A coarse-grained approach to model the dynamics of the actomyosin cortex

Figures

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  Fig. 1.. Dynamics of F-actin polymerization. A Snapshots of the system at three different simulation times, corresponding to the three regimes: nucleation, polymerization, and equilibrium/reorganization. B Number of filaments forming as a function of time during the three regimes. The three lines correspond to three independent runs of the model. C Percentage of the nodes in the network occupied by actin molecules as a function of time during the three phases. The three lines correspond to three independent runs of the model. D Probability size distribution of F-actin for the three different phases, measured in terms of monomer units. Histograms correspond to three time points of the same numerical realization of the model

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  Fig. 2.. Dependence of F-actin features on model parameters. A Dependence of the amount of G-actin in free monomer and polymer configuration on the total amount of G-actin in the system N1,0 for three different values of E1. B Phase diagram plotting the cortex occupancy for different values of the average < μ1> and E1. C Phase diagram plotting the average length of F-actin for different values of the average < μ1> and E1

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  Fig. 3.. The model reproduces F-actin treadmilling. A Snapshots of the cell cortex showing two filaments (highlighted in red and blue) moving in different directions due to directional treadmilling. B Displacement of all filaments in a simulation showing the dispersion in velocity values for different values of energy E1. C Dependence on the velocity of filaments on the potential < μ1> for different values of the E1

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  Fig. 4.. The model reproduces the dynamics of network formation. A Snapshots of system for different time points of a given simulation. ACs are added at t1. B Phase diagram showing the average network size at equilibrium for different values of E2 and N2,0. C Size of the largest and the second largest networks for different ratios of N2,0/N1,0. D Length distribution of filaments without (left) and with (right) ACs

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  Fig. 5.. The model reproduces actomyosin oscillations. A Snapshots of the system for three different time points of a given simulation (green is G-actin, blue is ACs, red is myosin). B Temporal evolution of total actin and myosin in the cortex. C Temporal evolution of tension (red) and number of bundles (green)

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  Fig. 6.. The model predicts the effect of integrin overexpression. A Snapshots of the system for two different values of E1 (green is G-actin, snapshot taken at the point of maximal value of occupancy in a oscillation). B Temporal evolution of total actin and myosin in the cortex for the two values of E1 tested. Dashed gray lines show the average levels of actin. C Mean fluorescent intensity of integrins in stress fibers of follicle cells in control and αPS1; βPS overexpression (labeled as gain of function (GOF)) conditions (N = 11 for each condition). D, E Confocal images of the basal surface of follicle cells for control (D) and GOF (E) conditions expressing the F-actin live marker Ubi-LifeActinGFP stained for anti-GFP (green) and anti-BPS integrin (red). Circles denote follicle cells with the highest (solid line) and the lowest (dashed line) levels of F-actin fluorescence. F Quantification of the dynamic changes of basal F-actin in three individual follicle cells for control (left) and GOF (right) conditions. G Basal F-actin average oscillation period for control and GOF conditions (N = 11 for each condition)