Automated single-molecule imaging in living cells.

Area of Science:

• Biophysics
• Cell Biology
• Pharmacology

Background:

• Single-molecule imaging is crucial for understanding cellular dynamics.
• Current methods can be labor-intensive and lack automation.
• Live-cell analysis requires high throughput and accuracy.

Purpose of the Study:

• To develop and validate an automated single-molecule imaging system for live-cell analysis.
• To apply the system for studying epidermal growth factor receptor (EGFR) dynamics.
• To demonstrate the system's utility in drug screening and cell signaling research.

Main Methods:

• Development of an AI-assisted microscopy system for automated cell searching, focusing, image acquisition, and single-molecule tracking.
• High-throughput single-molecule imaging and analysis of EGFR in 1600 cells within a 96-well plate.
• Measurement of EGFR lateral mobility, diffusion coefficient, oligomer size, and EC50 in response to ligands and drugs.

Main Results:

• Fully automated workflow for single-molecule imaging and tracking in living cells.
• Successful application to analyze EGFR dynamics in numerous cells, revealing changes in lateral mobility.
• Quantification of key dynamic and pharmacological parameters, including diffusion coefficients and EC50 values.

Conclusions:

• Automated single-molecule imaging is feasible for systematic cell signaling analysis.
• The developed system enables efficient and reproducible live-cell studies.
• This technology significantly contributes to biological research, drug screening, and pharmacological studies.