Principles of slowed hydrogen diffusion through a mucus layer

Owen L. Lewis, Ella Missey, and James P. Keener
Phys. Rev. E 104, 044403 – Published 6 October 2021

Abstract

The control of transport through mucus layers is a ubiquitous phenomenon in physiological systems. Mucus is often tasked with the mediation of passive, diffusive transport of small ionic species. However, questions remain regarding how mucin gel characteristics (charge density of the polymeric network, binding affinity of ions with mucus) govern the rate at which ions diffuse through mucus layers. Experimental studies measuring hydrogen diffusion through gastric mucus have provided conflicting results, and it is not clear if the rate of ionic diffusion through mucus layers is appreciably different than in aqueous environments (depending on experimental preparation). Here, we present a mathematical analysis of electrodiffussion of two ionic species (hydrogen and chloride) through a mucus layer. In addition to accounting for the chemical binding of hydrogen to the mucus network, we enforce a zero net current condition (as mucus layers in physiological systems are not generally electrogenic) and calculate the Donnan potential that occurs at the edge of the mucus layer. The model predicts the steady-state fluxes of ionic species and the induced potential across the layer. We characterize the dependence of these quantities on the chemical properties of the mucus gel, the composition of the bath solution, and the molecular mobility of the dissolved anion, and we show that the model predictions are consistent with a large portion of the experimental literature. Our analysis predicts that mucus layers generically slow the diffusive transport of hydrogen, but that chemical binding with the network attenuates this effect.

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  • Received 9 March 2021
  • Accepted 13 September 2021

DOI:https://doi.org/10.1103/PhysRevE.104.044403

©2021 American Physical Society

Physics Subject Headings (PhySH)

Physics of Living SystemsGeneral Physics

Authors & Affiliations

Owen L. Lewis*

  • Department of Mathematics and Statistics, University of New Mexico, Albuquerque, New Mexico 87131, USA

Ella Missey

  • Department of Mathematics, Florida State University, Tallahassee, Florida 32306, USA

James P. Keener

  • Department of Mathematics, University of Utah, Salt Lake City, Utah 84112, USA

  • *owenlewis@unm.edu
  • Present address: Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306, USA.
  • Also at Department of Bioengineering, University of Utah, Salt Lake City, Utah 84112, USA.

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Issue

Vol. 104, Iss. 4 — October 2021

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