We show how the competition between sensing and adaptation can result in a performance peak in E.coli chemotaxis using extensive numerical simulations in a detailed theoretical model. Receptor clustering amplifies the input signal coming from ligand binding which enhances chemotactic efficiency. However, large clusters also induce large fluctuations in the activity which causes adaptation to take over . The activity , and hence the run-tumble motility now gets controlled by methylation levels which are part of adaptation module, rather than ligand binding. This reduces chemotactic efficiency.
We show how the competition between sensing and adaptation can result in a performance peak in E.coli chemotaxis using extensive numerical simulations in a detailed theoretical model. Receptor clustering amplifies the input signal coming from ligand binding which enhances chemotactic efficiency. But large clusters also induce large fluctuations in total activity since the number of clusters go down . The activity and hence the run-tumble motility now gets controlled by methylation levels which are part of adaptation module, rather than ligand binding. This reduces chemotactic efficiency.
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the activity which causes adaptation to take over
total activity since the number of clusters go down
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