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Kashkanova, A. D.

Publications and source records attributed to Kashkanova, A. D..

2 recordsLinked to original sources

Interferometric nanoparticle tracking analysis enables label-free discrimination of extracellular vesicles from large lipoproteins

Extracellular vesicles (EVs) are increasingly gaining interest as biomarkers and therapeutics. Accurate sizing and quantification of EVs remain problematic, given their nanometer size range and small scattering cross-sections. This is compounded by the fact that common EV isolation methods result in co-isolation of particles with comparable features. Especially in blood plasma, similarly-sized lipoproteins outnumber EVs to a great extent. Recently, interferometric nanoparticle tracking analysis (iNTA) was introduced as a particle analysis method that enables determining the size and refractive index of nanoparticles with high sensitivity and precision. In this work, we apply iNTA to differentiate between EVs and lipoproteins, and compare its performance to conventional nanoparticle tracking analysis (NTA). We show that iNTA can accurately quantify EVs in artificial EV-lipoprotein mixtures and in plasma-derived EV samples of varying complexity. Conventional NTA could not report on EV numbers, as it was not able to distinguish between EVs and lipoproteins. iNTA has the potential to become a new standard for label-free EV characterization in suspension.

biophysics↗

Precision size and refractive index analysis of weakly scattering nanoparticles in polydispersions.

Characterization of the size and material properties of particles in liquid suspensions is in very high demand, e.g., for the analysis of colloidal samples or of bodily fluids such as urine or blood plasma. However, the existing methods are limited in deciphering the constituents of realistic samples. Here, we introduce iNTA as a new method, which combines interferometric detection of scattering with nanoparticle tracking analysis, to reach an unprecedented sensitivity and precision in determining the size and refractive index distributions of nanoparticles in suspensions. After benchmarking iNTA with samples of colloidal gold, we present its remarkable ability to resolve the constituents of various multi-component and polydisperse samples of known origin. Furthermore, we showcase the method by elucidating the refractive index and size distributions of extracellular vesicles from Leishmania parasites and nanoparticles in human urine. The current performance of iNTA already enables advances in several important applications, but we also discuss possible improvements.

biophysics↗