A statistical-mechanical framework for mechanically adaptive cytoskeletal organization

Abstract

Living cells continuously remodel their cytoskeleton in response to mechanical cues. Although these responses have been extensively documented, it remains unclear why continuous changes in the mechanical environment give rise to distinct intracellular architectures rather than gradual structural variation. Here, we introduce a statistical-mechanical framework in which alternative cytoskeletal organizations are represented as ensembles of microscopic configurations, allowing configurational entropy to compete with mechanically dependent interaction energies. Rather than reproducing the full molecular complexity of the cytoskeleton, the model asks which features of mechanically adaptive organization emerge from this minimal physical description. The framework predicts three successive structural transitions corresponding to stress fiber formation, alignment, and lateral aggregation. When these transitions are placed on a common cellular-tension axis that increases with substrate stiffness, the predicted sequence is consistent with our measurements of correlation length and anisotropy in senescent fibroblasts. The preservation of this stiffness-dependent sequence despite altered cellular physiology suggests that the observed ordering reflects a robust physical principle rather than a cell-state-specific phenomenon. Together, these results establish a statistical-mechanical framework for understanding how continuous mechanical cues bias the statistical selection of distinct cytoskeletal architectures.