A standardized method to determine the concentration of extracellular vesicles using tunable resistive pulse sensing

R Vogel, FAW Coumans, RG Maltesen… - Journal of …, 2016 - Taylor & Francis
R Vogel, FAW Coumans, RG Maltesen, AN Böing, KE Bonnington, ML Broekman, MF Broom…
Journal of extracellular vesicles, 2016Taylor & Francis
Background Understanding the pathogenic role of extracellular vesicles (EVs) in disease
and their potential diagnostic and therapeutic utility is extremely reliant on in-depth
quantification, measurement and identification of EV sub-populations. Quantification of EVs
has presented several challenges, predominantly due to the small size of vesicles such as
exosomes and the availability of various technologies to measure nanosized particles, each
technology having its own limitations. Materials and Methods A standardized methodology …
Background
Understanding the pathogenic role of extracellular vesicles (EVs) in disease and their potential diagnostic and therapeutic utility is extremely reliant on in-depth quantification, measurement and identification of EV sub-populations. Quantification of EVs has presented several challenges, predominantly due to the small size of vesicles such as exosomes and the availability of various technologies to measure nanosized particles, each technology having its own limitations.
Materials and Methods
A standardized methodology to measure the concentration of extracellular vesicles (EVs) has been developed and tested. The method is based on measuring the EV concentration as a function of a defined size range. Blood plasma EVs are isolated and purified using size exclusion columns (qEV) and consecutively measured with tunable resistive pulse sensing (TRPS). Six independent research groups measured liposome and EV samples with the aim to evaluate the developed methodology. Each group measured identical samples using up to 5 nanopores with 3 repeat measurements per pore. Descriptive statistics and unsupervised multivariate data analysis with principal component analysis (PCA) were used to evaluate reproducibility across the groups and to explore and visualise possible patterns and outliers in EV and liposome data sets.
Results
PCA revealed good reproducibility within and between laboratories, with few minor outlying samples. Measured mean liposome (not filtered with qEV) and EV (filtered with qEV) concentrations had coefficients of variance of 23.9% and 52.5%, respectively. The increased variance of the EV concentration measurements could be attributed to the use of qEVs and the polydisperse nature of EVs.
Conclusion
The results of this study demonstrate the feasibility of this standardized methodology to facilitate comparable and reproducible EV concentration measurements.
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