A computational approach for detecting micro-domains and confinement domains in cells: a simulation study

• Published in: Physical biology Vol. 17; no. 2; p. 025002
• Main Authors: Briane, Vincent, Salomon, Antoine, Vimond, Myriam, Kervrann, Charles
• Format: Journal Article
• Language: English
• Published: England IOP Publishing 12.02.2020
• Subjects: classification and clustering; diffusion; fluorescence microscopy; molecule trajectory
• ISSN: 1478-3975; 1478-3975
• DOI: 10.1088/1478-3975/ab5e1d

In this paper, we aim to detect trapping areas (equivalently microdomains or confinement areas) within cells, corresponding to regions where molecules are trapped and thereby undergo subdiffusion. We propose an original computational approach that takes as input a set of molecule trajectories estimated by appropriate tracking methods. The core of the algorithm is based on a combination of clustering algorithms with trajectory classification procedures able to distinguish subdiffusion, superdiffusion and Brownian motion. The idea is to automatically identify trapping areas where we observe a high concentration of subdiffusive particles. We evaluate our proof of concept on artificial sequences obtained with a biophysics-based simulator (Fluosim), and we illustrate its potential on real TIRF microscopy data.