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

Abstract

Fluorescence correlation spectroscopy (FCS) methods are powerful tools for unveiling the dynamical organization of cells. For simple cases, such as molecules passively moving in a homogeneous media, FCS analysis yields analytical functions that can be fitted to the experimental data to recover the phenomenological rate parameters. Unfortunately, many dynamical processes in cells do not follow these simple models, and in many instances it is not possible to obtain an analytical function through a theoretical analysis of a more complex model. In such cases, experimental analysis can be combined with Monte Carlo simulations to aid in interpretation of the data. In response to this need, we developed a method called FERNET (Fluorescence Emission Recipes and Numerical routines Toolkit) based on Monte Carlo simulations and the MCell-Blender platform, which was designed to treat the reaction-diffusion problem under realistic scenarios. This method enables us to set complex geometries of the simulation space, distribute molecules among different compartments, and define interspecies reactions with selected kinetic constants, diffusion coefficients, and species brightness. We apply this method to simulate single- and multiple-point FCS, photon-counting histogram analysis, raster image correlation spectroscopy, and two-color fluorescence cross-correlation spectroscopy. We believe that this new program could be very useful for predicting and understanding the output of fluorescence microscopy experiments.

Figure 1

(A and B) Schematic representation of the MCell-FERNET workflow (A) and FERNET routine (B).

Figure 2

Simulation of FCS routines. (A and B) Single-point FCS: a simulation of 300 molecules (ε = 10⁵ cpsm) passively moving with D = 40 μm²/s in a cube (side length = 6 μm) was run with t_s = 10 μs during 100 s. The ACF (A) and PCH (B) data calculated from the intensity trace obtained with the FERNET routine were fitted as described in the text (continuous lines), resulting in the parameters detailed in Table 1.

Figure 3

Detecting interactions with two-color FCS. Simulations of two-color FCS experiments were run considering two populations of molecules tagged with spectrally separated fluorescent probes (depicted as red circles and green rectangles). The fluorescence intensity of these molecules was assumed to be collected in independent channels (red and green symbols, respectively). (A–D) The ACFs of the intensity obtained for the red (○) and green (□) channels, and the CCFs (gray symbols) were calculated for the following scenarios: (A) noncompetitive binding, (B) competitive binding, (C) complex formation and binding, and (D) sequential binding. The diffusion and binding model proposed by Michelman-Ribeiro et al. (13) was fitted to the ACF and CCF curves in those scenarios in which the assumptions of the model were fulfilled (continuous lines). The simulated and recovered parameters are summarized in Table S1. To see this figure in color, go online.