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In vivo identification of apoptotic and extracellular vesicle-bound live cells using image-based deep learning.
- Source :
- Journal of Extracellular Vesicles; Dec2020, Vol. 9 Issue 1, p1-10, 10p
- Publication Year :
- 2020
-
Abstract
- The in vivo detection of dead cells remains a major challenge due to technical hurdles. Here, we present a novel method, where injection of fluorescent milk fat globule-EGF factor 8 protein (MFG-E8) in vivo combined with imaging flow cytometry and deep learning allows the identification of dead cells based on their surface exposure of phosphatidylserine (PS) and other image parameters. A convolutional autoencoder (CAE) was trained on defined pictures and successfully used to identify apoptotic cells in vivo. However, unexpectedly, these analyses also revealed that the great majority of PS<superscript>+</superscript> cells were not apoptotic, but rather live cells associated with PS<superscript>+</superscript> extracellular vesicles (EVs). During acute viral infection apoptotic cells increased slightly, while up to 30% of lymphocytes were decorated with PS<superscript>+</superscript> EVs of antigen-presenting cell (APC) exosomal origin. The combination of recombinant fluorescent MFG-E8 and the CAE-method will greatly facilitate analyses of cell death and EVs in vivo. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20013078
- Volume :
- 9
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Journal of Extracellular Vesicles
- Publication Type :
- Academic Journal
- Accession number :
- 146243345
- Full Text :
- https://doi.org/10.1080/20013078.2020.1792683