Ha Eunyong, Han Yewon, Kim Minseop, Gerelkhuu Zayakhuu, Kwon Sook Jin, Yoon Tae Hyun
Department of Chemistry, College of Natural Sciences Hanyang University Seoul Republic of Korea.
Research Institute for Convergence of Basic Science Hanyang University Seoul Republic of Korea.
J Extracell Biol. 2025 Jul 22;4(7):e70072. doi: 10.1002/jex2.70072. eCollection 2025 Jul.
Extracellular vesicles (EVs) contain a variety of biomolecules, including DNA, RNA, lipids and proteins. They can interact with target cells to perform various functions, offering potential for therapeutic applications like drug delivery and diagnosis. The growing interest in EVs drives the need for robust methods for EV characterisation. One of the prevalent EV characterisation methods is scatter-based nanoparticle tracking analysis (Sc-NTA). This method measures the size and concentration of particles by tracking the scattered light from individual particles. However, Sc-NTA has limitations in selectivity, as it detects all scattered light and fails to distinguish EVs from other nanoparticles, such as protein aggregates. To overcome this limitation, fluorescence-based NTA (Fl-NTA) is being utilised, where fluorescence tagging is used to selectively detect EVs. In previous studies, lipophilic dyes were employed for membrane labelling, but this resulted in false-positive signals due to the staining of even non-vesicular extracellular particles (NVEPs). Immunolabelling methods using antibodies that specifically bind to EV-specific protein were also introduced; yet challenges with sensitivity and photostability of the organic dyes remained. To address the challenges, we conjugated quantum dots (QDs) to antibodies that specifically bind to EV-specific markers, CD9, CD63 and then immunolabelled the EVs. Labelling conditions were optimised to develop a robust protocol for QD-based immunolabelling. Detection sensitivity was evaluated by comparing QD-based immunolabelling with Alexa dye-based methods. Furthermore, size distribution analysis demonstrated the ability of QDs to detect smaller EV populations. Finally, subpopulations of EVs from various cell lines were profiled. This approach enhances the accurate characterisation of EVs, providing a reliable and reproducible method for EV quality control and improved insights into their heterogeneity.
细胞外囊泡（EVs）包含多种生物分子，包括DNA、RNA、脂质和蛋白质。它们可以与靶细胞相互作用以执行各种功能，为药物递送和诊断等治疗应用提供了潜力。对EVs的兴趣日益增长，推动了对强大的EVs表征方法的需求。基于散射的纳米颗粒跟踪分析（Sc-NTA）是一种普遍的EVs表征方法。该方法通过跟踪单个颗粒的散射光来测量颗粒的大小和浓度。然而，Sc-NTA在选择性方面存在局限性，因为它检测所有散射光，无法将EVs与其他纳米颗粒（如蛋白质聚集体）区分开来。为了克服这一局限性，正在使用基于荧光的NTA（Fl-NTA），其中荧光标记用于选择性检测EVs。在先前的研究中，亲脂性染料用于膜标记，但由于即使是非囊泡细胞外颗粒（NVEP）也被染色，导致出现假阳性信号。还引入了使用与EV特异性蛋白特异性结合的抗体的免疫标记方法；然而，有机染料的灵敏度和光稳定性仍然存在挑战。为了解决这些挑战，我们将量子点（QDs）与与EV特异性标志物CD9、CD63特异性结合的抗体偶联，然后对EVs进行免疫标记。优化标记条件以开发基于QD的免疫标记的稳健方案。通过将基于QD的免疫标记与基于Alexa染料的方法进行比较来评估检测灵敏度。此外，大小分布分析证明了QDs检测较小EV群体的能力。最后，对来自各种细胞系的EVs亚群进行了分析。这种方法增强了对EVs的准确表征，为EV质量控制提供了一种可靠且可重复的方法，并改善了对其异质性的认识。
