Robust and well-established techniques for the quantification and characterization of extracellular vesicles (EVs) are a crucial need for the utilization of EVs as potential diagnostic and therapeutic tools. Current bulk analysis techniques such as proteomics and Western blot suffer from low resolution in the detection of small changes in target marker expression levels, exemplified by the heterogeneity of EVs. Microscopy-based techniques can provide valuable information from individual EVs; however, they are time-consuming and statistically less powerful than other techniques. Flow cytometry has been successfully employed for the quantification and characterization of individual EVs within larger populations. However, traditional flow cytometry is not highly suited for the examination of smaller, submicron particles. Here we demonstrate the accurate and precise quantification of nanoparticles such as EVs using the Virus Counter 3100 (VC3100) platform, a fluorescence-based technique that uses the principles of flow cytometry with critical enhancements to enable the effective detection of smaller particles. This approach can detect nanoparticles precisely with no evidence of inaccurate concentration measurement from masking effects associated with traditional nanoparticle tracking analysis (NTA). Fluorescently labeled EVs from different sources were successfully quantified using the VC3100 without a postlabeling washing step. Moreover, protein profiling and characterization of individual EVs were achieved and have been shown to determine the expression level of target protein markers.

用于细胞外囊泡 (EV) 的量化和表征的稳健且成熟的技术是利用 EV 作为潜在诊断和治疗工具的关键需求。当前的批量分析技术，如蛋白质组学和蛋白质印迹，在检测目标标记表达水平的微小变化方面存在分辨率低的问题，例如 EV 的异质性。基于显微镜的技术可以从单个 EV 中提供有价值的信息；然而，与其他技术相比，它们耗时且在统计上不那么强大。流式细胞术已成功用于对较大人群中的单个 EV 进行量化和表征。然而，传统的流式细胞术不太适合检测较小的亚微米颗粒。在这里，我们展示了使用 Virus Counter 3100 (VC3100) 平台对 EV 等纳米粒子进行准确和精确的量化，这是一种基于荧光的技术，它使用流式细胞术原理和关键增强功能来有效检测较小的粒子。这种方法可以精确检测纳米粒子，没有证据表明与传统纳米粒子跟踪分析 (NTA) 相关的掩蔽效应导致浓度测量不准确。使用 VC3100 成功量化了来自不同来源的荧光标记 EV，无需标记后清洗步骤。此外，还实现了单个 EV 的蛋白质分析和表征，并已证明可以确定目标蛋白质标记物的表达水平。