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Register a new userStochastic modeling of cargo transport by teams of molecular motors
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Many different types of cellular cargos are transported bidirectionally along microtubules by teams of molecular motors. The motion of this cargo-motors system has been experimentally characterized in vivo as processive with rather persistent directionality. Different theoretical approaches have been suggested in order to explore the origin of this kind of motion. An effective theoretical approach, introduced by Muller et al., describes the cargo dynamics as a tug-of-war between different kinds of motors. An alternative approach has been suggested recently by Kunwar et al., who considered the coupling between motor and cargo in more detail. Based on this framework we introduce a model considering single motor positions which we propagate in continuous time. Furthermore, we analyze the possible influence of the discrete time update schemes used in previous publications on the systems dynamic.
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Within cells, vesicles and proteins are actively transported several micrometers along the cytoskeletal filaments. The transport along microtubules is propelled by dynein and kinesin motors, which carry the cargo in opposite directions. Bidirectional intracellular transport is performed with great efficiency, even under strong confinement, as for example in the axon. For this kind of transport system, one would expect generically cluster formation. In this work, we discuss the effect of the recently observed self-enhanced binding-affinity along the kinesin trajectories on the MT. We introduce a stochastic lattice-gas model, where the enhanced binding affinity is realized via a floor-field. From Monte Carlo simulations and a mean-field analysis we show that this mechanism can lead to self-organized symmetry-breaking and lane-formation which indeed leads to efficient bidirectional transport in narrow environments.
Regulating physical size is an essential problem that biological organisms must solve from the subcellular to the organismal scales, but it is not well understood what physical principles and mechanisms organisms use to sense and regulate their size. Any biophysical size-regulation scheme operates in a noisy environment and must be robust to other cellular dynamics and fluctuations. This work develops theory of filament length regulation inspired by recent experiments on kinesin-8 motor proteins, which move with directional bias on microtubule filaments and alter microtubule dynamics. Purified kinesin-8 motors can depolymerize chemically-stabilized microtubules. In the length-dependent depolymerization model, the rate of depolymerization tends to increase with filament length, because long filaments accumulate more motors at their tips and therefore shorten more quickly. When balanced with a constant filament growth rate, this mechanism can lead to a fixed polymer length. However, the mechanism by which kinesin-8 motors affect the length of dynamic microtubules in cells is less clear. We study the more biologically realistic problem of microtubule dynamic instability modulated by a motor-dependent increase in the filament catastrophe frequency. This leads to a significant decrease in the mean filament length and a narrowing of the filament length distribution. The results improve our understanding of the biophysics of length regulation in cells.
Non-processive molecular motors have to work together in ensembles in order to generate appreciable levels of force or movement. In skeletal muscle, for example, hundreds of myosin II molecules cooperate in thick filaments. In non-muscle cells, by contrast, small groups with few tens of non-muscle myosin II motors contribute to essential cellular processes such as transport, shape changes or mechanosensing. Here we introduce a detailed and analytically tractable model for this important situation. Using a three-state crossbridge model for the myosin II motor cycle and exploiting the assumptions of fast power stroke kinetics and equal load sharing between motors in equivalent states, we reduce the stochastic reaction network to a one-step master equation for the binding and unbinding dynamics (parallel cluster model) and derive the rules for ensemble movement. We find that for constant external load, ensemble dynamics is strongly shaped by the catch bond character of myosin II, which leads to an increase of the fraction of bound motors under load and thus to firm attachment even for small ensembles. This adaptation to load results in a concave force-velocity relation described by a Hill relation. For external load provided by a linear spring, myosin II ensembles dynamically adjust themselves towards an isometric state with constant average position and load. The dynamics of the ensembles is now determined mainly by the distribution of motors over the different kinds of bound states. For increasing stiffness of the external spring, there is a sharp transition beyond which myosin II can no longer perform the power stroke. Slow unbinding from the pre-power-stroke state protects the ensembles against detachment.
Inside cells, various cargos are transported by teams of molecular motors. Intriguingly, the motors involved generally have opposite pulling directions, and the resulting cargo dynamics is a biased stochastic motion. It is an open question how the cell can control this bias. Here we develop a model which takes explicitly into account the elastic coupling of the cargo with each motor. We show that bias can be simply controlled or even reversed in a counterintuitive manner via a change in the external force exerted on the cargo or a variation of the ATP binding rate to motors. Furthermore, the superdiffusive behavior found at short time scales indicates the emergence of motor cooperation induced by cargo-mediated coupling.
We discuss a theoretical model for bidirectional cargo transport in biological cells, which is driven by teams of molecular motors and subject to thermal fluctuations. The model describes explicitly the directed motion of the molecular motors on the filament. The motor-cargo coupling is implemented via linear springs. By means of extensive Monte Carlo simulations we show that the model describes the experimentally observed regimes of anomalous diffusion, i.e. subdiffusive behavior at short times followed by superdiffusion at intermediate times. The model results indicate that subdiffuse regime is induced by thermal fluctuations while the superdiffusive motion is generated by correlations of the motors activity. We also tested the efficiency of bidirectional cargo transport in crowded areas by measuring its ability to pass barriers with increased viscosity. Our results show a remarkable gain of efficiency for high viscosities.
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