relationship between the proportion of particles classified as EV (“Proportion EV gate”) and the known proportion of EV in the sample was highly linear across the full range of EV proportions (0 to 100% EV nominal, R2 0.99) (Fig. 3.B). DAISY analysis of plasma-derived and platelet-derived EV showed a marked difference in their respective refractive index distributions (Fig.3C). Applying EV classification and quantitation revealed that whilst the plasma-derived EV sample consisted of approximately 28% true EV particles by number, approximately 96% of the particles in the platelet-derived EV sample were classified as EV (Fig.3D).

Conclusion

By differentiating between EV and lipoprotein subfractions through refractive index information, DAISY analysis confirms that platelet derived EVs offer a high purity alternative to plasma-derived EVs. With such priority, platelet EVs form a suitable reference material for blood EV research.

References

[1] Johnsen, K. B., Gudbergsson, J. M., Andresen, T. L., & Simonsen, J. B. (2019). What is the blood concentration of extracellular vesicles? Implications for the use of extracellular vesicles as blood-borne biomarkers of cancer. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, 1871(1), 109–116. https://doi.org/10.1016/j.bbcan.2018.11.006 ‌

[2] Mladenović, D., Khamari, D., Kittel, Á., Koort, K., Buzás, E. I., & Zarovni, N. (2023). Acidification of blood plasma facilitates the separation and analysis of extracellular vesicles. Journal of Thrombosis and Haemostasis. https://doi.org/10.1016/j.jtha.2023.01.007

[3] Nataša Zarovni, Mladenović, D., Brambilla, D., Panico, F., & Chiari, M. (2025). Stoichiometric constraints for detection of EV‐borne biomarkers in blood. Journal of Extracellular Vesicles, 14(2). https://doi.org/10.1002/jev2.70034 ‌

[4] Mladenović, D., Brealey, J., Peacock, B., Kairi Koort, & Nataša Zarovni. (2025). Quantitative fluorescent nanoparticle tracking analysis and nano‐flow cytometry enable advanced characterization of single extracellular vesicles. Journal of Extracellular Biology, 4(1). https://doi.org/10.1002/jex2.70031

[5] Olsén, E., García Rodríguez, B., Skärberg, F., Parkkila, P., Volpe, G., Höök, F., & Sundås Midtvedt, D. (2024). Dual-Angle Interferometric Scattering Microscopy for Optical Multiparametric Particle Characterization. Nano Letters, 24(6), 1874–1881.

[6] Extracellular Vesicles. (2026). Holtra. https://www.holtra.tech/en/applications/extracellular-vesicles.aspx