In vivo identification of apoptotic and extracellular vesicle‐bound live cells using image‐based deep learning. Issue 1 (16th July 2020) - Kranich, Jan
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 .