Properties of sodium-driven bacterial flagellar motor: A two-state model approach

Abstract

Bacterial flagellar motor (BFM) is one of the ion-driven molecular machines, which drives the rotation of flagellar filaments and enable bacteria to swim in viscous solutions. Understanding its mechanism is one challenge in biophysics. Based on previous models and inspired by the idea used in description of motor proteins, in this study one two-state model is provided. Meanwhile, according to corresponding experimental data, mathematical relationship between BFM membrane voltage and pH value of the environment, and relationship between internal and external sodium concentrations are given. Therefore, with model parameter values obtained by fitting theoretical results of torque-speed relation to recent experimental data, many biophysical properties of bacterial flagellar motor can be obtained for any pH values and any external sodium concentrations. Including the rotation speed, stall torque (i.e. the torque generated by BFM), rotation dispersion, and rotation randomness. In this study, the single-stator BFM will be firstly analyzed, and then properties of multiple-stator BFM are addressed briefly.

References in corpus (11)

• Tug-of-war as a cooperative mechanism for bidirectional cargo transport by molecular motors
• Channel-Facilitated Molecular Transport Across Membranes: Attraction, Repulsion and Asymmetry
• Effects of multiple occupancy and inter-particle interactions on selective transport through narrow channels: theory versus experiment
• Dynamics of the bacterial flagellar motor with multiple stators
• Coupling between switching regulation and torque generation in bacterial flagellar motor
• Modeling torque versus speed, shot noise, and rotational diffusion of the bacterial flagellar motor
• The efficiency of the molecular motors
• Properties of tug-of-war model for cargo transport by molecular motors
• Effect of Interactions on Molecular Fluxes and Fluctuations in the Transport Across Membrane Channels
• A general two-cycle network model of molecular motors
• Growth and shortening of microtubules: a two-state model approach