Cellular information dynamics through transmembrane flow of ions View Full Text


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Article Info

DATE

2017-12

AUTHORS

Robert A. Gatenby, B. Roy Frieden

ABSTRACT

We propose cells generate large transmembrane ion gradients to form information circuits that detect, process, and respond to environmental perturbations or signals. In this model, the specialized gates of transmembrane ion channels function as information detectors that communicate to the cell through rapid and (usually) local pulses of ions. Information in the ion "puffs" is received and processed by the cell through resulting changes in charge density and/or mobile cation (and/or anion) concentrations alter the localization and function of peripheral membrane proteins. The subsequent changes in protein binding to the membrane or activation of K+, Ca2+ or Mg2+-dependent enzymes then constitute a cellular response to the perturbation. To test this hypothesis we analyzed ion-based signal transmission as a communication channel operating with coded inputs and decoded outputs. By minimizing the Kullback-Leibler cross entropy [Formula: see text] between concentrations of the ion species inside [Formula: see text] and outside [Formula: see text] the cell membrane, we find signal transmission through transmembrane ion flow forms an optimal Shannon information channel that minimizes information loss and maximizes transmission speed. We demonstrate the ion dynamics in neuronal action potentials described by Hodgkin and Huxley (including the equations themselves) represent a special case of these general information principles. More... »

PAGES

15075

References to SciGraph publications

  • 1990-04. Channels as enzymes in THE JOURNAL OF MEMBRANE BIOLOGY
  • 2013-04. The Critical Roles of Information and Nonequilibrium Thermodynamics in Evolution of Living Systems in BULLETIN OF MATHEMATICAL BIOLOGY
  • 2007-02. Information Theory in Living Systems, Methods, Applications, and Challenges in BULLETIN OF MATHEMATICAL BIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41598-017-15182-2

    DOI

    http://dx.doi.org/10.1038/s41598-017-15182-2

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1092504167

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/29118414


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