Abstract
Molecular motor proteins fulfill the critical function of transporting organelles and other building blocks along the biopolymer network of the cell’s cytoskeleton, but crowding effects are believed to crucially affect this motor-driven transport due to motor interactions. Physical transport models, like the paradigmatic, totally asymmetric simple exclusion process (TASEP), have been used to predict these crowding effects based on simple exclusion interactions, but verifying them in experiments remains challenging. Here, we introduce a correlation imaging technique to precisely measure the motor density, velocity, and run length along filaments under crowding conditions, enabling us to elucidate the physical nature of crowding and test TASEP model predictions. Using the kinesin motor proteins kinesin-1 and OSM-3, we identify crowding effects in qualitative agreement with TASEP predictions, and we achieve excellent quantitative agreement by extending the model with motor-specific interaction ranges and crowding-dependent detachment probabilities. These results confirm the applicability of basic nonequilibrium models to the intracellular transport and highlight motor-specific strategies to deal with crowding.
- Received 20 March 2017
DOI:https://doi.org/10.1103/PhysRevX.7.041037
Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.
Published by the American Physical Society
Physics Subject Headings (PhySH)
Popular Summary
Molecular motor proteins drive essential transport processes in cells by carrying cargo while walking along the cytoskeleton, the skeleton of a cell. Just like traffic jams affect traffic on crowded roads, similar effects are believed to affect the motion of these dense motor proteins. But how crowding effects hamper the transport—and how motor proteins deal with it—remains a mystery. Physical transport models have been used to describe this collective motion using simple interacting particles, but it is not clear how well these models describe real motor protein transport. This is because imaging of the molecular motors is difficult in the most relevant regime: at high density, where the motors can no longer be optically resolved. Using new imaging techniques, we present new insight into motor protein traffic.
By using a novel correlation technique to analyze image sequences, we accurately measure motor velocities and run lengths at high motor densities, allowing us to quantitatively assess jamming effects in motor protein transport. We confirm the general predictions of a common physical transport model but find that motors have their own specific interaction ranges and detachment kinetics. By comparing experimental results with model predictions for two types of motors from the kinesin family, we arrive at a clear understanding of the collective motor protein transport under crowding, governed by motor-specific strategies.
Our experiments were performed in a controlled environment (in vitro), so it will be interesting to see how these properties carry over to a live cell (in vivo), where additional environmental interactions might affect jamming behavior.