Bei Mu Gua Lou San facilitates mucus expectoration by increasing surface area and hydration levels of airway mucus in an air-liquid-interface cell culture model of the respiratory epithelium.

BACKGROUND: Bei Mu Gua Lou San (BMGLS) is an ancient formulation known for its moisturizing and expectorant properties, but the underlying mechanisms remain unknown. We investigated concentration-dependent effects of BMGLS on its rehydrating and mucus-modulating properties using an air-liquid-interface (ALI) cell culture model of the Calu-3 human bronchial epithelial cell line and primary normal human bronchial epithelial cells (NHBE), and specifically focused on quantity and composition of the two major mucosal proteins MUC5AC and MUC5B. METHODS: ALI cultures were treated with BMGLS at different concentrations over three weeks and evaluated by means of histology, immunostaining and electron microscopy. MUC5AC and MUC5B mRNA levels were assessed and quantified on protein level using an automated image-based approach. Additionally, expression levels of the major mucus-stimulating enzyme 15-lipoxygenase (ALOX15) were evaluated. RESULTS: BMGLS induced concentration-dependent morphological changes in NHBE but not Calu-3 ALI cultures that resulted in increased surface area via the formation of herein termed intra-epithelial structures (IES). While cellular rates of proliferation, apoptosis or degeneration remained unaffected, BMGLS caused swelling of mucosal granules, increased the area of secreted mucus, decreased muco-glycoprotein density, and dispensed MUC5AC. Additionally, BMGLS reduced expression levels of MUC5AC, MUC5B and the mucus-stimulating enzyme 15-lipoxygenase (ALOX15). CONCLUSIONS: Our studies suggest that BMGLS rehydrates airway mucus while stimulating mucus secretion by increasing surface areas and regulating goblet cell differentiation through modulating major mucus-stimulating pathways.

Quantification of increased MUC5AC expression in airway mucus of smoker using an automated image-based approach.

Microscopic analysis of mucus quantity and composition is crucial in research and diagnostics on muco-obstructive diseases. Currently used image-based methods are unable to extract concrete numeric values of mucosal proteins, especially on the expression of the key mucosal proteins MUC5AC and MUC5B. Since their levels increase under pathologic conditions such as extensive exposure to cigarette smoke, it is imperative to quantify them to improve treatment strategies of pulmonary diseases. This study presents a simple, image-based, and high-processing computational method that allows determining the ratio of MUC5AC and MUC5B within the overall airway mucus while providing information on their spatial distribution. The presented pipeline was optimized for automated downstream analysis using a combination of bright field and immunofluorescence imaging suitable for tracheal and bronchial tissue samples, and air-liquid interface (ALI) cell cultures. To validate our approach, we compared tracheal tissue and ALI cell cultures of isolated primary normal human bronchial epithelial cells derived from smokers and nonsmokers. Our data indicated 18-fold higher levels of MUC5AC in submucosal glands of smokers covering about 8% of mucosal areas compared to <1% in nonsmoking individuals, confirming results of previous studies. We further identified a subpopulation of nonsmokers with slightly elevated glandular MUC5AC levels suggesting moderate exposure to second-hand smoke or fine particulate air pollution. Overall, this study demonstrates a novel, user-friendly and freely available tool for digital pathology and the analysis of therapeutic interventions tested in ALI cell cultures.