In silico evolution of chemotaxis

Richard Goldstein, National Institute for Medical Research (NIMR), London, United Kingdom
Tuesday 24 March, Location: MRC-LMCB, time: 16:30

Chemotaxis in E. coli is one of the best-studied examples of how biochemical networks can mediate behaviour. As we gradually learn more about chemotaxis in other organisms, we find that there is a wide variety of different mechanisms and strategies in use,  including some very different from that in E. coli. We are interested in why different bacteria have evolved different solutions to this problem, how the choice is influenced by the conditions in which these organisms evolved, and how these different solutions might be implemented. Unfortunately it is difficult to answer 'what if' questions about evolution - there are many practical obstacles to changing historical conditions. 
Alternatively, we can create artificial systems that evolve in a manner characteristic of natural living systems, either experimentally or in silico. In order to understand the relationship between conditions and resulting chemotactic strategies, we simulated the evolution of chemotaxis in digital organisms. This approach starts with a population of virtual bacteria that move in a virtual environment based on the dynamics of the simple biochemical pathways they harbour. As mutations lead to changes in pathway structure and dynamics, bacteria better ability to localise with favourable conditions gain a selective advantage. We find that a certain dynamics evolves consistently under different model assumptions and environments. These dynamics, which we call non-adaptive dynamics, directly couple tumbling probability of the cell to increasing stimuli. The non-adaptive dynamics mediating taxis responses provide an explanation for experimental observations made in mutant strains of E. coli and in wild type Rhodobacter sphaeroides that could not be explained with standard models. We speculate that such dynamics exist in other bacteria as well and play a role linking the metabolic state of the cell and the taxis response.

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Goldstein poster

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