Response rescaling in bacterial chemotaxis
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Lazova-2011-Aug-Response rescaling i.pdf
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Author(s) • • • •
Lazova, Milena D.
Ahmed, Tanvir
Bellomo, Domenico
Stocker, Roman
Shimizu, Thomas S.
Date Issued
August 2011
Journal
Proceedings of the National Academy of Sciences of the United States of America
Publisher
National Academy of Sciences (U.S.)
Citation
Lazova, M. D. et al. “Response Rescaling in Bacterial Chemotaxis.” Proceedings of the National Academy of Sciences 108.33 (2011): 13870–13875.
Version
Final published version
Abstract
Sensory systems rescale their response sensitivity upon adaptation according to simple strategies that recur in processes as diverse as single-cell signaling, neural network responses, and whole-organism perception. Here, we study response rescaling in Escherichia coli chemotaxis, where adaptation dynamically tunes the cells’ motile response during searches for nutrients. Using in vivo fluorescence resonance energy transfer (FRET) measurements on immobilized cells, we demonstrate that the design of this prokaryotic signaling network follows the fold-change detection (FCD) strategy, responding faithfully to the shape of the input profile irrespective of its absolute intensity. Using a microfluidics-based assay for free swimming cells, we confirm intensity-independent gradient responses at the behavioral level. By theoretical analysis, we identify a set of sufficient conditions for FCD in E. coli chemotaxis, which leads to the prediction that the adaptation timescale is invariant with respect to the background input level. Additional FRET experiments confirm that the adaptation timescale is invariant over an ∼10,000-fold range of background concentrations. These observations in a highly optimized bacterial system support the concept that FCD represents a robust sensing strategy for spatial searches. To our knowledge, these experiments provide a unique demonstration of FCD in any biological sensory system.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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DOI of Published Version
https://doi.org/10.1073/pnas.1108608108