Mucus coats the lung epithelium and traps thousands of pathogens that we inhale every day. Human bronchial epithelial (hBE) cells lining the lung have cilia that propel mucus via shear forces, a mechanism known as muco-ciliary transport (MCT). MCT acts to clear mucus, providing a primary defense against trapped pathogens. In respiratory diseases such as cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD), MCT breaks down, leading to chronic infection, damage to airway tissues, and ultimately, morbidity and mortality. This loss of MCT is directly associated with mucus dehydration (i.e., increasing mucus solids concentration). Because of this, therapies that target hydrating or thinning airway mucus are being developed to re-establish MCT in patients with COPD and CF, although they are only marginally effective. Importantly, the underlying mechanism for this concentration-dependent effect on MCT is not well understood; bulk rheological changes in mucus properties have been extensively studied as a function of mucus concentration, but there is a lack of methods to measure mucus under oscillatory shear forces that cilia apply to transport mucus. We hypothesize that the nanostructure of the macromolecules (mucins) that comprise mucus is modified by ciliary shear forces in a concentration-dependent way, which dictates how ciliary shear forces are propagated within the mucus layer to enable MCT. A better understanding of these heterogeneous, shear-dependent properties of mucus will provide needed insight into strategies for developing more effective mucus thinning therapies. Here we propose a bioanalytical tool to image nanostructural changes in mucus undergoing active muco- ciliary transport, while simultaneously quantifying MCT. We have already shown that PEGylated gold nanorods (GNRs) readily diffuse into human airway mucus, and using optical coherence tomography (OCT), the dynamic light scattering from GNRs provides an accurate measurement of GNR diffusion rate that is inversely correlated with mucus concentration. We will use diffusion-sensitive OCT (DS-OCT) of GNRs to depth-resolve mucus nanoporosity within the mucus layer, from the high-shear peri-ciliary layer (PCL) to the stress-free air boundary. Simultaneous measurements of the mucus flow field by tracking endogenous scatterers or embedded microbeads will provide shear strain and MCT velocity. Our approach will be to first validate measurements in a parallel-plate shearing system (PPSS) that applies controlled, cilia-like oscillatory shear on well-known fluids. We will then perform PPSS measurements on hBE mucus to establish the onset conditions for shear-thinning and nanoporosity changes.
Our second Aim will be to perform these same measurements on an in vitro model of actively transporting mucus to study the role of shear-thinning and nanoporosity on MCT. Finally, measurements will be obtained during and after application of mucus hydrating agents to study dynamic effects of mucus hydration and re-establishment of MCT during treatment. These studies will provide an important link to in vivo-like conditions, providing previously inaccessible insight on MCT and drug therapies.

Public Health Relevance

The clearance of mucus in the airways is important for maintaining respiratory health, but breaks down in diseases such as chronic obstructive pulmonary disease and cystic fibrosis. We propose to construct an imaging tool to measure changes in the nanostructure of mucus while undergoing active transport by airway cilia that we hypothesize dictate mucus clearance, in order to better understand why the mucus becomes less effectively cleared from the airways in these diseases. The insight gained from this proposal may lead to better drugs and better imaging tools for monitoring drug treatments designed to increase mucus clearance.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Exploratory/Developmental Grants (R21)
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Biomedical Imaging Technology Study Section (BMIT)
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Sheridan, John T
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University of North Carolina Chapel Hill
Schools of Arts and Sciences
Chapel Hill
United States
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Marks, Daniel L; Blackmon, Richard L; Oldenburg, Amy L (2018) Diffusion tensor optical coherence tomography. Phys Med Biol 63:025007
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