Monte Carlo simulations for the evaluation of oligomerization data in TOCCSL experiments

Area of Science:

• Cellular biology
• Biophysics
• Microscopy techniques

Background:

• Cellular processes rely on protein-protein interactions and oligomerization.
• Accurate detection of protein oligomerization is crucial for understanding cellular function.
• Previous methods faced limitations at high protein densities.

Purpose of the Study:

• To develop a theoretical framework for quantitative interpretation of TOCCSL measurements.
• To identify and analyze factors influencing TOCCSL experimental outcomes.
• To improve the accuracy of detecting protein oligomerization states.

Main Methods:

• Utilized extensive Monte Carlo simulations.
• Analyzed the "thinning out clusters while conserving the stoichiometry of labeling" (TOCCSL) technique.
• Investigated the impact of experimental parameters and system characteristics.

Main Results:

• Identified laser intensity profile and molecular diffusion as sources of partially photobleached oligomers.
• Demonstrated that partially photobleached oligomers are falsely detected as lower-order oligomers.
• Quantified random colocalizations that lead to false detection of higher-order oligomers.

Conclusions:

• The theoretical framework enables quantitative interpretation of TOCCSL data.
• Understanding sources of error is key to accurate protein oligomerization analysis.
• Refined TOCCSL interpretation enhances the study of protein interactions in biological systems.