Deep-Learning-Assisted Single-Molecule Tracking on a Live Cell Membrane

Single-molecule
fluorescence imaging is a powerful tool to study
protein function by tracking molecular position and distribution,
but the precise and rapid identification of dynamic molecules remains
challenging due to the heterogeneous distribution and interaction
of proteins on the live cell membrane. We now develop a deep-learning
(DL)-assisted single-molecule imaging method that can precisely distinguish
the monomer and complex for rapid and real-time tracking of protein
interaction. This DL-based model, which comprises convolutional layers,
max pooling layers, and fully connected layers, is trained to reach
an accuracy of >98% for identifying monomer and complex. We use
this
method to investigate the dynamic process of chemokine receptor CXCR4
on the live cell membrane during the early signaling stage. The results
show that, upon ligand activation, the CXCR4 undergoes a dynamic process
of forming a receptor complex. We further demonstrate that the CXCR4
complex tends to be internalized at 2.5-fold higher rate into the
cell interior than the monomer via the clathrin-dependent pathway.
This study is the first example to scrutinize the early signaling
process of CXCR4 at the single-molecule level on the live cell membrane.
We envision that this DL-assisted imaging method would be a broadly
useful technique to study more protein families for elucidating their
physiological and pathological functions.