# Modeling gastric mucus layer physiology

> **NIH NIH R01** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2020 · $365,725

## Abstract

This proposal brings together a team of applied mathematicians and experimental physicists, engineers,
and biologists, with expertise in biogels, mucus physics, microbiology and bacterial motility, and
gastroenterology to tackle an important problem in physiology and pathology: how the gastric mucus layer
is maintained and how it responds to infecting bacteria and to changes in topology and size in gastric
organoids (GOs). Cells in the stomach epithelium secrete the mucin that forms a mucus layer to protect the
epithelium from the harsh environment of the stomach lumen, which is acidic and contains digestive
enzymes such as pepsin. Epithelial cells also secrete acid, neutralizing bicarbonate, and pepsinogen, the
inactive precursor to pepsin.
These secretions form a complex coupled system since the rheology of mucin depends on pH and ionic
strength, acid can be bound by negatively charged mucin, ions and mucin electrostatically interact,
pepsinogen activation is pH dependent, and pepsin catalyzes mucin degradation. Goal #1 of this proposal
is to understand how this coupled system maintains homeostasis. Goal #2 is to understand infection by
Helicobacter pylori, which must swim across the mucus layer to colonize the epithelium. It locally modifies
the gel rheology as it swims by secreting neutralizing ammonia. Goal #3 is to understand whether gastric
organoids (GOs), spherical 3D cultures of a monolayer of differentiated epithelial cells, can accurately
model gastric mucus layer physiology and pathology.
The approach is to A: Build a mathematical model that fully couples mucin, ion, and enzyme transport
and interactions. Validate it through in vitro experiments on acid transport through mucin. B: Investigate
mechanisms of mucus layer homeostasis and acid transport using the mathematical model, flat 2D layers
of cultured epithelium, and physical models of mucus, by exploring volumetric, spatial, and temporal
variations of secretion rates. C: Mathematically model interaction of swimming H. pylori with mucus and
experimentally image and track single bacteria together with local ion concentrations and micro-rheology.
Model and experimentally observe collective effects of infection by dense populations of bacteria. D: Model
and experimentally test how variations in size and spatial localization of secretion affect mucus layer
formation in GOs to learn how and when they may be used as accurate models of physiology/pathology.

## Key facts

- **NIH application ID:** 9974529
- **Project number:** 5R01GM131408-03
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** AARON L FOGELSON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $365,725
- **Award type:** 5
- **Project period:** 2018-08-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9974529

## Citation

> US National Institutes of Health, RePORTER application 9974529, Modeling gastric mucus layer physiology (5R01GM131408-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9974529. Licensed CC0.

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