Key result
An analytical model incorporating active dynamics of myosin motors successfully encapsulated load-and-fail dynamics and shifts in traction optima, providing excellent agreement with experiments.
Why the study?
The molecular clutch hypothesis models cellular force generation, but analytical models were needed to incorporate active myosin motor dynamics and establish their role in traction force regulation.
The proposed analytical model successfully encapsulates the hallmarks of motor-clutch models and demonstrates how modulating myosin activity shifts optimal stiffness.
No immediate clinical application; extends motor-clutch modeling for future cardiac mechanobiology studies.
Cells generate traction forces on the extracellular matrix to crawl forward. A complex molecular machinery is involved in the generation, transmission, and transduction of cellular forces inside and outside of cells. The molecular clutch hypothesis, with motors as rudimentary force generators, has been beneficial in modelling the distinctive biomechanical roles played by the components of this machinery. In this paper, we propose an analytical model that incorporates the active dynamics of myosin motors and establishes their roles in regulating the traction force in an experimentally accessible parameter space. As the parameters pertaining to molecular determinants are varied, we show that the system traverses between diverse states of stabilities - from decaying oscillations to self-sustaining limit cycles. The hallmarks of motor-clutch models like load-and-fail dynamics and shift in traction optima are successfully encapsulated. Modulating myosin activity in our model via different pathways exhibits striking shifts in optimal stiffness, providing excellent agreement with experiments and additional testable predictions.
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Ghosh et al. (2022) studied this question. Analytical model of myosin motors was evaluated on Traction force regulation and system stability. An analytical model incorporating active dynamics of myosin motors successfully encapsulated load-and-fail dynamics and shifts in traction optima, providing excellent agreement with experiments.
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