A High-Throughput Distal Lung Air-Blood Barrier Model Enabled By Density-Driven Underside Epithelium Seeding

Area of Science:

• Biotechnology
• Respiratory Medicine
• Cell Biology

Background:

• Current high-throughput tissue barrier models often lack physiological relevance, particularly for the lung's air-blood barrier, which is typically modeled using epithelial cell monocultures.
• Existing methods neglect the crucial role of endothelial cell feedback in regulating barrier function.
• A key challenge in developing relevant high-throughput coculture models is the need for underside cell seeding, which is difficult to miniaturize and automate.

Purpose of the Study:

• To develop a scalable, low-cost method for seeding cells on the underside of membranes, enabling the creation of physiologically relevant, high-throughput coculture models.
• To establish a 96-well model of the distal lung epithelium-endothelium barrier for studying barrier function.
• To assess the model's response to inflammatory stimuli and viral infections.

Main Methods:

• A novel method was developed to optimize medium density, allowing cells to float and attach to the underside of a membrane, eliminating the need for inversion.
• A 96-well model of the distal lung epithelium-endothelium barrier was generated using serum-free, glucocorticoid-free air-liquid differentiation.
• The model's barrier function, intercellular junctions, and response to inflammatory stimuli (poly(I:C)) and viruses (influenza A, HCoV OC43) were evaluated.

Main Results:

• The developed method successfully created a polarized epithelium-endothelium coculture with mature barrier function and appropriate intercellular junction staining.
• The model demonstrated epithelial-to-endothelial transmission of inflammatory stimuli like poly(I:C).
• Exposure to influenza A virus PR8 and human beta-coronavirus OC43 induced a dose-dependent inflammatory response that propagated from the epithelium to the endothelium.

Conclusions:

• The described underside seeding method is a scalable and cost-effective approach for creating physiologically relevant high-throughput coculture models.
• This new model accurately mimics the distal lung air-blood barrier and its response to pathogens and inflammatory triggers.
• The generalizability of the seeding technique extends to various coculture tissue models, paving the way for advanced, scalable screening platforms.