Abstract

Mechanosensing is a key feature through which organisms can receive inputs from the environment and convert them into specific functional and behavioral outputs. Mechanosensation occurs in many cells and tissues, regulating a plethora of molecular processes based on the distribution of forces and stresses both at the cell membrane and at the intracellular organelles levels, through complex interactions between cells’ microstructures, cytoskeleton, and extracellular matrix. Although several primary and secondary mechanisms have been shown to contribute to mechanosensation, a fundamental pathway in simple organisms and mammals involves the presence of specialized sensory neurons and the presence of different types of mechanosensitive ion channels on the neuronal cell membrane. In this contribution, we present a review of the main ion channels which have been proven to be significantly involved in mechanotransduction in neurons. Further, we discuss recent studies focused on the biological mechanisms and modeling of mechanosensitive ion channels’ gating, and on mechanotransduction modeling at different scales and levels of details.

Highlights

  • Mechanosensation is among the most important sensory functions in animals

  • The main pathway through which organisms achieve mechanosensing accounts for specialized sensory neurons opportunely enriched with mechano-electrical transduction (MeT) complexes and interfaced with different types of biological structures

  • We briefly describe the MS ion channels that have been identified in the literature, with a particular focus on their functions in mechanosensory neurons

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Summary

A Review

Nonlinear Physics and Mathematical Models Research Unit, Engineering Department, Campus Bio-Medico.

Introduction
Ion Channels in Neurons Mechanosensing
Anoctamin Superfamily
TRP Superfamily
Other Mechano-Gated Proteins and Channels
Modeling
Continuum Modeling of Ion Channel Mechanosensing—Eulerian Description
Multiscale Mechano-Electrical Modeling
Discussion and Conclusions
Findings
Methods
Full Text
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