Modeling Respiratory Infections Using Patient-Derived Apical-Out Airway Organoids.

Airway organoids bridge the gap between conventional epithelial cultures and animal models by combining human tissue architecture, cellular diversity, and experimental accessibility. However, because these systems are dynamic, reproducible infection modeling requires careful definition of parameters influencing infection readouts, including epithelial polarity, maturation, cellular composition, and access to a physiologically relevant apical surface. We established patient-derived apical-out airway organoids and characterized them longitudinally using multiple modalities throughout differentiation, followed by proof-of-concept viral infection and host-response profiling. Organoids generated from resected human lung tissue were converted from an apical-in to an apical-out orientation and maintained in suspension. Over 21 days, they retained outward-facing apical features and matured from basal-cell-enriched structures into airway-like epithelium containing goblet cells, microvilli, ionocytes and ciliated cells, with mucus production and motile surface cilia. This time-resolved characterization demonstrated changes in organoid growth, epithelial organization, and lineage composition, guiding selection of maturation stages for infection experiments. Exposure of the apical surface to GFP-expressing human metapneumovirus (hMPV) enabled infection without disruptive shearing or microinjection. Viral fluorescence and immunostaining confirmed hMPV infection and revealed associated cytopathic changes in infected organoids. Infection efficiency and cellular tropism varied across maturation stages. Bulk RNA sequencing of infected versus mock-infected organoids showed reproducibly distinct transcriptional profiles and enrichment of antiviral and innate immune pathways. These findings demonstrate that the epithelial features shaping infection readouts must be defined empirically within each organoid system through longitudinal, multimodal characterization, thereby supporting rigorous interpretation and reproducible application in mechanistic and translational respiratory infection studies.