Exponential signaling gain at the receptor level enhances signal-to-noise ratio in bacterial chemotaxis

Silke Neumann, Linda Lovdok, Kajetan Bentele, Johannes Meisig, Ekkehard Ullner, Ferencz S Paldy, Victor Sourjik, Markus Kollmann*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
10 Downloads (Pure)

Abstract

Cellular signaling systems show astonishing precision in their response to external stimuli despite strong fluctuations in the molecular components that determine pathway activity. To control the effects of noise on signaling most efficiently, living cells employ compensatory mechanisms that reach from simple negative feedback loops to robustly designed signaling architectures. Here, we report on a novel control mechanism that allows living cells to keep precision in their signaling characteristics - stationary pathway output, response amplitude, and relaxation time - in the presence of strong intracellular perturbations. The concept relies on the surprising fact that for systems showing perfect adaptation an exponential signal amplification at the receptor level suffices to eliminate slowly varying multiplicative noise. To show this mechanism at work in living systems, we quantified the response dynamics of the E. coli chemotaxis network after genetically perturbing the information flux between upstream and downstream signaling components. We give strong evidence that this signaling system results in dynamic invariance of the activated response regulator against multiplicative intracellular noise. We further demonstrate that for environmental conditions, for which precision in chemosensing is crucial, the invariant response behavior results in highest chemotactic efficiency. Our results resolve several puzzling features of the chemotaxis pathway that are widely conserved across prokaryotes but so far could not be attributed any functional role.

Original languageEnglish
Article numbere87815
Number of pages11
JournalPloS ONE
Volume9
Issue number4
DOIs
Publication statusPublished - 15 Apr 2014

Keywords

  • stochastic gene-expression
  • Escherichia-coli
  • chemoreceptor clusters
  • single-cell
  • adaptation
  • robustness
  • network
  • binding
  • chea
  • components

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