Modeling Cystic Fibrosis Chronic Infection Using an Engineered Mucus-like Hydrogel

Abstract

Airway mucus provides protection to airway epithelial surfaces by trapping and clearing harmful pathogens. In cystic fibrosis, a genetic disorder that primarily impacts the respiratory system, airway mucus has altered properties including increased solids content and viscoelasticity. These altered properties cause mucus clearance mechanisms to fail and create a microenvironment primed for chronic airway infections. These complex polymicrobial infections show increased resistance to antibiotics and are associated with poor patient prognosis. Current in vitro models of cystic fibrosis airway infections fail to combine the key elements needed to fully represent this microenvironment and also lack the ability to capture major aspects of chronic airway infections in cystic fibrosis. In this study, mucus-like hydrogels with varied compositions and viscoelastic properties reflecting relative differences between healthy airway mucus and cystic fibrosis airway mucus were developed. Models of the cystic fibrosis and healthy airway microenvironments were created by combining the mucus-like hydrogels with relevant pathogens, human bronchial epithelial cells, and a common antibiotic used to treat airway infections in patients with cystic fibrosis. This research project demonstrated that antibiotic resistance was not solely dependent on the altered properties of the mucus-like hydrogels but was also influenced by culture conditions including microbe species, whether the culture was monomicrobial or polymicrobial, and the presence of epithelial cells. In addition, our cystic fibrosis airway model showed the ability to mimic important features that are characteristic of chronic cystic fibrosis airway infections including sustained polymicrobial growth and increased antibiotic tolerance. This model has the potential to be used to investigate antibiotic resistance and polymicrobial interactions in chronic cystic fibrosis airway infections and can also be adapted to study microbe behavior in other mucus-related diseases.