Abstract
Berg and Purcell [Biophys. J. 20, 193 (1977)] calculated how the accuracy of concentration sensing by single-celled organisms is limited by noise from the small number of counted molecules. Here we generalize their results to the sensing of concentration ramps, which is often the biologically relevant situation (e.g., during bacterial chemotaxis). We calculate lower bounds on the uncertainty of ramp sensing by three measurement devices: a single receptor, an absorbing sphere, and a monitoring sphere. We contrast two strategies, simple linear regression of the input signal versus maximum likelihood estimation, and show that the latter can be twice as accurate as the former. Finally, we consider biological implementations of these two strategies, and identify possible signatures that maximum likelihood estimation is implemented by real biological systems.
- Received 19 February 2010
DOI:https://doi.org/10.1103/PhysRevLett.104.248101
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Viewpoint
ViewpointImproving accuracy by leaps and unbounds
Published 14 June 2010
New analyses suggest strategies by which biological sensors may be able to measure changes in concentrations of chemical signaling molecules more accurately, but does this reflect what actually happens in nature?
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