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

The 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) 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 .

Cdc48-independent proteasomal degradation coincides with a reduced need for ubiquitylation.

Ubiquitin fusion degradation (UFD) substrates are delivered at the proteasome by a handover mechanism involving the ubiquitin-selective chaperone Cdc48 and the ubiquitin shuttle factor Rad23. Here, we show that introduction of a 20 amino acid peptide extension not only rendered degradation independent of Cdc48, in line with the model that this chaperone is involved in early unfolding events of tightly folded substrates, but at the same time relieved the need for efficient polyubiquitylation and the ubiquitin shuttle factor Rad23. Removal of the ubiquitylation sites in the N-terminal UFD signal made the degradation of this substrate strictly dependent on the peptide extension and also on Cdc48 and, importantly the presence of a functional ubiquitylation machinery.