Actin network heterogeneity tunes activator-inhibitor dynamics at the cell cortex
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Biological systems can display diverse patterns of self-organization, even when built on conserved networks of interaction between molecular species. In these cases, reaction-diffusion equations provide a valuable tool to learn how new dynamics could emerge from quantitative tuning of parameters. Bringing these models into quantitative correspondence with biological data remains an outstanding challenge, especially when the biology manifests heterogeneities that are difficult to account for mathematically. One particular example occurs in cell biology, where the membrane-bound regulatory protein RhoA interacts with the filamentous actin cortex in an activator-inhibitor loop. Though this core biochemical circuit is conserved across multiple cell types in different organisms, it produces different patterns of RhoA activity in different contexts, from traveling waves in starfish to transient pulses in C. elegans . To understand how this variation emerges, we develop an activator-inhibitor model that accounts explicitly for actin assembly and heterogeneity. We use the model to infer the parameters of actin dynamics responsible for each experimental phenotype, and find them to agree with independent measurements in most cases. To interpret parameter groupings, we use a simplified model to demonstrate how spatial and orientational randomness separately induce variation in spatiotemporal dynamics of RhoA activity. This work sheds light on how phenotypic diversity arises from heterogeneity and anisotropy, with important implications for the next generation of activator-inhibitor models.
Significance
To divide, move, and polarize, cells must self-organize their constituent proteins into large-scale patterns with varied spatiotemporal character. The design principles of this process remain poorly understood, primarily because a quantitative match between mathematical models and experimental data is difficult. In this paper, we consider pattern formation from two constituents on the cell cortex: the regulatory protein RhoA, and actin filaments. Using a mathematical model, constrained quantitatively on data from multiple organisms, we show how diversity in RhoA activity patterns could arise from intra- and inter-organismal changes in actin filament architecture and assembly dynamics. Our results reveal general principles for pattern formation at the cortex, and our combination of data analysis, modeling, and parameter inference provides a broadly-applicable, interdisciplinary methodology to unravel self-organization.