Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userMaximal fluctuations of confined actomyosin gels: dynamics of the cell nucleus
74
0
0.0
(
0
)
Added by
Jean-Fran\\c{c}ois Rupprecht
Publication date
2017
fields
Physics
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
We investigate the effect of stress fluctuations on the stochastic dynamics of an inclusion embedded in a viscous gel. We show that, in non-equilibrium systems, stress fluctuations give rise to an effective attraction towards the boundaries of the confining domain, which is reminiscent of an active Casimir effect. We apply this generic result to the dynamics of deformations of the cell nucleus and we demonstrate the appearance of a fluctuation maximum at a critical level of activity, in agreement with recent experiments [E. Makhija, D. S. Jokhun, and G. V. Shivashankar, Proc. Natl. Acad. Sci. U.S.A. 113, E32 (2016)].
rate research
Read More
Bacterial processes ranging from gene expression to motility and biofilm formation are constantly challenged by internal and external noise. While the importance of stochastic fluctuations has been appreciated for chemotaxis, it is currently believed that deterministic long-range fluid dynamical effects govern cell-cell and cell-surface scattering - the elementary events that lead to swarming and collective swimming in active suspensions and to the formation of biofilms. Here, we report the first direct measurements of the bacterial flow field generated by individual swimming Escherichia coli both far from and near to a solid surface. These experiments allowed us to examine the relative importance of fluid dynamics and rotational diffusion for bacteria. For cell-cell interactions it is shown that thermal and intrinsic stochasticity drown the effects of long-range fluid dynamics, implying that physical interactions between bacteria are determined by steric collisions and near-field lubrication forces. This dominance of short-range forces closely links collective motion in bacterial suspensions to self-organization in driven granular systems, assemblages of biofilaments, and animal flocks. For the scattering of bacteria with surfaces, long-range fluid dynamical interactions are also shown to be negligible before collisions; however, once the bacterium swims along the surface within a few microns after an aligning collision, hydrodynamic effects can contribute to the experimentally observed, long residence times. As these results are based on purely mechanical properties, they apply to a wide range of microorganisms.
Cells coexist together in colonies or as tissues. Their behaviour is controlled by an interplay between intercellular forces and biochemical regulation. We develop a simple model of the cell cycle, the fundamental regulatory network controlling growth and division, and couple this to the physical forces arising within the cell collective. We analyse this model using both particle-based computer simulations and a continuum theory. We focus on 2D colonies confined in a channel. These develop moving growth fronts of dividing cells with quiescent cells in the interior. The profile and speed of these fronts are non-trivially related to the substrate friction and the cell cycle parameters, providing a possible approach to measure such parameters in experiments.
A stochastic version of the Barkai-Leibler model of chemotaxis receptors in {it E. coli} is studied here to elucidate the effects of intrinsic network noise in their conformational dynamics. It was originally proposed to explain the robust and near-perfect adaptation of {it E. coli} observed across a wide range of spatially uniform attractant/repellent (ligand) concentrations. A receptor is either active or inactive and can stochastically switch between the two states. Enzyme CheR methylates inactive receptors while CheB demethylates active ones and the probability for it to be active depends on its level of methylation and ligandation. A simple version of the model with two methylation sites per receptor (M=2) shows zero-order ultrasensitivity (ZOU) akin to the classical 2-state model of covalent modification studied by Goldbeter and Koshland (GK). For extremely small and large ligand concentrations, the system reduces to two 2-state GK modules. A quantitative measure of the spontaneous fluctuations in activity (variance) estimated mathematically under linear noise approximation (LNA) is found to peak near the ZOU transition. The variance is a weak, non-monotonic and decreasing functions of ligand and receptor concentrations. Gillespie simulations for M=2 show excellent agreement with analytical results obtained under LNA. Numerical results for M=2, 3 and 4 show ZOU in mean activity; the variance is found to be smaller for larger M. The magnitude of receptor noise deduced from available experimental data is consistent with our predictions. A simple analysis of the downstream signaling pathway shows that this noise is large enough to have a beneficial effect on the motility of the organism. The response of mean receptor activity to small time-dependent changes in the external ligand concentration, computed within linear response theory, is found to have a bilobe form.
We develop a microscopic biophysical model for self-organization and reshaping of artificial tissue, that is co-driven by microscopic active forces between cells and extracellular matrix (ECM), and macroscopic forces that develop within the tissue, finding close agreement with experiment. Microscopic active forces are stimulated by $mu$m scale interactions between cells and the ECM within which they exist, and when large numbers of cells act together these forces drive, and are affected by, macroscopic-scale self-organization and reshaping of tissues in a feedback loop. To understand this loop, there is a need to: (1) construct microscopic biophysical models that can simulate these processes for the very large number of cells found in tissues; (2) validate and calibrate those models against experimental data; and (3) understand the active feedback between cells and the extracellular matrix, and its relationship to macroscopic self-organization and reshaping of tissue. Our microscopic biophysical model consists of a contractile network representing the ECM, that interacts with a large number of cells via dipole forces, to describe macroscopic self-organization and reshaping of tissue. We solve the model using simulated annealing, finding close agreement with experiments on artificial neural tissue. We discuss calibration of model parameters. We conclude that feedback between microscopic cell-ECM dipole interactions and tissue-scale forces, is a key factor in driving macroscopic self-organization and reshaping of tissue. We discuss application of the biophysical model to simulation and rational design of artificial tissues.
We develop a general theory for active viscoelastic materials made of polar filaments. This theory is motivated by the dynamics of the cytoskeleton. The continuous consumption of a fuel generates a non equilibrium state characterized by the generation of flows and stresses. Our theory can be applied to experiments in which cytoskeletal patterns are set in motion by active processes such as those which are at work in cells.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
