细胞外小泡
管道(软件)
分割
计算机科学
纳米技术
高分辨率
生物系统
材料科学
人工智能
生物
细胞生物学
遥感
地质学
程序设计语言
作者
Kshipra Kapoor,Seoyun Kong,Hikaru Sugimoto,Wenhua Guo,Vivek Boominathan,Yilin Chen,Sibani Lisa Biswal,Tanguy Terlier,Kathleen M. McAndrews,Raghu Kalluri
出处
期刊:ACS Nano
[American Chemical Society]
日期:2024-04-23
卷期号:18 (18): 11717-11731
被引量:7
标识
DOI:10.1021/acsnano.3c12556
摘要
Evaluating the heterogeneity of extracellular vesicles (EVs) is crucial for unraveling their complex actions and biodistribution. Here, we identify consistent architectural heterogeneity of EVs using cryogenic transmission electron microscopy (cryo-TEM), which has an inherent ability to image biological samples without harsh labeling methods while preserving their native conformation. Imaging EVs isolated using different methodologies from distinct sources, such as cancer cells, normal cells, immortalized cells, and body fluids, we identify a structural atlas of their dominantly consistent shapes. We identify EV architectural attributes by utilizing a segmentation neural network model. In total, 7,576 individual EVs were imaged and quantified by our computational pipeline. Across all 7,576 independent EVs, the average eccentricity was 0.5366 ± 0.2, and the average equivalent diameter was 132.43 ± 67 nm. The architectural heterogeneity was consistent across all sources of EVs, independent of purification techniques, and compromised of single spherical, rod-like or tubular, and double shapes. This study will serve as a reference foundation for high-resolution images of EVs and offer insights into their potential biological impact.
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