Dynamic heterogeneity and non-Gaussian statistics for acetylcholine receptors on live cell membrane

He, Wei; Song, Hao; Su, Yun; Geng, Li; Ackerson, Bruce J.; Peng, H. Benjamin; Tong, Penger

doi:10.1038/ncomms11701

Cited by 173 publications

(200 citation statements)

References 48 publications

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“…The non-Gaussian dynamics and broad spectrum of diffusivities may be a general feature of crowded macromolecular systems, with similar results to ours recently reported for the diffusion of membrane receptors in Xenopus embryo muscle cells (64). Another example is a colloidal fluid near its glass transition, which exhibits a broad spectrum of particle dynamics resulting in a stretched-exponential displacement distribution (11) and positive values of the NGP (12).…”

Section: Discussionsupporting

confidence: 85%

“…Thus, the analyses presented in this work provide a wealth of information on cellular transport and a procedure for deconvolving the physical mechanism for transport from the considerable variability inherent from cell-to-cell and within a single cell. Our study complements well other work that uses several different statistics to analyze anomalous transport behaviors (58,64,72). Cellular transport is involved in virtually all biological processes.…”

Section: Discussionsupporting

confidence: 71%

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Cytoplasmic RNA-Protein Particles Exhibit Non-Gaussian Subdiffusive Behavior

Lampo

Stylianidou²,

Backlund

et al. 2017

Biophysical Journal

188

271

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The cellular cytoplasm is a complex, heterogeneous environment (both spatially and temporally) that exhibits viscoelastic behavior. To further develop our quantitative insight into cellular transport, we analyze data sets of mRNA molecules fluorescently labeled with MS2-GFP tracked in real time in live Escherichia coli and Saccharomyces cerevisiae cells. As shown previously, these RNA-protein particles exhibit subdiffusive behavior that is viscoelastic in its origin. Examining the ensemble of particle displacements reveals a Laplace distribution at all observed timescales rather than the Gaussian distribution predicted by the central limit theorem. This ensemble non-Gaussian behavior is caused by a combination of an exponential distribution in the time-averaged diffusivities and non-Gaussian behavior of individual trajectories. We show that the non-Gaussian behavior is a consequence of significant heterogeneity between trajectories and dynamic heterogeneity along single trajectories. Informed by theory and simulation, our work provides an in-depth analysis of the complex diffusive behavior of RNA-protein particles in live cells.

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Section: Discussionsupporting

confidence: 85%

Section: Discussionsupporting

confidence: 71%

Cytoplasmic RNA-Protein Particles Exhibit Non-Gaussian Subdiffusive Behavior

Lampo

Stylianidou²,

Backlund

et al. 2017

Biophysical Journal

188

271

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show abstract

“…Such rejection is important since this immobile fraction often dominates the population of single trajectories2122, and may complicate attempts to distinguish the step-size Gaussianity of distinct subpopulations.…”

Section: Discussionmentioning

confidence: 99%

Resolving mixed mechanisms of protein subdiffusion at the T cell plasma membrane

Golan

Sherman

2017

Nat Commun

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The plasma membrane is a complex medium where transmembrane proteins diffuse and interact to facilitate cell function. Membrane protein mobility is affected by multiple mechanisms, including crowding, trapping, medium elasticity and structure, thus limiting our ability to distinguish them in intact cells. Here we characterize the mobility and organization of a short transmembrane protein at the plasma membrane of live T cells, using single particle tracking and photoactivated-localization microscopy. Protein mobility is highly heterogeneous, subdiffusive and ergodic-like. Using mobility characteristics, we segment individual trajectories into subpopulations with distinct Gaussian step-size distributions. Particles of low-to-medium mobility consist of clusters, diffusing in a viscoelastic and fractal-like medium and are enriched at the centre of the cell footprint. Particles of high mobility undergo weak confinement and are more evenly distributed. This study presents a methodological approach to resolve simultaneous mixed subdiffusion mechanisms acting on polydispersed samples and complex media such as cell membranes.

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“…Similarly, in simulations of crowded membranes it was shown that δ is between 1.3 and 1.6, and α below 1 [33] 4 . This behaviour can be explained by the fact that the considered medium is spatially or temporally heterogeneous [23,24,28,[35][36][37]. In such a system the thermal fluctuations are still Gaussian but the observed displacements are mixtures of these Gaussian contributions with random weights, effecting the non-Gaussian outcome.…”

Section: Physical Stochastic Modelling and Autoregressive Models 21mentioning

confidence: 99%

Random coefficient autoregressive processes describe Brownian yet non-Gaussian diffusion in heterogeneous systems

2019

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Many studies on biological and soft matter systems report the joint presence of a linear mean-squared displacement and a non-Gaussian probability density exhibiting, for instance, exponential or stretched-Gaussian tails. This phenomenon is ascribed to the heterogeneity of the medium and is captured by random parameter models such as 'superstatistics' or 'diffusing diffusivity'. Independently, scientists working in the area of time series analysis and statistics have studied a class of discrete-time processes with similar properties, namely, random coefficient autoregressive models. In this work we try to reconcile these two approaches and thus provide a bridge between physical stochastic processes and autoregressive models. We start from the basic Langevin equation of motion with time-varying damping or diffusion coefficients and establish the link to random coefficient autoregressive processes. By exploring that link we gain access to efficient statistical methods which can help to identify data exhibiting Brownian yet non-Gaussian diffusion.

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Dynamic heterogeneity and non-Gaussian statistics for acetylcholine receptors on live cell membrane

Cited by 173 publications

References 48 publications

Cytoplasmic RNA-Protein Particles Exhibit Non-Gaussian Subdiffusive Behavior

Cytoplasmic RNA-Protein Particles Exhibit Non-Gaussian Subdiffusive Behavior

Resolving mixed mechanisms of protein subdiffusion at the T cell plasma membrane

Random coefficient autoregressive processes describe Brownian yet non-Gaussian diffusion in heterogeneous systems

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