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Analysis of Transient Behavior in Complex Trajectories: Application to Secretory Vesicle Dynamics

Sébastien Huet ^*, Erdem Karatekin ^*, Viet Samuel Tran ^*, Isabelle Fanget ^*, Sophie Cribier  and Jean-Pierre Henry ^*

^* Institut de Biologie Physico-Chimique, Centre National de la Recherche Scientifique, UPR 1929, Université Paris 7 Denis Diderot, Paris, F-75005, France; and Université Pierre et Marie Curie-Paris 6, CNRS, UMR 7099, Paris, F-75005 France

Correspondence: Address reprint requests to Jean-Pierre Henry or Erdem Karatekin, Institut de Biologie Physico-Chimique, CNRS UPR 1929, Université Paris 7 Denis Diderot, 13 rue Pierre et Marie Curie, 75005 Paris, France. Tel.: 33-1-58-41-50-13; Fax: 33-1-58-41-50-23; E-mails: jean-pierre.henry{at}ibpc.fr, erdem.karatekin{at}ibpc.fr.

Analysis of trajectories of dynamical biological objects, such as breeding ants or cell organelles, is essential to reveal the interactions they develop with their environments. Many previous works used a global characterization based on parameters calculated for entire trajectories. In cases where transient behavior was detected, this usually concerned only a particular type, such as confinement or directed motion. However, these approaches are not appropriate in situations in which the tracked objects may display many different types of transient motion. We have developed a method to exhaustively analyze different kinds of transient behavior that the tracked objects may exhibit. The method discriminates stalled periods, constrained and directed motions from random dynamics by evaluating the diffusion coefficient, the mean-square displacement curvature, and the trajectory asymmetry along individual trajectories. To detect transient motions of various durations, these parameters are calculated along trajectories using a rolling analysis window whose width is variable. The method was applied to the study of secretory vesicle dynamics in the subplasmalemmal region of human carcinoid BON cells. Analysis of transitions between transient motion periods, combined with plausible assumptions about the origin of each motion type, leads to a model of dynamical subplasmalemmal organization.

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