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Single Extracellular Vesicle Imaging and Computational Analysis Identifies Inherent Architectural Heterogeneity.

Authors :
Kapoor KS
Kong S
Sugimoto H
Guo W
Boominathan V
Chen YL
Biswal SL
Terlier T
McAndrews KM
Kalluri R
Source :
ACS nano [ACS Nano] 2024 May 07; Vol. 18 (18), pp. 11717-11731. Date of Electronic Publication: 2024 Apr 23.
Publication Year :
2024

Abstract

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.

Details

Language :
English
ISSN :
1936-086X
Volume :
18
Issue :
18
Database :
MEDLINE
Journal :
ACS nano
Publication Type :
Academic Journal
Accession number :
38651873
Full Text :
https://doi.org/10.1021/acsnano.3c12556