© 2016 Journal of Visualized Experiments. Mucins, the heavily-glycosylated proteins lining mucosal surfaces, have evolved as a key component of innate defense by protecting the epithelium against invading pathogens. The main role of these macromolecules is to facilitate particle trapping and clearance while promoting lubrication of the mucosa. During protein synthesis, mucins undergo intense O-glycosylation and multimerization, which dramatically increase the mass and size of these molecules. These post-translational modifications are critical for the viscoelastic properties of mucus. As a result of the complex biochemical and biophysical nature of these molecules, working with mucins provides many challenges that cannot be overcome by conventional protein analysis methods. For instance, their high-molecular-weight prevents electrophoretic migration via regular polyacrylamide gels and their sticky nature causes adhesion to experimental tubing. However, investigating the role of mucins in health (e.g., maintaining mucosal integrity) and disease (e.g., hyperconcentration, mucostasis, cancer) has recently gained interest and mucins are being investigated as a therapeutic target. A better understanding of the production and function of mucin macromolecules may lead to novel pharmaceutical approaches, e.g., inhibitors of mucin granule exocytosis and/or mucolytic agents. Therefore, consistent and reliable protocols to investigate mucin biology are critical for scientific advancement. Here, we describe conventional methods to separate mucin macromolecules by electrophoresis using an agarose gel, transfer protein into nitrocellulose membrane, and detect signal with mucin-specific antibodies as well as infrared fluorescent gel reader. These techniques are widely applicable to determine mucin quantitation, multimerization and to test the effects of pharmacological compounds on mucins.
Ramsey, K., Rushton, Z. L., & Ehre, C. (2016). Mucin agarose gel electrophoresis: Western blotting for high-molecular-weight glycoproteins. Journal of Visualized Experiments, 2016(112), e54153. https://doi.org/10.3791/54153