PROBING BIOPHYSICAL INTERACTIONS TO UNDERSTAND VIRAL DIFFUSION AND PARTICLE FATE IN THE AIRWAY MUCOSAL BARRIER
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The mucus barrier in the airway is the first line of defense against inhaled particulates and pathogens. Within the mucus barrier, large, heavily glycosylated gel-forming mucin proteins form a network to trap particles for removal. Influenza A virus (IAV) must first cross the mucus barrier before reaching the underlying airway epithelial cells to cause infection. On the IAV envelope, hemagglutinin (HA) binds sialic acid on the surface of the cell to initiate viral entry. However, HA preferentially binds sialic acid attached to galactose by either an ⍺2,3 or ⍺2,6 linkage. In addition to the cell surface, sialic acid is found on mucins and is thought to act as a decoy receptor to entrap the IAV within the mucus layer. However, neuraminidase (NA) on the envelope of IAV cleaves the bond between HA and sialic acid, releasing the virus. While the mechanism of IAV infection has been characterized, the interplay between mucus biophysical properties and the binding of IAV within the mucus network prior to infection requires further investigation. The overall objective of this dissertation is to understand how IAV moves through the mucosal barrier to subsequently cause infection. We hypothesize the structural features of the mucus gel network are responsible for the changes in IAV movement, rather than the binding and unbinding of the virus. To investigate this, we first analyzed the movement of IAV in ex vivo mucus from human endotracheal tubes. In order to further analyze this movement, we developed a novel analysis to calculate the dissociation constant of IAV-mucus binding in a 3D gel network environment. Using this data, we established a pipeline for estimating the passage of particles, including IAV, through the airway mucosal barrier. A machine learning-based trajectory analysis was employed to classify individual trajectories in order to calculate the percentage of particles able to cross the mucus barrier within a physiologically relevant time frame. Lastly, we investigated the effect of sialic acid binding preference on diffusion of IAV through mucus collected from different in vitro human airway epithelial cell cultures. The combined results of these studies confirmed our hypothesis that the mucus microstructure rather than the adhesive interactions of IAV to the mucins was responsible for the differences in IAV diffusion. This work provides further insight into role of the mucosal barrier in IAV infection and identifies the mucus gel network microstructure as a target for the development of therapeutics against IAV.