Iva Tolic-Nørrelykke

Tolic-Norrelykke, Iva M.

doi:10.1016/j.cub.2011.03.018

Cited by 4 publications

(8 citation statements)

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“…Motor-driven processes in cells often exhibit anomalous statistics [12,[46][47][48], and these statistics can have important functional consequences [9]. While existing random-walk models of aging typically start by assuming trapped states with power-law dwell times, we introduce a microscopic mechanism for how simple biologically consistent interactions can…”

Section: Discussionmentioning

confidence: 99%

“…The resulting trajectories can be treated as random walks, and quantitative analysis of their statistics can provide insights into underlying mechanisms [1,9]. Often, the mean square displacement (MSD) exhibits a power-law (typically sublinear) dependence on the separation in time between two observations, known as the lag time (∆) [1,9,[11][12][13][14][15]. In certain cases [9,14], the MSD also decays as the amount of data included in averages (the measurement time, T ) increases; this trend indicates a power-law distribution of dwell times and is known as "aging" in theories of glassy dynamic [16].These correlations can have important biological implications [9,17].…”

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confidence: 99%

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Cycling State that Can Lead to Glassy Dynamics in Intracellular Transport

et al. 2016

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Power-law dwell times have been observed for molecular motors in living cells, but the origins of these trapped states are not known. We introduce a minimal model of motors moving on a twodimensional network of filaments, and simulations of its dynamics exhibit statistics comparable to those observed experimentally. Analysis of the model trajectories, as well as experimental particle tracking data, reveals a state in which motors cycle unproductively at junctions of three or more filaments. We formulate a master equation for these junction dynamics and show that the time required to escape from this vortex-like state can account for the power-law dwell times. We identify trends in the dynamics with the motor valency for further experimental validation. We demonstrate that these trends exist in individual trajectories of myosin II on an actin network.We discuss how cells could regulate intracellular transport and, in turn, biological function, by controlling their cytoskeletal network structures locally.Individual microscopic particles (beads [1,2] or fluorescently labeled molecules [3-5]) can now be tracked in cells. These studies reveal complex dynamics [6][7][8]. The resulting trajectories can be treated as random walks, and quantitative analysis of their statistics can provide insights into underlying mechanisms [1,9]. Often, the mean square displacement (MSD) exhibits a power-law (typically sublinear) dependence on the separation in time between two observations, known as the lag time (∆) [1,9,[11][12][13][14][15]. In certain cases [9,14], the MSD also decays as the amount of data included in averages (the measurement time, T ) increases; this trend indicates a power-law distribution of dwell times and is known as "aging" in theories of glassy dynamic [16].These correlations can have important biological implications [9,17]. For example, a recent study shows that the anomalous dynamics observed for insulin secretory vesicles (granules) can account for the biphasic kinetics of insulin release [9] without the need to invoke separate pools of granules, as previously [18]. In particular, the sustained release relies on the glassy dynamics. Glassy dynamics are often interpreted in terms of trapping in local minima of an energy landscape with an exponential or power-law distribution of depths [19,20]. However, how such a landscape could arise from typical biomolecular interactions is unclear. Crowding is insufficient, as it results in standard Brownian motion but with a reduced diffusion coefficient [21]. Because the moving vesicles are associated with molecular motors, which consume cellular energy stores (nucleotide triphosphates) for directed motion along cytoskeletal filaments, other, intrinsically nonequilibrium mechanisms of generating these statistics may exist.In the case of insulin release, the vesicles have both kinesin and dynein associated with them [22], which walk in opposite directions on microtubules [23]. More generally, many cytoskeletal assemblies in cells have multiple motors associated with ...

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Cycling State that Can Lead to Glassy Dynamics in Intracellular Transport

et al. 2016

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“…Applications of these kinds may occur at much smaller spatial scales compared to those typical of animal territorial dynamics. At the sub-cellular level for example, the positioning of certain cell components is crucial to its functioning and relies upon the continuous exploration through a variety of motor proteins of the slowly changing intracellular space [25]. The moving boundaries in this context would represent the translation and deformation of the cell membrane.…”

Section: Discussionmentioning

confidence: 99%

Brownian walkers within subdiffusing territorial boundaries

Giuggioli

Potts

2011

Phys. Rev. E

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Inspired by the collective phenomenon of territorial emergence, whereby animals move and interact through the scent marks they deposit, we study the dynamics of a 1D Brownian walker in a random environment consisting of confining boundaries that are themselves diffusing anomalously. We show how to reduce, in certain parameter regimes, the non-Markovian, many-body problem of territoriality to the analytically tractable one-body problem studied here. The mean square displacement (MSD) of the 1D Brownian walker within subdiffusing boundaries is calculated exactly and generalizes well known results when the boundaries are immobile. Furthermore, under certain conditions, if the boundary dynamics are strongly subdiffusive, we show the appearance of an interesting non-monotonicity in the time dependence of the MSD, giving rise to transient negative diffusion.

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“…. 0.85 [8][9][10][11]; and the diffusion of telomeres in the nucleus of mammalian cells shows α ≈ 0.3 at shorter times, and α ≈ 0.5 at intermediate times [12]. A study assuming normal diffusion for the analysis of tracking data of single cell nuclear organelles shows extreme fluctuations of the diffusivity as function of time along individual trajectories, possibly pointing to subdiffusion effects [13].…”

Section: Introductionmentioning

confidence: 98%

“…Yet apparently the first experimental study based on the time series analysis of single particle trajectories is due to Nordlund who tracked small mercury spheres in water [5]. Today single trajectory analysis is a common method to probe the motion of particles, notably, in complex biological environments [6][7][8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Single Particle Trajectories: Mean Maximal Excursion Method

Tejedor

Bénichou

Voituriez

et al. 2010

Biophysical Journal

200

207

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An increasing number of experimental studies employ single particle tracking to probe the physical environment in complex systems. We here propose and discuss what we believe are new methods to analyze the time series of the particle traces, in particular, for subdiffusion phenomena. We discuss the statistical properties of mean maximal excursions (MMEs), i.e., the maximal distance covered by a test particle up to time t. Compared to traditional methods focusing on the mean-squared displacement we show that the MME analysis performs better in the determination of the anomalous diffusion exponent. We also demonstrate that combination of regular moments with moments of the MME method provides additional criteria to determine the exact physical nature of the underlying stochastic subdiffusion processes. We put the methods to test using experimental data as well as simulated time series from different models for normal and anomalous dynamics such as diffusion on fractals, continuous time random walks, and fractional Brownian motion.

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Iva Tolic-Nørrelykke

Cited by 4 publications

References 0 publications

Cycling State that Can Lead to Glassy Dynamics in Intracellular Transport

Cycling State that Can Lead to Glassy Dynamics in Intracellular Transport

Brownian walkers within subdiffusing territorial boundaries

Quantitative Analysis of Single Particle Trajectories: Mean Maximal Excursion Method

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