Monday, March 2, 2009

Bacterial chemotaxis as a guiding line

We still lack a coherent, integrative understanding of how eukaryotes sense the properties of their environment, how they process this information, and how exactly they respond in re-organizing their cytoskeleton and thereby move in a goal-oriented way.

In contrast to that, our understanding of bacterial chemotaxis is much further advanced. We know the main players of the chemotaxis signal network, from the aspartate receptor-complex downstream to the flagella motor. One can actually compute, in a quantitative model, how a change in the extra-cellular concentration of attractant molecules eventually affects the relative fractions of clockwise and counter-clockwise rotations of the motor and thus leads to a change in the bacteria's tumble frequency. We understand how this modulated random walk brings the organism closer to the attractant.

People have also successfully simulated the effect of knocking out certain proteins in the signal pathway. One even understands how robust these biochemical signal processors are with respect to random parameter variations.

Why is it so far not possible to achieve a similar understanding of eukaryotic cell migration ? Why can't we take bacterial chemotaxis as a guiding line for developing a model ?

There are so many obvious similarities.

For example, the whole strategy for approaching the goal (attractant) is based on an internally generated random process (stochastic tumbling events in between segments of swimming along a straight line), which is only modulated by the signals of the receptor. (Note that this is in line with the recent insights how stochasticity is exploited in biochemical systems.) This search strategy seems related to the exploratory behaviour that I suggested for migrating cells in an environment with sparse adhesion opportunities and hindrances.

It has even been found that there are long-time correlations in the statistics of the tumbling intervalls. The authors have mentioned the possibility that the resulting Levy-walks might reflect an optimized search strategy.

Subsequently, other authors have tried to indentify a biochemical mechanism that might produce the necessary power-law correlations in the motor control signal.

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