Particle size distribution of exosomes and microvesicles determined by transmission electron microscopy, flow cytometry, nanoparticle tracking analysis, and resistive pulse sensing - Pol, E.; Coumans, F. A. W.; Grootemaat, A. E.; Gardiner, C.; Sargent, I. L.; Harrison, P.; Sturk, A.; Leeuwen, T. G.; Nieuwland, R. (Journal of thrombosis and haemostasis, 2014)
Summary Background Enumeration of extracellular vesicles has clinical potential as a biomarker for disease. In biological samples, the smallest and largest vesicles typically differ 25‐fold in size, 300 000‐fold in concentration, 20 000‐fold in volume, and 10 000 000‐fold in scattered light. Because of this heterogeneity, the currently employed techniques detect concentrations ranging from 104 to 1012 vesicles mL–1. Objectives To investigate whether the large variation in the detected concentration of vesicles is caused by the minimum detectable vesicle size of five widely used techniques. Methods The size and concentration of vesicles and reference beads were measured with transmission electron microscopy (TEM), a conventional flow cytometer, a flow cytometer dedicated to detecting submicrometer particles, nanoparticle tracking analysis (NTA), and resistive pulse sensing (RPS). Results Each technique gave a different size distribution and a different concentration for the same vesicle sample. Conclusion Differences between the detected vesicle concentrations are primarily caused by differences between the minimum detectable vesicle sizes. The minimum detectable vesicle sizes were 70–90 nm for NTA, 70–100 nm for RPS, 150–190 nm for dedicated flow cytometry, and 270–600 nm for conventional flow cytometry. TEM could detect the smallest vesicles present, albeit after adhesion on a surface. Dedicated flow cytometry was most accurate in determining the size of reference beads, but is expected to be less accurate on vesicles, owing to heterogeneity of the refractive index of vesicles. Nevertheless, dedicated flow cytometry is relatively fast and allows multiplex fluorescence detection, making it most applicable to clinical research.