Professor Richard Berry D. Phil.

Abstract:

The reliable response to weak biological signals requires that they be amplified with fidelity. In E. coli, the flagellar motors that control swimming can switch direction in response to very small changes in the concentration of the signaling protein CheY-P, but how this works is not well understood. A recently proposed allosteric model based on cooperative conformational spread in a ring of identical protomers seems promising as it is able to qualitatively reproduce switching, locked state behavior and Hill coefficient values measured for the rotary motor. In this paper we undertook a comprehensive simulation study to analyze the behavior of this model in detail and made predictions on three experimentally observable quantities: switch time distribution, locked state interval distribution, Hill coefficient of the switch response. We parameterized the model using experimental measurements, finding excellent agreement with published data on motor behavior. Analysis of the simulated switching dynamics revealed a mechanism for chemotactic ultrasensitivity, in which cooperativity is indispensable for realizing both coherent switching and effective amplification. These results showed how cells can combine elements of analog and digital control to produce switches that are simultaneously sensitive and reliable. © 2012 Ma et al.

Abstract:

Bacterial cell envelopes often contain a flagellar motor – a reversible rotary nanomachine with an approximate diameter of 45nm – that allows cells to swim. Power is provided by the movement of H+ or Na+ down the electrochemical gradients across the cytoplasmic membrane, often termed the proton motive force or sodium motive force. A helical filament is rotated by each motor at several hundred revolutions per second. In many species, the motor switches direction stochastically; switching rates are controlled by a network of sensory and signaling proteins. The first direct observation, approximately 40 years ago, of the function of a single molecular motor was of the bacterial flagellar motor. Nevertheless, due to the large size and complexity of the motor, much remains to be discovered about this nanomachine, particularly the many structural details of the torque-generating mechanism. This chapter summarizes what has been learned about the structure and function of the motor with a focus on recent observations, particularly those obtained using single molecule techniques.

Abstract:

We report statistical time-series analysis tools providing improvements in the rapid, precision extraction of discrete state dynamics from time traces of experimental observations of molecular machines. By building physical knowledge and statistical innovations into analysis tools, we provide techniques for estimating discrete state transitions buried in highly correlated molecular noise. We demonstrate the effectiveness of our approach on simulated and real examples of steplike rotation of the bacterial flagellar motor and the F1-ATPase enzyme. We show that our method can clearly identify molecular steps, periodicities and cascaded processes that are too weak for existing algorithms to detect, and can do so much faster than existing algorithms. Our techniques represent a step in the direction toward automated analysis of high-sample-rate, molecular-machine dynamics. Modular, open-source software that implements these techniques is provided. © 2011 Biophysical Society.