Quantitative fluorescent nanoparticle tracking analysis and nano‐flow cytometry enable advanced characterization of single extracellular vesicles

荧光团 荧光 亚历山福禄 细胞外小泡 纳米粒子跟踪分析 流式细胞术 表征(材料科学) 纳米技术 人口 化学 分析化学(期刊) 生物系统 材料科学 微泡 色谱法 物理 生物 分子生物学 光学 小RNA 生物化学 细胞生物学 社会学 基因 人口学
作者
Danilo Mladenović,Joseph Brealey,Ben Peacock,Kairi Koort,Nataša Zarovni
出处
期刊:Journal of extracellular biology [Wiley]
卷期号:4 (1): e70031-e70031 被引量:34
标识
DOI:10.1002/jex2.70031
摘要

Current state-of-the-art tools for analysing extracellular vesicles (EVs) offer either highly sensitive but unidimensional bulk measurements of EV components, or high-resolution multiparametric single-particle analyses which lack standardization and appropriate reference materials. This limits the accuracy of the assessment of marker abundance and overall marker distribution amongst individual EVs, and finally, the understanding of true EV heterogeneity. In this study, we aimed to define the standardized operating procedures and reference material for fluorescent characterization of EVs with two commonly used EV analytical platforms-nanoparticle tracking analysis (NTA) and nano-flow cytometry (nFCM). We achieved quantitative fluorescence analyses on ZetaView NTA and NanoAnalyzer nFCM instruments, by utilizing yellow-green FluoSpheres (FS) with assigned ERF (equivalent reference fluorophore) values. This standardization technique allowed for fluorescent EV signal to be expressed in ERF units (indicative of bound fluorescent antibodies per EV), thus enabling measurement of target protein marker abundance on individual EVs, and in the whole EV population. The NTA's and nFCM's limits of detection (LoD) were evaluated at 21 and 9 Alexa Fluor 488 (AF488) molecules, respectively. To complement the limited quantification of markers expressed in a few copies per single EV, in-line bulk fluorescence measurements with a plate reader were performed. This provided absolute marker quantification and more insightful analyses of EV heterogeneity and marker stoichiometry. The standardization method outlined in this work unlocks the full analytical potential of NTA and nFCM, enabling cross-platform data comparison. At the same time, it highlights some of the technical challenges and considerations and thus contributes to the ongoing efforts towards the development of EV analytical tools.
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