Studying receptor diffusion by interpreting SPT data with a correlated random walk and a first-passage time algorithm

Abstract

One of the most powerful and commonly used methods for studying molecular diffusion on the cell membrane is Single Particle Tracking (SPT). During an SPT experiment, the trajectory of a membrane-associated biomolecule, labeled with an optical bead or a fluorescent tag, is recorded. This trajectory or SPT data is used to quantify and characterize the motion of the individual particles being studied. In particular, one of the main problems in the analysis of SPT data of membrane receptors is to identify the presence of heterogeneity, which may be attributed to microdomains or receptor clusters. In this work, we apply a correlated random walk (CRW) model and adapt a first-passage time (FPT) algorithm originally developed for the interpretation of animal movement, to study the molecular diffusion of membrane receptors and provide a robust method for determining the presence and size of confined regions of diffusion. This SPT data analysis is used to identify heterogeneity for the lymphocyte receptor LFA-1 by determining the presence and size of receptor clusters.