To refer to this page use:
|Abstract:||Myxococcus xanthus is a model organism for studying bacterial social behaviors due to its ability to form complex multi-cellular structures. Knowledge of M. xanthus surface gliding motility and the mechanisms that coordinated it are critically important to our understanding of collective cell behaviors. Although the mechanism of gliding motility is still under investigation, recent experiments suggest that there are two possible mechanisms underlying force production for cell motility: the focal adhesion mechanism and the helical rotor mechanism, which differ in the biophysics of the cell–substrate interactions. Whereas the focal adhesion model predicts an elastic coupling, the helical rotor model predicts a viscous coupling. Using a combination of computational modeling, imaging, and force microscopy, we find evidence for elastic coupling in support of the focal adhesion model. Using a biophysical model of the M. xanthus cell, we investigated how the mechanical interactions between cells are affected by interactions with the substrate. Comparison of modeling results with experimental data for cell-cell collision events pointed to a strong, elastic attachment between the cell and substrate. These results are robust to variations in the mechanical and geometrical parameters of the model. We then directly measured the motor-substrate coupling by monitoring the motion of optically trapped beads and find that motor velocity decreases exponentially with opposing load. At high loads, motor velocity approaches zero velocity asymptotically and motors remain bound to beads indicating a strong, elastic attachment.|
|Electronic Publication Date:||8-May-2014|
|Citation:||Balagam, Rajesh, Litwin, Douglas B, Czerwinski, Fabian, Sun, Mingzhai, Kaplan, Heidi B, Shaevitz, Joshua W, Igoshin, Oleg A. (2014). Myxococcus xanthus Gliding Motors Are Elastically Coupled to the Substrate as Predicted by the Focal Adhesion Model of Gliding Motility. PLoS Computational Biology, 10 (5), e1003619 - e1003619. doi:10.1371/journal.pcbi.1003619|
|Pages:||e1003619 - e1003619|
|Type of Material:||Journal Article|
|Journal/Proceeding Title:||PLoS Computational Biology|
Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.