Bacterial chemotaxis: from information processing to behaviour

Abstract

Chemotaxis allows flagellated bacteria to navigate in complex chemical environments, following nutrients and escaping toxins. The sensory system made up of chemoreceptors is constantly monitoring the extracellular concentrations of nutrients and toxins, while the signalling pathway processes and transmits the external information to the flagellated motors for movement. In the case of Escherichia coli, the chemotaxis pathway has been extensively characterised experimentally using genetics, biochemistry, and a wide range of imaging tools. This makes E. coli an ideal model organism for quantitative analysis and modelling. Several remarkable properties of the E. coli chemotaxis pathway have been summarised in terms of design principles. However, the swimming behaviour remains poorly understood, even for genetically identical cells in the artificial conditions normally used in a laboratory. Here, I propose an interdisciplinary approach, which combines theory, computational simulations, and experimental data from my collaborators, to study E. coli chemotaxis from an information-theoretic point of view. I demonstrate that the E. coli chemotaxis pathway is designed to optimally transmit environmental information over a certain range of concentrations and gradients. To do so, I develop a theory that identifies both the responses and the environmental conditions that transmit maximal environmental in- formation. Interestingly, when maximal information is transmitted, the behaviour characterised in terms of the drift velocity towards the nutrient is also maximised. A new design principle is proposed: maximal information transmission leads to maximal drift. Furthermore, the energetic cost of chemotaxis is much lower than the energy consumed to maintain the biological signalling pathway. Hence, thermodynamics does not seem to set constraints on information transmission and drift. However, to fully capitalise on my results, a closer connection with single-cell experiments is suggested.