Network Tomography-based tracking for intracellular traffic analysis in fluorescence microscopy imaging

International audienceDetermination of the sub-cellular localization and dynamics of any proteins is an important step towards the understanding of multi-molecular complexes in a cellular context. Green Fluorescent Protein (GFP)-tagging and time-lapse fluorescence microscopy allows to acquire multidimensional data on rapid cellular activities, and then make possible the analysis of proteins of interest. Consequently, novel techniques of image analysis are needed to quantify dynamics of biological processes observed in such image sequences. In biological trafficking analysis, the previous tracking methods do not manage when many small and poorly distinguishable objects interact. Nevertheless, an another way of tracking that usually consists in determining the full trajectories of all the objects, can be more relevant. General information about the traffic like the regions of origin and destination of the moving objects represent interesting features for analysis. In this paper, we propose to estimate the paths (regions of origin and destination) used by the objects of interest, and the proportions of moving objects for each path. This can be accomplished by exploiting the recent advances in Network Tomography (NT) commonly used in network communications. This idea is demonstrated on real image sequences for the Rab6 protein, a GTPase involved in the regulation of intracellular membrane trafficking