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Gradient sensing via cell communication.

Dallas Foster1, Brian Frost-LaPlante2, Collin Victor3

  • 1Department of Mathematics, Oregon State University, Corvallis, Oregon 97331, USA.

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|March 19, 2021
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Summary
This summary is machine-generated.

Cell-to-cell communication is crucial for gradient sensing. This study generalizes a model to show how communication details, cell size, and noise impact sensing precision, offering insights for biological systems.

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Area of Science:

  • Biophysics
  • Cell Biology
  • Systems Biology

Background:

  • Cell-to-cell communication is hypothesized to be important for gradient sensing.
  • Existing models, like the local excitation, global inhibition (LEGI) model, explore this in simplified systems.

Purpose of the Study:

  • To generalize the LEGI model's communication mechanism.
  • To investigate how gradient sensing depends on communication parameters, cell size, neighbor influence, and noise.

Main Methods:

  • Generalization of the nearest-neighbor communication in the LEGI model.
  • Analysis of various candidate communication models.
  • Derivation of physical and analytical explanations for observed phenomena.

Main Results:

  • Gradient sensing precision is sensitive to the specific cell-to-cell communication model used.
  • The study quantifies the impact of communication parametrization, cell size, and noise on sensing accuracy.

Conclusions:

  • The findings highlight the critical role of communication model choice in gradient sensing.
  • The established framework aids in selecting appropriate models for studying cell communication and sensing.