Background Intracellular transport requires molecular motors that step along cytoskeletal filaments actively dragging cargoes through the crowded cytoplasm. Here, we explore the interplay of the opposed polarity motors kinesin-1 and cytoplasmic dynein during peroxisome transport along microtubules in Drosophila S2 cells. Methods We used single particle tracking with nanometer accuracy and millisecond time resolution to extract quantitative information on the bidirectional motion of organelles. The transport performance was studied in cells expressing a slow chimeric plus-end directed motor or the kinesin heavy chain. We also analyzed the influence of peroxisomes membrane fluidity in methyl-β-ciclodextrin treated cells. The experimental data was also confronted with numerical simulations of two well-established tug of war scenarios. Results and conclusions The velocity distributions of retrograde and anterograde peroxisomes showed a multi-modal pattern suggesting that multiple motor teams drive transport in either direction. The chimeric motors interfered with the performance of anterograde transport and also reduced the speed of the slowest retrograde team. In addition, increasing the fluidity of peroxisomes membrane decreased the speed of the slowest ante-rograde and retrograde teams. General significance Our results support the existence of a crosstalk between opposed-polarity motor teams. Moreover, the slowest teams seem to mechanically communicate with each other through the membrane to trigger transport.

Intracellular transport is propelled by kinesin and cytoplasmic dynein motors that carry membrane-bound vesicles and organelles bidirectionally along microtubule tracks. Much is known about these motors at the molecular scale, but many questions remain regarding how kinesin and dynein cooperate and compete during bidirectional cargo transport at the cellular level. The goal of the present study was to use a stochastic stepping model constructed by using published load-dependent properties of kinesin-1 and dynein-dynactin-BicD2 (DDB) to identify specific motor properties that determine the speed, directionality, and transport dynamics of a cargo carried by one kinesin and one dynein motor. Model performance was evaluated by comparing simulations to recently published experiments of kinesin-DDB pairs connected by complementary oligonucleotide linkers. Plotting the instantaneous velocity distributions from kinesin-DDB experiments revealed a single peak centered around zero velocity. In contrast, velocity distributions from simulations displayed a central peak around 100 nm/s, along with two side peaks corresponding to the unloaded kinesin and DDB velocities. We hypothesized that frequent motor detachment events and relatively slow motor reattachment rates resulted in periods in which only one motor is attached. To investigate this hypothesis, we varied specific model parameters and compared the resulting instantaneous velocity distributions, and we confirmed this systematic investigation using a machine learning approach that minimized the residual sum of squares between the experimental and simulation velocity distributions. The experimental data were best recapitulated by a model in which the kinesin and dynein stall forces are matched, motor detachment rates are independent of load, and the kinesin-1 reattachment rate is 50 s-1. These results provide new insights into motor dynamics during bidirectional transport and put forth hypotheses that can be tested by future experiments. Statement of significance: Bidirectional transport of vesicles along microtubules is vital for cellular function, particularly in the highly elongated axons and dendrites of neurons, and transport defects are linked to neurodegenerative diseases. For developing future therapeutic strategies, a better understanding is needed for how motors, cargo adapters, and accessory proteins coordinate their activities to transport cargo to their proper cellular locations. We approached this problem by simulating how antagonistic kinesin and dynein motors compete in pairs. We constrain our simulations by recent experimental results and conclude that the motors spend nearly all their time attached to the microtubule and competing against one another. This behavior is not predicted by existing single-molecule experiments and thus provides new insights into bidirectional transport.

The transport of intracellular organelles is accomplished by groups of molecular motors, such as kinesin, myosin, and dynein. Previous studies have demonstrated that the cooperation between kinesins on a track is beneficial for long transport. However, within crowded three-dimensional (3D) cytoskeletal networks, surplus motors could impair transport and lead to traffic jams of cargos. Comprehensive understanding of the effects of the interactions among molecular motors, cargo, and tracks on the 3D cargo transport dynamics is still lack. In this work, a 3D stochastic multiphysics model is introduced to study the synergistic and antagonistic motions of kinesin motors walking on multiple mircotubules (MTs). Based on the model, we show that kinesins attaching to a common cargo can interact mechanically through the transient forces in their cargo linkers. Under different environmental conditions, such as different MT topologies and kinesin concentrations, the transient forces in the kinesins, the stepping frequency and the binding and unbinding probabilities of kinesins are changed substantially. Therefore, the macroscopic transport properties, specifically the stall force of the cargo, the transport direction at track intersections, and the mean-square displacement (MSD) of the cargo along the MT bundles vary over the environmental conditions. In general, conditions that improve the synergistic motion of kinesins increase the stall force of the cargo and the capability of maintaining the transport. In contrast, the antagonistic motion of kinesins temporarily traps the cargo and slows down the transport. Furthermore, this study predicts an optimal number of kinesins for the cargo transport at MT intersections and along MT bundles.