We're all familiar with the behaviour of objects at everyday sizes: if they are heavy, they stay put due to friction, and it's difficult to get them to move anywhere quickly unless you use a lot of force. If instead they are very light, then they can get smoothly carried around on air currents like a feather. That's just a couple of intuitive analogies that don't work at all at the molecular scale! Down inside the workings of cells, at the scale of molecules, everything is constantly buzzing around due to thermal effects and collisions with other molecules scramble up the motion. So simply scaling down our everyday machines might not be the best way to function in this noisy environment. Yet, life is not just a mash of molecules: there are exquisite mechanisms inside cells for doing things (fairly) reliably and repeatably. This includes the rather amazing bacterial flagellar rotary motor that cells use to propel themselves towards their food (fun cartoon of its assembly). It has long been hypothesised that the motor action has to be made in lots of tiny little steps, because this is the only way for a molecular scale machine to efficiently use the available (free) energy to work against the thermal noise that wants to dissipate any organized motion.Biological physicists (like Richard Berry and his team) are intently interested in understanding exactly how this stepping motor works, and they have recently been able to develop the instrumentation to start answering these kinds of questions. Our group is interested in how life deals with fluctuations so we were very interested in their work. Note that you can't use microscopy techniques like conventional electron microscopy, because you have to kill the cell in order to image it. Then you have no chance of seeing the motor in action.
Because of the jostling microscopic environment the data produced by these new systems can be very noisy. We developed statistical methods that tried to separate out the physics we did know (aspects of mechanics and thermal noise) from the biological physics we didn't (how the motors actually steps between successive molecular configurations). This is where statistical modelling comes in: it turns out that the problem of separating step-like motion from the noise in the data so you can image the step-like motion is difficult unless you invoke non-traditional signal processing methods. You also need to take account of the experimental apparatus that introduces some unavoidable lag into the system (Richard's team attaches a tiny bead to the flagellum and tracks this bead). In our soon-to-be-published Biophysical Journal paper "Steps and bumps: precision extraction of discrete states of molecular machines using physically-based, high-throughput time series analysis" (you'll find a pre-print on our publications page), we also introduced a novel technique based on a kind of probabilistic periodicity detection, for teasing out the cylindrical arrangement of proteins that make up the main structure of the motor, which gives the motor a characteristic set of "dance steps". Max and Nick
