A simple and powerful analysis of lateral subdiffusion using single particle tracking

Abstract

In biological membranes many factors such as cytoskeleton, lipid composition, crowding and molecular interactions deviate lateral diffusion from the expected random walks. These factors have different effects on diffusion but act simultaneously so the observed diffusion is a complex mixture of diffusive behaviors (directed, >Brownian, anomalous or confined). Therefore commonly used approaches to quantify diffusion based on averaging of the displacements, such as the mean square displacement, are not adapted to the analysis of this heterogeneity. We introduce a new parameter, the packing coefficient Pc, which gives an estimate of the degree of free movement that a molecule displays in a period of time independently of its global diffusivity. Applying this approach to two different situations (diffusion of a lipid probe and trapping of receptors at synapses), we show that Pc detected and localized temporary changes of diffusive behavior both in time and in space. More importantly, it allowed the detection of periods with very high confinement (~immobility), their frequency and duration, and thus it can be used to calculate the effective k on and k off of scaffolding interactions such those that immobilize receptors at synapses. not peer-reviewed)

FluoSim: simulator of single molecule dynamics for fluorescence live-cell and super-resolution imaging of membrane proteins

“…www.nature.com/scientificreports/ FluoSim reproduced a wide range of experimental results (SPT, FRAP, PAF, FCS, SRI) on the Nrx1β-Nlg1 membrane complex using a unique set of parameters extracted from published in-vitro studies and/or taken from our own measurements 26,27 , thereby giving strong credit to the correlative approach. The program is very fast and robust, and should be applicable to model a wide range of 2D-like dynamic molecular systems experiencing membrane diffusion and transient confinement, for example integrins at focal contacts in fibroblasts 34,35 , cadherins at cell-cell contacts [36][37][38] , neuronal adhesion proteins and neurotransmitter receptors at synapses 24,39,40 , and trapping of membrane molecules by lipid rafts or cytoskeletal interactions [41][42][43] .…”

FluoSim: simulator of single molecule dynamics for fluorescence live-cell and super-resolution imaging of membrane proteins

“…FluoSim reproduced a wide range of experimental results (SPT, FRAP, FCS, SRI) on the Nrx1β-Nlg1 membrane complex using a unique set of parameters extracted from published in-vitro studies and/or taken from our own measurements 24,25 , thereby giving strong credit to the correlative approach. The program is very fast and robust, and should be applicable to model a wide range of 2D-like dynamic molecular systems experiencing membrane diffusion and transient confinement, for example integrins at focal contacts in fibroblasts 31,32 , cadherins at cell-cell contacts [33][34][35] , neuronal adhesion proteins and neurotransmitter receptors at synapses 22,36,37 , and trapping of membrane molecules by lipid raft molecules or cytoskeletal interactions [38][39][40] .…”

A Hidden Markov Model for Detecting Confinement in Single Particle Tracking Trajectories

“…Analysis of SPT data is not straightforward primarily because of the stochastic nature of diffusion. This has led to the development of a range of statistical methods that detect deviations from Brownian motion, such as mean square displacement (MSD) (8)(9)(10)(11)(12)(13), and confinement (14)(15)(16)(17)(18)(19) analyses. A new breed of methods model switching in the movement dynamics between various dynamic states (20)(21)(22)(23)(24), often within a hidden Markov chain framework (25)(26)(27)(28)(29)(30).…”