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Nonadaptive Fluctuation in an Adaptive Sensory System: Bacterial Chemoreceptor

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  • Masatoshi Nishikawa
  • Tatsuo Shibata

Abstract

Background: Sensory systems often exhibit an adaptation or desensitization after a transient response, making the system ready to receive a new signal over a wide range of backgrounds. Because of the strong influence of thermal stochastic fluctuations on the biomolecules responsible for the adaptation, such as many membrane receptors and channels, their response is inherently noisy, and the adaptive property is achieved as a statistical average. Methodology/Principal Findings: Here, we study a simple kinetic model characterizing the essential aspects of these adaptive molecular systems and show theoretically that, while such an adaptive sensory system exhibits a perfect adaptation property on average, its temporal stochastic fluctuations are able to be sensitive to the environmental conditions. Among the adaptive sensory systems, an extensively studied model system is the bacterial receptor responsible for chemotaxis. The model exhibits a nonadaptive fluctuation sensitive to the environmental ligand concentration, while perfect adaptation is achieved on average. Furthermore, we found that such nonadaptive fluctuation makes the bacterial behavior dependent on the environmental chemoattractant concentrations, which enhances the chemotactic performance. Conclusions/Significance: This result indicates that adaptive sensory systems can make use of such stochastic fluctuation to carry environmental information, which is not possible by means of the average, while keeping responsive to the changing stimulus.

Suggested Citation

  • Masatoshi Nishikawa & Tatsuo Shibata, 2010. "Nonadaptive Fluctuation in an Adaptive Sensory System: Bacterial Chemoreceptor," PLOS ONE, Public Library of Science, vol. 5(6), pages 1-12, June.
  • Handle: RePEc:plo:pone00:0011224
    DOI: 10.1371/journal.pone.0011224
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    References listed on IDEAS

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    1. N. Barkai & S. Leibler, 1997. "Robustness in simple biochemical networks," Nature, Nature, vol. 387(6636), pages 913-917, June.
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