In Vivo Identification of Apoptotic and Extracellular Vesicle-Bound Live Cells Using Image-Based Deep Learning

MCML Authors

Fabian Theis

Prof. Dr.

Principal Investigator

Mathematical Modelling of Biological Systems

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+ cells were not apoptotic, but rather live cells associated with PS+ extracellular vesicles (EVs). During acute viral infection apoptotic cells increased slightly, while up to 30% of lymphocytes were decorated with PS+ 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.

article

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Journal of Extracellular Vesicles

9.1. Jul. 2020.

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Authors

J. Kranich • N.-K. Chlis • L. Rausch • A. Latha • M. Schifferer • T. Kurz • A. F.-A. Kia • M. Simons • F. J. Theis • T. Brocker

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Links

DOI

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Research Area

 C2 | Biology