Protein gradients and clustering dynamics in bacterial chemotaxis
The chemotaxis pathway of Escherichia coli, which enables the bacterium to swim to
the
most beneficial environment, is the best-understood to date. Signals from the
environment are detected by transmembrane receptor-kinase complexes, which are
mostly
clustered at the cell pole, and then transmitted to the randomly positioned
flagellar
motors by diffusion of the phosphorylated CheYp protein. A component of the
pathway
which promotes dephosphorylation of CheYp, the protein CheZ, has been shown by
fluorescent methods to be distributed between the cytoplasm and the receptor
cluster.
With the aid of a computer program that can simulate the movement and interaction
of a
large number of individual molecules in a structured environment (Andrews & Bray,
Phys.
Biol., 2004), we constructed a three-dimensional model of an E. coli cell. We
examined
the generation and diffusion of CheYp through the cell under control conditions
and in
response to attractant and repellent stimuli. The results agree well with
experimental
observations but allow an analysis at much higher detail, such as the calculation
of
diffusion traces and lifetimes of individual molecules. Exploring the effects of
cellular architecture, macromolecular crowding and positioning of the CheZ
phosphatase,
we identified conditions for the formation of gradients of phosphorylated CheY
(Lipkow
et al., J. Bacteriol., 2005).
Supported by analytical methods and simulations, we demonstrate that intracellular
gradients can have an unexpectedly complicated form. This will occur, for example,
if
one of the phospho-states binds to a large or immobile structure and needs to be
taken
into account when measuring gradients experimentally, for example via FRET probes.
We
present a model in which CheZ dynamically changes location and self-organises into
oligomeric clusters of higher activity at the pole depending on stimulus level.
Our
simulations suggest that the changing location of CheZ will sharpen responses of
the
cell, make adaptation more precise, and increase the range of detectable ligand
concentrations. They introduce an unprecedented level of sophistication into what
is
usually considered a simple signalling pathway.
Vincent Moulton
© 2005, CBL
Computational Biology Laboratory,
School of Computing Sciences,
University of East Anglia,
Norwich, NR4 7TJ, UK.