Virtual Lung Project (Greg Forest, Michael Rubinstein, Rich Superfine, Tim Elston, Russ Taylor, Sorin Mitran)
The Virtual Lung Project has spawned a wide spectrum of nanotechnology applications. In this collaboration between faculty and students from Applied Mathematics, Chemistry, Computer Science, Pharmacology, Physics & Astronomy, and the Cystic Fibrosis Center, we are adapting and designing instrumentation from nano-scale microscopy toward understanding the physical and chemical properties of pulmonary cells, tissues, liquids, and cilia, and toward understanding how biological components in an organ interact to perform vital functions in "normal" versus "diseased" states.
The classical view of the airway surface liquid (ASL) is that it consists of two layers – the mucus and the periciliary layer (PCL). The mucus layer is propelled by cilia and rides on top of the PCL, which is assumed to be a low viscosity dilute liquid that does not hinder cilia beating and acts as a lubricating layer for mucus motion. This simple classical model of ASL has a major problem, however. It does not explain what stabilizes the mucus layer and prevents it (and the pathogens it contains) from penetrating the PCL and adhering to the cell surface. We propose a different model of the ASL in which the PCL consists of a dense brush of mucins attached to cilia and microvilli. This brush stabilizes the mucus layer and prevents its penetration into the PCL, while providing lubrication and elastic coupling between beating cilia, as well as protecting cells from particles and bacteria contained in the mucus. The predictions of our polyelectrolyte brush model, such as mucus concentration dependence on PCL thickness and of mucus transport velocity, are in good agreement with fluorescence probe and confocal data. This systems level approach toward pulmonary function and dysfunction, built up from nanoscale components and experiments, has implications for many health technologies: new methods of drug discovery, approval, and delivery; new methods for probing the physical and chemical properties of biological material; and the theoretical and computational foundations for interpreting data.
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