Exploring the dynamics of cell processes through simulations of fluorescence microscopy experiments

Area of Science:

• Cellular dynamics and biophysics
• Fluorescence microscopy techniques
• Computational biology and modeling

Background:

• Fluorescence correlation spectroscopy (FCS) is vital for studying cellular dynamics.
• Analytical models for FCS analysis are limited to simple systems.
• Complex cellular processes often lack theoretical analytical functions for data interpretation.

Purpose of the Study:

• To develop a computational tool for analyzing complex reaction-diffusion dynamics in cellular environments.
• To provide a method for interpreting fluorescence microscopy data beyond simple analytical models.
• To enhance the understanding of cellular organization and molecular interactions.

Main Methods:

• Development of FERNET (Fluorescence Emission Recipes and Numerical routines Toolkit).
• Utilized Monte Carlo simulations integrated with the MCell-Blender platform.
• Incorporated complex geometries, compartmentalization, and defined interspecies reactions with kinetic parameters.

Main Results:

• FERNET enables simulation of various fluorescence correlation spectroscopy (FCS) methods, including single- and multiple-point FCS.
• The toolkit supports photon-counting histogram analysis and raster image correlation spectroscopy.
• Simulations can incorporate realistic cellular geometries and molecular behaviors.

Conclusions:

• FERNET offers a powerful approach for modeling and interpreting complex reaction-diffusion systems in cells.
• The toolkit facilitates prediction and understanding of fluorescence microscopy experiment outputs.
• This method advances the analysis of cellular dynamics in realistic biological contexts.