Department of Mechanical Engineering and Applied Mechanics, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Nano Lett. 2022 Jun 8;22(11):4315-4324. doi: 10.1021/acs.nanolett.2c00274. Epub 2022 May 19.
Extracellular vesicles (EVs) have attracted enormous attention for their diagnostic and therapeutic potential. However, it has proven challenging to achieve the sensitivity to detect individual nanoscale EVs, the specificity to distinguish EV subpopulations, and a sufficient throughput to study EVs among an enormous background. To address this fundamental challenge, we developed a droplet-based optofluidic platform to quantify specific individual EV subpopulations at high throughput. The key innovation of our platform is parallelization of droplet generation, processing, and analysis to achieve a throughput (∼20 million droplets/min) more than 100× greater than typical microfluidics. We demonstrate that the improvement in throughput enables EV quantification at a limit of detection = 9EVs/μL, a >100× improvement over gold standard methods. Additionally, we demonstrate the clinical potential of this system by detecting human EVs in complex media. Building on this work, we expect this technology will allow accurate quantification of rare EV subpopulations for broad biomedical applications.
细胞外囊泡 (EVs) 因其在诊断和治疗方面的潜力而受到广泛关注。然而,要实现对单个纳米级 EV 的检测灵敏度、对 EV 亚群的特异性区分以及对大量背景下 EV 进行研究的足够高通量,这一直是一个挑战。为了解决这一基本挑战,我们开发了一种基于液滴的光电流体平台,以高通量定量特定的单个 EV 亚群。我们平台的关键创新是并行化液滴生成、处理和分析,以实现比典型微流控技术高 100 倍以上的高通量(约 2000 万个液滴/分钟)。我们证明,通过提高通量,该方法能够以检测限 = 9EVs/μL 定量 EV,比金标准方法提高了 100 多倍。此外,我们通过在复杂介质中检测人 EV 来证明该系统的临床潜力。在此基础上,我们预计这项技术将能够实现对稀有 EV 亚群的精确定量,从而广泛应用于生物医学领域。