An integrated mathematical epithelial cell model for airway surface liquid regulation by mechanical forces. (7th February 2018) - Wu, Dan; Boucher, Richard C.; Button, Brian; Elston, Timothy; Lin, Ching-Long
Highlights: An epithelial cell model for airway surface liquid(ASL) regulation was developed. The cell model reproduces various responses similar to in vitro epithelial cells. The cell model was tested with various mechanical forces and evaporative flux. ASL homeostasis in both normal and cystic fibrosis airway epithelia were studied. Abstract: A robust method based on reverse engineering was utilized to construct the ion-channel conductance functions for airway epithelial sodium channels (ENaC), the cystic fibrosis transmembrane conductance regulator (CFTR), and calcium-activated chloride channels (CaCC). The ion-channel conductance models for both normal (NL) and cystic fibrosis (CF) airway epithelia were developed and then coupled to an adenosine triphosphate (ATP) metabolism model and a fluid transport model (collectively called the integrated cell model) to investigate airway surface liquid (ASL) volume regulation and hence mucus concentration, by mechanical forces in NL and CF human airways. The epithelial cell models for NL and CF required differences in Cl − secretion (decreased in CF) and Na + absorption (raised in CF) to reproduce behaviors similar to in vitro epithelial cells exposed to mechanical forces (cyclic shear stress, cyclic compressive pressure and cilial strain) and selected modulators of ion channels and ATP release. The epithelial cell models were then used to investigate the effects of mechanical forces and evaporative flux on ASL and mucus homeostasis in both NL and CF airway epithelia. Because of reduced CF ASL volumes, CF mucus concentrations increased and produced a greater dependence of ASL volume regulation on cilia-mucus-ATP release interactions in CF than NL epithelial nodules. Similarly, the CF model was less tolerant to evaporation induced ASL volume reduction at all ATP release rates than the NL model. Consequently, this reverse engineered model appears to provide a robust tool for investigating CF pathophysiology and novel therapies.