In vivo identification of apoptotic and extracellular vesicle-bound live cells using image-based deep learning

Jan Kranich, Nikolaos Kosmas Chlis, Lisa Rausch, Ashretha Latha, Martina Schifferer, Tilman Kurz, Agnieszka Foltyn-Arfa Kia, Mikael Simons, Fabian J. Theis, Thomas Brocker

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

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.

Original languageEnglish
Article number1792683
JournalJournal of Extracellular Vesicles
Volume9
Issue number1
DOIs
StatePublished - 1 Jan 2020

Keywords

  • Extracellular Vesicles
  • apoptosis
  • dendritic cells
  • exosomes
  • irradiation
  • viral Infection

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