Classification of diffusion dynamics from particle trajectories

Measuring confined diffusion, Brownian motion and active transport is central in cell biology since they represent the main modes of mobility of molecules in living cells. In quantitative microscopy, there are multiple techniques that allow molecule mobility analysis. Single Particle Tracking (SPT) is attractive since it can reveal individual dynamics, close to molecular resolution. However, robust statistical procedures to classify individual trajectories are lacking. Consequently, we have especially developed TOTH to process individual trajectories provided by particle tracking algorithms and 2D+t and 3D+t images acquired with standard microscopy methods such as wide-field or confocal microscopy or with super-resolution microscopy such as spt-PALM. In our framework, we assume that the motions of particles follow a certain class of random process: the diffusion processes. We have proposed a statistical method able to classify the motion of the observed trajectories into three groups: “confined”, “directed” and “free diffusion” (namely Brownian motion). THOTH is an alternative to the commonly used Mean Square Displacement (MSD) analysis. We assessed our procedure on both simulations and real cases; an example of confined diffusion is the Ornstein-Uhlenbeck process while an example of directed diffusion is the Brownian motion with constant drift. The method is currently applied to investigate membrane trafficking (Rab11/Langerin and Rab11/TfR protein sequences) using the following procedure: 1. Tracking of particles with any competitive algorithm. 2. Statistical test /classification applied on tracks longer than ten time points. 3. Estimation of diffusion parameters (e.g. drift, diffusion, ...). Each trajectory is labeled with the most likely process and the parameters of the underlying process are estimated. Future work will concern the detection of change of motion dynamic over time.