Carbon Dot Blinking Fingerprint Uncovers Native Membrane Receptor Organizations via Deep Learning.
Journal:
Analytical chemistry
PMID:
35188385
Abstract
Oligomeric organization of G protein-coupled receptors is proposed to regulate receptor signaling and function, yet rapid and precise identification of the oligomeric status especially for native receptors on a cell membrane remains an outstanding challenge. By using blinking carbon dots (CDs), we now develop a deep learning (DL)-based blinking fingerprint recognition method, named deep-blinking fingerprint recognition (BFR), which allows automatic classification of CD-labeled receptor organizations on a cell membrane. This DL model integrates convolutional layers, long-short-term memory, and fully connected layers to extract time-dependent blinking features of CDs and is trained to a high accuracy (∼95%) for identifying receptor organizations. Using deep blinking fingerprint recognition, we found that CXCR4 mainly exists as 87.3% monomers, 12.4% dimers, and <1% higher-order oligomers on a HeLa cell membrane. We further demonstrate that the heterogeneous organizations can be regulated by various stimuli at different degrees. The receptor-binding ligands, agonist SDF-1α and antagonist AMD3100, can induce the dimerization of CXCR4 to 33.1 and 20.3%, respectively. In addition, cytochalasin D, which inhibits actin polymerization, similarly prompts significant dimerization of CXCR4 to 30.9%. The multi-pathway organization regulation will provide an insight for understanding the oligomerization mechanism of CXCR4 as well as for elucidating their physiological functions.