Problem Set 6
1. You
should read the classic paper by Berg and Purcell:
Physics of
chemoreception. HC Berg &
EM Purcell, Biophys J 20, 93-219 (1977).
As much as possible, try to follow the
mathematical derivations. If there
are places where you get stuck, make notes and bring these to the discussion on
Thursday.
- To
help you understand some of what is going on in Berg & Purcell, you
should do a small simulation of diffusion. Start in one dimension, and imagine a particle that can
sit at (for example) 1000 different points along a line. At each time step, flip a coin and
decide whether the particle moves to the right or the left; to avoid
trouble with the particle leaving the region you are studying, you can
wrap the line into a ring, so that if the particle at site number 1000 and
tries to move right, it goes to site 1. You should be able to do this in a few lines of MATLAB
code. Before running the
code, what is the mean displacement across one time step? What is the mean square
displacement across on time step?
Now run the code, say for tens of thousands of time steps. The result should be a trajectory
x(t). Plot this result. To analyze it, collect �data� on
how much the particle moves over a time t -> t+ T. Show that the distribution of
displacements starts t look Gaussian when T becomes large, and that the
variance of this Gaussian is growing linearly with T, as expected for
diffusion.
- Generalize
this calculation (1 particle with 1000 sites) to have, say 100 particles
and 10,000 sites; assume that particles are completely independent of each
other, even if they land on the same site. Suppose that all the particles start at the same
site. As your simulation
progresses, they disperse, corresponding to the fact that concentration
gradients relax via diffusion.
Suppose you summarize the state of the system at time t by
computing the variance in position of all the particles; how does this
variance change with time?
What does the distribution of particle positions look like? Can you show that, although the
variance is changing, the shape of the distribution (suitably normalized)
is not? What is this shape?
How many time steps do you need before the distribution of particles
starts to look uniform along the line? Does this make sense given what you know about
diffusion? Once the distribution looks uniform, suppose you count the
number of molecules in a window of 100 sites. What is the average of this number (you should be able
to answer that without looking at the data!)? What is the variance in this number? Since you have many samples, you
should be able to estimate the full probability distribution for this
molecule count. Plot your
result and see if you can fit it to the Poisson distribution.
- Go
back to having just one particle, but now allow for motion in three
dimensions (it takes some thought to see how to set this up). For example,
let the particle move in a box that is 10x10x10 sites in size, and at each
moment you flip independent coins to decide if the x, y, and z coordinates
should increase or decrease by one unit; as before you need to wrap the
edges around, so that if you are at position 10 and try to increase the
coordinate by one you go to position 1. Let your one particle start at some random position,
and ask how long it takes before it hits one particular site that you
choose—the site where some chemical reaction might happen. Suppose you do this experiment
many times, and measure each time how long it takes to hit the chosen
site. What is the
distribution of these times?
What happens when you make the box bigger (e.g., 20x20x20
sites)? What if you make the
site you have to hit bigger, say consisting of a 2x2x2 box, such that you declare
a �hit� if the particle enters any of these 8 sites? Explain how these simulations relate
to the idea of diffusion limited reaction rates.
- If
you look at your simulations in (4), you�ll see that the distribution of
times required to hit the site is broad, but well behaved. Repeat the same simulation in one
dimension (back to the line of 1000 sites). What does the distribution look like now? You might need to do the
simulation many times in order to get a convincing answer. Hopefully you�ll see that one
dimension is different from three!
As an aside, you will note that Berg and Purcell
provide an interesting mixture of intuitive and mathematical arguments, often
sliding (perhaps suspiciously!) from one qualitative picture to another. Some of you might wish that things
could be made more precise. This
turns out to be a bit of work, but it is kind of fun, and shows that what Berg
and Purcell did was really much more general than one might have thought.
Physical
limits to biochemical signaling. W Bialek & S Setayeshgar, Proc Nat�l
Acad Sci (USA) 102, 10040-10045 (2005).