Spatiotemporal development of coexisting wave domains of Rho activity in the cell cortex

Abstract

The Rho family GTPases are molecular switches that regulate cytoskeletal dynamics and cell movement through a complex spatiotemporal organization of their activity. In Patiria miniata (starfish) oocytes under in vitro experimental conditions (with overexpressed Ect2, induced expression of Δ90 cyclin B, and roscovitine treatment), such activity generates multiple co-existing regions of coherent propagation of actin waves. Here we use computational modeling to investigate the development and properties of such wave domains. The model reveals that the formation of wave domains requires a balance between the activation and inhibition in the Rho signaling motif. Intriguingly, the development of the wave domains is preceded by a stage of low-activity quasi-static patterns, which may not be readily observed in experiments. Spatiotemporal patterns of this stage and the different paths of their destabilization define the behavior of the system in the later high-activity (observable) stage. Accounting for a strong intrinsic noise allowed us to achieve good quantitative agreement between simulated dynamics in different parameter regimes of the model and different wave dynamics in Patiria miniata and wild type Xenopus laevis (frog) data. For quantitative comparison of simulated and experimental results, we developed an automated method of wave domain detection, which revealed a sharp reversal in the process of pattern formation in starfish oocytes. Overall, our findings provide an insight into spatiotemporal regulation of complex and diverse but still computationally reproducible cell-level actin dynamics.

Septins provide microenvironment sensing and cortical actomyosin partitioning in motile amoeboid T lymphocytes

“…Next, the resulting images were rescaled with a log function and masked with a threshold value of 6.4. To identify individual cells, the resulting binary masks were overlaid with the smoothed SD maps and subjected to our in-house watershed segmentation routine [using an algorithm that includes “draining” criteria allowing to avoid over-segmentation ( 51 ), which is typical for the traditional watershed approaches]. Centroids of all eight-connected objects in the segmented images were recorded for tracking.…”

Spatiotemporal coordination of Rac1 and Cdc42 at the whole cell level during cell ruffling

“…To ensure mass conservation and positivity of the solution, we applied additional checks at each iteration, as described in [44]. We solved the equations in an arbitrarily shaped simulation domain representing cell shape with no-flux boundary conditions.…”

“…To this end, we used the discrete Laplace operator (based on a five-point stencil) with components representing fluxes across the edge of the simulation domain set to zero. For the details of this implementation, see [44]. As a static simulation domain (i.e., in the case of a non-moving cell), we used a square domain of 200x200 grid points (4x4 a.u).…”

“…To investigate the response of the 2D model of GTPase activity during cell ruffling to different values of noise, we performed a series of simulations with different values of noise amplitude (Supplemental Figure 1). We also applied textural analysis for the quantification of patterns (see [44] for this method of analysis). With small values of noise, patterns were not formed because diffusion fluxes had sufficiently high values to prevent pattern formation at the edge of the domain.…”

“…Importantly, this model captures the Turing-unstable type of behavior, in which the activity of small-GTPases remains non-homogeneous, as well as the transition to the excitable regime, in which a stimulus-induced activation is required to generate GTPase patterning. Therefore, the MCRD model can be used to represent a core signaling motif of GTPases and, when coupled with downstream and upstream effectors, can reproduce rich dynamics, including the formation of complex cortical waves of GTPase activity [44]. A more detailed variation of this model was also successfully applied to study the coordination of RhoA and Rac1 in the leading and trailing edges of moving cells [45].…”