Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userDistribution of active forces in the cell cortex
406
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
In this work, we study in detail the distribution of stochastic forces generated by the molecular motors activity, in the actin cortex of pre-muscular cells. By combining active and passive rheology experiments, performed on the same micro-bead bound to the actin network through membrane adhesive receptors, we measure the auto-correlation function Cff(t) of the average force pulling on the bead. Like for any out-of-equilibrium system, the force distribution differs from the thermodynamical equilibrium one, especially at long time scale t>1sec where the bead motion becomes partially directed. Thus the fluctuation-dissipation theorem does not apply and one can measure the distance from equilibrium through its violation. This work focuses on the influence of various parameters (ligand density, temperature, ATP depletion, molecular motors activity) on the force distribution. In particular, it is shown that the amplitude of active forces increases when the bead is more tighly attached to the cortex: this is interpreted through a model which takes into account the number of bonds between the bead and the cytoskeleton and the viscoelastic properties of the medium. It also increases with temperature, consistently with a description of the cell metabolism in terms of thermally activated reactions. Last, but not least, ATP depletion in the cell, or partial inhibitition of the actomyosin activity, leads to a decrease of the amplitude of the force distribution. Altogether, we propose a consistent and quantitative description for the motion of a micrometric probe interacting with the actin network, and for the amplitude of the stochastic forces generated by molecular motors in the cortex surrounding this probe.
rate research
Read More
Mapping of the forces on biomolecules in cell membranes has spurred the development of effective labels, e.g. organic fluorophores and nanoparticles, to track trajectories of single biomolecules. Standard methods use particular statistics, namely the mean square displacement, to analyze the underlying dynamics. Here, we introduce general inference methods to fully exploit information in the experimental trajectories, providing sharp estimates of the forces and the diffusion coefficients in membrane microdomains. Rapid and reliable convergence of the inference scheme is demonstrated on trajectories generated numerically. The method is then applied to infer forces and potentials acting on the receptor of the $epsilon$-toxin labeled by lanthanide-ion nanoparticles. Our scheme is applicable to any labeled biomolecule and results show show its general relevance for membrane compartmentation.
Gaining access to the cell interior is fundamental for many applications, such as electrical recording, drug and biomolecular delivery. A very promising technique consists of culturing cells on nano/micro pillars. The tight adhesion and high local deformation of cells in contact with nanostructures can promote the permeabilization of lipids at the plasma membrane, providing access to the internal compartment. However, there is still much experimental controversy regarding when and how the intracellular environment is targeted and the role of the geometry and interactions with surfaces. Consequently, we investigated, by coarse-grained molecular dynamics simulations of the cell membrane, the mechanical properties of the lipid bilayer under high strain and bending conditions. We found out that a high curvature of the lipid bilayer dramatically lowers the traction force necessary to achieve membrane rupture. Afterwards, we experimentally studied the permeabilization rate of cell membrane by pillars with comparable aspect ratios but different sharpness values at the edges. The experimental data support the simulation results: even pillars with diameters in the micron range may cause local membrane disruption when their edges are sufficiently sharp. Therefore, the permeabilization likelihood is connected to the local geometric features of the pillars rather than diameter or aspect ratio. The present study can also provide significant contributions to the design of 3D biointerfaces for tissue engineering and cellular growth.
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.
Virus capsids in interchromatin corrals of a cell nucleus are experimentally known to exhibit anomalous diffusion as well as normal diffusion, leading to the Gaussian distribution of the diffusion-exponent fluctuations over the corrals. Here, the sojourn-time distribution of the virus capsid in local areas of the corral, i.e., probability distribution of the sojourn time characterizing diffusion in the local areas, is examined. Such an area is regarded as a virtual cubic block, the diffusion property in which is normal or anomalous. The distribution, in which the Gaussian fluctuation is incorporated, is shown to tend to slowly decay. Then, the block-size dependence of average sojourn time is discussed. A comment is also made on (non-)Markovianity of the process of moving through the blocks.
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.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
