Skeletal actomyosin geometry orchestrates motor cooperativity as a time-variable network

Abstract

Groups of non-processive myosin motors exhibit complex and non-linear behaviors when binding to actin, operating at larger scales and time frames than individual myosin-head actions. This indicates the presence of strong cooperative disposition, generally attributed to the motor’s biochemistry. Limits in contemporary microscopy prevent verification of motor-filament (un)binding dynamics, whilst mathematical models rely on continuum abstractions in which cooperativity is implicit and individual motor behavior is lacking. Understanding the fundamental interactions driving the emergent behaviour in actomyosin remains an open question. Here we show that the diversity of empirically observedin-vitrooscillations can be explained by a single minimal synchronization model of self-organised time-variable network of Kuramoto oscillators orchestrated by the actomyosin geometry. The synchronization model mirrors the irregular and regular saw-tooth oscillations present inin-vitroactomyosin and sarcomeric contraction experiments, without parameter adjustments, and despite the model’s simplicity. Actomyosin-like behaviour thus arise as a generic property of the discontinuous mechanical coupling in an incommensurate architecture, rather than specific to molecular motor reaction kinetics. This demonstrates that non-biological motors can cooperate similarly to biological motors when working within an actomyosin geometry. This suggests that the actomyosin complex may not depend on motor-specific qualities to achieve its biological function. We build a physical experimental replica with non-biological motors and demonstrate that the brief self-organised connectivity dynamics is sufficient to cause the formation of spontaneous metachronal travelling waves. Global entrainment occurs via spatiotemporal patterning of the connectivity among nodes, coupling a maximum of 35% of motors, whilst minimising velocity changes, in a demonstration of morphological control and self-gearing mechanism. Altogether, the synchronization model reduces mathematical complexity and unify theoretical predictions of observed emergent behaviour. These findings also offer novel insights into synchronizing time-variable networks and potential applications in emulating actomyosin-like behaviors within contemporary robotics using non-biological motors.