A spatial model of YAP/TAZ signaling reveals how stiffness, dimensionality, and shape contribute to emergent outcomes

Abstract

YAP/TAZ is a master regulator of mechanotransduction whose functions rely on translocation from the cytoplasm to the nucleus in response to diverse physical cues. Substrate stiffness, substrate dimensionality, and cell shape are all input signals for YAP/TAZ, and through this pathway, regulate critical cellular functions and tissue homeostasis. Yet, the relative contributions of each biophysical signal and the mechanisms by which they synergistically regulate YAP/TAZ in realistic tissue microenvironments that provide multiplexed input signals remain unclear. For example, in simple two-dimensional culture, YAP/TAZ nuclear localization correlates strongly with substrate stiffness, while in three-dimensional (3D) environments, YAP/TAZ translocation can increase with stiffness, decrease with stiffness, or remain unchanged. Here, we develop a spatial model of YAP/TAZ translocation to enable quantitative analysis of the relationships between substrate stiffness, substrate dimensionality, and cell shape. Our model couples cytosolic stiffness to nuclear mechanics to replicate existing experimental trends, and extends beyond current data to predict that increasing substrate activation area through changes in culture dimensionality, while conserving cell volume, forces distinct shape changes that result in nonlinear effect on YAP/TAZ nuclear localization. Moreover, differences in substrate activation area versus total membrane area can account for counterintuitive trends in YAP/TAZ nuclear localization in 3D culture. Based on this multiscale investigation of the different system features of YAP/TAZ nuclear translocation, we predict that how a cell reads its environment is a complex information transfer function of multiple mechanical and biochemical factors. These predictions reveal a few design principles of cellular and tissue engineering for YAP/TAZ mechanotransduction.

Control of protein-based pattern formation via guiding cues

“…Mechanochemical feedback loops are a special case of a general phenomenon that can be observed in many pattern-forming systems: may patterns in cells are not the result of a single guiding cue, but are the products of multiple interacting cues and processes [53, 75, 79, 203–205]. However, it is often difficult to separate all the processes involved in the robust formation of functional protein patterns in living cells, as the example of C. elegans polarisation shows [3, 8, 53, 93].…”

Control of protein-based pattern formation via guiding cues

“…Mechanochemical feedback loops are a special case of a general phenomenon that can be observed in many pattern-forming systems: may patterns in cells are not the result of a single guiding cue, but are the products of multiple interacting cues and processes [53,75,79,[203][204][205]. However, is often difficult to separate all the processes involved in the robust formation of functional protein patterns in living cells, as the example of C. elegans polarisation shows [3,8,53,93].…”

OpenACC Acceleration of an Agent-Based Biological Simulation Framework

“…If execution time were left unchanged, then larger domains with more agents could be simulated, enabling studies of more complex tissues and even small organisms. Lastly, the increased "computational budget" afforded by a more complete GPU acceleration could allow us to introduce multiple agents per biological cell allowing sophisticated simulations of not only cell morphology (e.g., as in subcellular element models [1], [44]), but even introducing agents for subcellular components and biophysical processes, such as movement, fission, and fusion of Golgi bodies during signaling [45], [46]. This could be transformative in relating emerging high-resolution microsopy [47], [48] to intracellular biophysics and functional biology.…”