Correlating anomalous diffusion with lipid bilayer membrane structure using single molecule tracking and atomic force microscopy

Skaug, Michael J.; Faller, Roland; Longo, Marjorie L.

doi:10.1063/1.3596377

Cited by 42 publications

(39 citation statements)

References 46 publications

(56 reference statements)

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“…Th e diff erent character of the observed diff usion can be interpreted on the basis of obstacles present in the bilayer. So, a combination of studies in which the results of optical diff usion experiments are compared to the nanometric structure obtained by AFM could be of high value in this context [53].…”

Section: Chemical-physical Properties Of Supported Lipid Bilayersmentioning

confidence: 99%

Model Bio‐Membranes Investigated by AFM and AFS: A Suitable Tool to Unravel Lipid Organization and their Interaction with Proteins

Alessandrini¹,

Facci²

2014

Smart Membranes and Sensors

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Th e study of the biological membrane has largely benefi tted from the exploitation of model bilayer systems. Th ese simplifi ed models of the complex biological membrane composed of thousands of diff erent types of molecules allow both to understand basic physical principles underlying the membrane functioning and to test new techniques that will be subsequently applied to biological membranes. Here we concentrate on one of the most used model systems for this kind of investigations: the Supported Lipid Bilayer (SLB). In particular, we analyze the possibilities of investigation off ered by Atomic Force Microscopy and Spectroscopy (AFM/ AFS) on this model system. We discuss the information that these techniques are able to provide on the phase behavior of the lipid bilayers and on the partitioning of membrane proteins relative to the bilayer lateral heterogeneity. We discuss also the possibility to characterize the mechanical properties of lipid bilayers on the nanometer scale lateral resolution.

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Section: Chemical-physical Properties Of Supported Lipid Bilayersmentioning

confidence: 99%

Model Bio‐Membranes Investigated by AFM and AFS: A Suitable Tool to Unravel Lipid Organization and their Interaction with Proteins

Alessandrini¹,

Facci²

2014

Smart Membranes and Sensors

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“…Although some previous studies have considered the effect of different obstacle shapes and sizes in detail [30][31][32][33], others have simply focused on studying transport through environments in which a single type of obstacle is present [14,15]. Here, we focus on environments containing a mixture of different types of obstacles since experimental images ( Fig.…”

Section: Introductionmentioning

confidence: 97%

“…Such FDE models have been analyzed in various biological settings including chemical reactions [23], reaction fronts [22,24] and reaction-diffusion mechanisms [25]. We would like to emphasize that the group of studies described here, focusing explicitly on motion through crowded environments using experimental and simulation data [30][31][32][33][35][36][37][38][39], have not attempted to interpret their results using any kind of FDE framework. Conversely, the group of studies described here focusing on FDE models [21][22][23][24][25] have not attempted to connect the solution of any FDE model to measurements from any simulation or experiment which explicitly represents transport through a crowded environment.…”

Section: Introductionmentioning

confidence: 98%

“…Progress has also been made by combining experimental and theoretical approaches, for example, studying overlapping circular and elliptical obstacles [38] and studying more complicated environments containing up to 15 different types of obstacles [31]. Other more experimentally oriented studies have sought to interpret trajectory data describing the motion of individual cells or molecules using various mathematical frameworks [32,33,39].…”

Section: Introductionmentioning

confidence: 98%

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Modeling transport through an environment crowded by a mixture of obstacles of different shapes and sizes

Ellery

Baker

McCue

et al. 2016

Physica A: Statistical Mechanics and its Applications

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h i g h l i g h t s• Stochastic simulations of individual and collective motion through a crowded environment. • Crowded environments populated by mixtures of obstacles of different shapes and sizes.• Transport properties depend on the obstacle volume fraction and details of the obstacle shape and size distribution. • Standard fractional diffusion equation descriptions ought to be used with care. a b s t r a c tMany biological environments are crowded by macromolecules, organelles and cells which can impede the transport of other cells and molecules. Previous studies have sought to describe these effects using either random walk models or fractional order diffusion equations. Here we examine the transport of both a single agent and a population of agents through an environment containing obstacles of varying size and shape, whose relative densities are drawn from a specified distribution. Our simulation results for a single agent indicate that smaller obstacles are more effective at retarding transport than larger obstacles; these findings are consistent with our simulations of the collective motion of populations of agents. In an attempt to explore whether these kinds of stochastic random walk simulations can be described using a fractional order diffusion equation framework, we calibrate the solution of such a differential equation to our averaged agent density information. Our approach suggests that these kinds of commonly used differential equation models ought to be used with care since we are unable to match the solution of a fractional order diffusion equation to our data in a consistent fashion over a finite time period.

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“…Nowadays, the time-correlated noise and its consequences, most notably the sub-diffusive processes [5][6][7], are thoroughly researched phenomena with multiple applications (e.g. [8,9]). …”

Section: Introductionmentioning

confidence: 99%

Collectivity in diffusion of colloidal particles: from effective interactions to spatially correlated noise

Majka¹,

Góra²

2017

J. Phys. A: Math. Theor.

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The collectivity in the simultaneous diffusion of many particles, i.e. the interdependence of stochastic forces affecting different particles in the same solution, is a largely overlooked phenomenon with no well-established theory. Recently, we have proposed a novel type of thermodynamically consistent Langevin dynamics driven by the Spatially Correlated Noise (SCN) that can contribute to the understanding of this problem. This model draws a link between the theory of effective interactions in binary colloidal mixtures and the properties of SCN. In the current article we review this model from the perspective of collective diffusion and generalize it to the case of multiple (N > 2) particles. Since our theory of SCN-driven Langevin dynamics has certain issues that could not be resolved within its framework, in this article we also provide another approach to the problem of collectivity. We discuss the multi-particle Mori-Zwanzig model, which is fully microscopically consistent. Indeed, we show that this model supplies many information, complementary to the SCN-based approach, e.g. it predicts the deterministic dynamics of the relative distance between the particles, it provides the approximation for non-equilibrium effective interactions and predicts the collective subdiffusion of tracers in group. These results provide the short-range, inertial limit of the earlier model and agree with its predictions under some general conditions. In this article we also review the origin of SCN and its consequences for the variety of physical systems, with emphasis on the colloids.

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Correlating anomalous diffusion with lipid bilayer membrane structure using single molecule tracking and atomic force microscopy

Cited by 42 publications

References 46 publications

Model Bio‐Membranes Investigated by AFM and AFS: A Suitable Tool to Unravel Lipid Organization and their Interaction with Proteins

Model Bio‐Membranes Investigated by AFM and AFS: A Suitable Tool to Unravel Lipid Organization and their Interaction with Proteins

Modeling transport through an environment crowded by a mixture of obstacles of different shapes and sizes

Collectivity in diffusion of colloidal particles: from effective interactions to spatially correlated noise

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