Dennis Bray1, Matthew D Levin, Karen Lipkow. 1. Department of Physiology, Development, and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, United Kingdom. db10009@cam.ac.uk
Abstract
BACKGROUND: Chemotaxis is the process by which organisms migrate toward nutrients and favorable environments and away from toxins and unfavorable environments. In many species of bacteria, this occurs when extracellular signals are detected by transmembrane receptors and relayed to flagellar motors, which control the cell's swimming behavior. RESULTS: We used a molecularly detailed reaction-kinetics model of the chemotaxis pathway in Escherichia coli coupled to a graphical display based on known swimming parameters to simulate the responses of bacteria to 2D gradients of attractants. The program gives the correct phenotype of over 60 mutants in which chemotaxis-pathway components are deleted or overexpressed and accurately reproduces the responses to pulses and step increases of attractant. In order to match the known sensitivity of bacteria to low concentrations of attractant, we had to introduce a set of "infectivity" reactions based on cooperative interactions between neighboring chemotaxis receptors in the membrane. In order to match the impulse response to a brief stimulus and to achieve an effective accumulation in a gradient, we also had to increase the activities of the adaptational enzymes CheR and CheB at least an order of magnitude greater than published values. Our simulations reveal that cells develop characteristic levels of receptor methylation and swimming behavior at different positions along a gradient. They also predict a distinctive "volcano" profile in some gradients, with peaks of cell density at intermediate concentrations of attractant. CONCLUSIONS: Our results display the potential use of computer-based bacteria as experimental objects for exploring subtleties of chemotactic behavior.
BACKGROUND: Chemotaxis is the process by which organisms migrate toward nutrients and favorable environments and away from toxins and unfavorable environments. In many species of bacteria, this occurs when extracellular signals are detected by transmembrane receptors and relayed to flagellar motors, which control the cell's swimming behavior. RESULTS: We used a molecularly detailed reaction-kinetics model of the chemotaxis pathway in Escherichia coli coupled to a graphical display based on known swimming parameters to simulate the responses of bacteria to 2D gradients of attractants. The program gives the correct phenotype of over 60 mutants in which chemotaxis-pathway components are deleted or overexpressed and accurately reproduces the responses to pulses and step increases of attractant. In order to match the known sensitivity of bacteria to low concentrations of attractant, we had to introduce a set of "infectivity" reactions based on cooperative interactions between neighboring chemotaxis receptors in the membrane. In order to match the impulse response to a brief stimulus and to achieve an effective accumulation in a gradient, we also had to increase the activities of the adaptational enzymes CheR and CheB at least an order of magnitude greater than published values. Our simulations reveal that cells develop characteristic levels of receptor methylation and swimming behavior at different positions along a gradient. They also predict a distinctive "volcano" profile in some gradients, with peaks of cell density at intermediate concentrations of attractant. CONCLUSIONS: Our results display the potential use of computer-based bacteria as experimental objects for exploring subtleties of chemotactic behavior.