A patch-based method for repetitive and transient event detection in fluorescence imaging.

Area of Science:

• Cellular and Molecular Imaging
• Biophysics
• Computational Biology

Background:

• Advanced light microscopy generates large datasets crucial for understanding cellular dynamics.
• Automatic detection of molecular events is essential for deciphering complex cellular architectures.
• Quantifying transient molecular behaviors in living cells remains a challenge.

Purpose of the Study:

• To develop and validate a calibrated method for automatic detection and quantification of sudden, transient molecular events in fluorescence microscopy.
• To distinguish appearing/vanishing fluorescent spots from other cellular movements.
• To analyze the method's performance on both synthetic and real biological image data.

Main Methods:

• A calibrated method comparing image patches to identify sudden fluorescent spot appearance/disappearance.
• Analysis of two statistical control procedures for event detection.
• Comparison with a frame difference approach using synthetic image sequences.
• Validation using real image sequences of Langerin-YFP in membrane trafficking.

Main Results:

• The proposed method effectively distinguishes transient events from lateral movements.
• Performance was evaluated on synthetic data and validated on real microscopy data (Wide Field and TIRF).
• The method successfully detected transient local fluorescence concentrations in membrane trafficking models.
• The approach was applied to statistically explore perturbation effects on transient event rates.

Conclusions:

• The calibrated method provides an efficient and accurate approach for detecting transient molecular events in living cells.
• This technique aids in the statistical analysis of cellular dynamics and the impact of perturbations.
• The findings contribute to a deeper understanding of molecular behavior and coordination within the living cell.