Standardized procedure to measure the size distribution of extracellular vesicles together with other particles in biofluids with microfluidic resistive pulse sensing.

Michael Cimorelli,Rienk Nieuwland,Edwin Van Der Pol,Zoltán Varga,Sheereen Majd

doi:10.1371/journal.pone.0249603

Abstract

The particle size distribution (PSD) of extracellular vesicles (EVs) and other submicron particles in biofluids is commonly measured by nanoparticle tracking analysis (NTA) and tunable resistive pulse sensing (TRPS). A new technique for measuring the PSD is microfluidic resistive pulse sensing (MRPS). Because specific guidelines for measuring EVs together with other particles in biofluids with MRPS are lacking, we developed an operating procedure to reproducibly measure the PSD. The PSDs of particles in human plasma, conditioned medium of PC3 prostate cancer cell line (PC3 CM), and human urine were measured with MRPS (nCS1, Spectradyne LLC) to investigate: (i) the optimal diluent that reduces the interfacial tension of the sample while keeping EVs intact, (ii) the lower limit of detection (LoD) of particle size, (iii) the reproducibility of the PSD, (iv) the optimal dilution for measuring the PSD, and (v) the agreement in measured concentration between microfluidic cartridges with overlapping detection ranges. We found that the optimal diluent is 0.1% bovine serum albumin (w/v) in Dulbecco’s phosphate-buffered saline. Based on the shape of the PSD, which is expected to follow a power-law function within the full detection range, we obtained a lower LoD of 75 nm for plasma and PC3 CM and 65 nm for urine. Normalized PSDs are reproducible (R2 > 0.950) at dilutions between 10–100x for plasma, 5–20x for PC3 CM, and 2–4x for urine. Furthermore, sample dilution does not impact the dilution-corrected concentration when the microfluidic cartridges are operated within their specified concentration ranges. PSDs from microfluidic cartridges with overlapping detection ranges agreed well (R2 > 0.936) and when combined the overall PSD spanned 5 orders of magnitude of measured concentration. Based on these findings, we have developed operating guidelines to reproducibly measure the PSD of EVs together with other particles in biofluids with MRPS.

Highlights

Extracellular vesicles (EVs) are membrane-enclosed, cell-derived nanoparticles found in biofluids [1]
The particle size distribution (PSD) of extracellular vesicles (EVs) and other submicron particles in biofluids is commonly measured by nanoparticle tracking analysis (NTA) and tunable resistive pulse sensing (TRPS)
The PSDs of particles in human plasma, conditioned medium of PC3 prostate cancer cell line (PC3 CM), and human urine were measured with microfluidic resistive pulse sensing (MRPS) to investigate: (i) the optimal diluent that reduces the interfacial tension of the sample while keeping EVs intact, (ii) the lower limit of detection (LoD) of particle size, (iii) the reproducibility of the PSD, (iv) the optimal dilution for measuring the PSD, and (v) the agreement in measured concentration between microfluidic cartridges with overlapping detection ranges

Summary

Introduction

Extracellular vesicles (EVs) are membrane-enclosed, cell-derived nanoparticles found in biofluids [1]. The particle size distribution (PSD), which describes the relative number of particles in a range of sizes, of EVs in human blood plasma has only been measured by cryogenic electron microscopy and in part by flow cytometry [1, 16] because other detection techniques, such as non-fluorescence nanoparticle tracking analysis (NTA) and tunable resistive pulse sensing (TRPS), are unable to differentiate EVs from other particles. NTA and TRPS cannot identify EVs, PSDs and particle number concentrations measured with dedicated sizing techniques are essential to EV science, especially to (i) confirm the presence of submicron particles, (ii) estimate the particle number concentration within the detected size range, (iii) understand potential artifacts of other detection techniques, such as swarm detection for flow cytometry [17], (iv) develop reference and test samples, and (v) understand and optimize isolation methods

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