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Updated: Jul 5, 2026

Three-dimensional Quantification of Intestinal Mucus Using Whole-mount Tissue Imaging
Published on: September 12, 2025
Quantitative imaging approaches to capture structural and functional dynamics of colonic mucus in health and disease
Megan Turluk1, Benjamin Bigiremana1, Darrek Kniffen1
1Department of Biology, University of British Columbia - Okanagan Campus, Kelowna, BC, Canada.
Abstract:
Mucins are highly glycosylated proteins, a subset of which form the structural basis of mucus barriers at mucosal surfaces. In the gastrointestinal tract, the secreted gel-forming mucin MUC2 is the principal component of the intestinal mucus layer and plays a critical role in maintaining host-microbiota homeostasis. MUC2 undergoes extensive post-translational glycosylation mediated by numerous glycosyltransferases, producing a dense network of O- and N-linked glycans that regulate mucus structure, microbial interactions, and barrier function. Disruption of mucus integrity has been implicated in a range of diseases including infection, inflammation, and cancer. Accurate visualization and quantification of mucus architecture are therefore essential for understanding mucus biology and its role in disease pathogenesis. Histological analysis remains the most accessible approach for studying mucus structure in situ. Recent work has revealed that the inner (barrier) layer can be subdivided into two distinct sublayers (b1 and b2) with different cellular origins and glycan compositions. These structural features necessitate analytical approaches capable of quantifying mucus thickness, spatial organization, and microbial proximity with high reproducibility. Here we describe a set of complementary workflows for the visualization and quantitative analysis of intestinal mucus. These include brightfield histochemical staining using Alcian Blue, fluorescence lectin labeling to resolve mucus sublayers, and combined mucin-bacterial fluorescence in situ hybridization for confocal imaging. In addition, we present automated image analysis pipelines implemented in ImageJ/Fiji for reproducible quantification of mucus thickness and spatial structure. Together, these approaches provide a practical framework for studying mucus barrier biology and mucus-microbe interactions in health and disease.
