Reverse-engineering of biochemical reaction networks from spatio-temporal correlations of fluorescence fluctuations

Abstract

Recent developments of fluorescence labeling and highly advanced microscopy techniques have enabled observations of activities of biosignaling molecules in living cells. The high spatial and temporal resolutions of these video microscopy experiments allow detection of fluorescence fluctuations at the timescales approaching those of enzymatic reactions. Such fluorescence fluctuation patterns may contain information about the complex reaction–diffusion system driving the dynamics of the labeled molecule. Here, we have developed a method of identifying the reaction–diffusion system of fluorescently labeled signaling molecules in the cell, by combining spatio-temporal correlation function analysis of fluctuating fluorescent patterns, stochastic reaction–diffusion simulations, and an iterative system identification technique using a simulated annealing algorithm. In this report, we discuss the validity and usability of spatio-temporal correlation functions in characterizing the reaction–diffusion dynamics of biomolecules, and demonstrate application of our reaction–diffusion system identification method to a simple conceptual model for small GTPase activation.