Fluorescence microscopy can provide valuable information about cell interior dynamics. Particularly, mean squared displacement (MSD) analysis is widely used to characterize proteins and sub-cellular structures' mobility providing the laws of molecular diffusion. The MSD curve is traditionally extracted from individual trajectories recorded by single-particle tracking-based techniques. More recently, image correlation methods like iMSD have been shown capable of providing averaged dynamic information directly from images, without the need for isolation and localization of individual particles. iMSD is a powerful technique that has been successfully applied to many different biological problems, over a wide spatial and temporal scales. The aim of this work is to review and compare these two well-established methodologies and their performance in different situations, to give an insight on how to make the most out of their unique characteristics. We show the analysis of the same datasets by the two methods. Regardless of the experimental differences in the input data for MSD or iMSD analysis, our results show that the two approaches can address equivalent questions for free diffusing systems. We focused on studying a range of diffusion coefficients between D = 0.001μm2s-1and D = 0.1μm2s-1, where we verified that the equivalence is maintained even for the case of isolated particles. This opens new opportunities for studying intracellular dynamics using equipment commonly available in any biophysical laboratory.
Keywords: fluorescence; mean squared displacement; optical microscopy.
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