Development of a Controlled-Dose Aerosol Challenge Method Using a Lung Fluid Quantitative Nebulizer

Airborne transmission represents a primary route of influenza virus dissemination. In animal infection models, conventional intranasal instillation fails to recapitulate the physiological features of natural respiratory infection. Existing aerosol-based challenge methods—including whole-body inhalation and oronasal exposure—face limitations in precise quantification of the delivered infectious dose. Moreover, oronasal exposure systems require specialized, high-cost instrumentation. This study established an economical and dosing-controlled aerosol challenge method utilizing a lung fluid quantitative nebulizer, which can deliver aerosolized virus directly to the lower respiratory tract via endotracheal intubation. The count median aerodynamic diameter (CMAD) of aerosols generated by the nebulizer was 2.28 μm. We compared pulmonary deposition efficiency and pathogenicity between lung-delivery aerosol inhalation and conventional intranasal instillation of PR8 influenza virus in mice. The pulmonary deposition rate for the aerosol inhalation was 63.1%, with an LD50 of 31.1 EID50; in contrast, intranasal instillation achieved a pulmonary deposition rate of 20.0% and an LD50 of 115.0 EID50. Histopathological analysis revealed significantly more severe lesions in lungs of mice challenged via lung-delivery aerosol inhalation relative to those receiving intranasal instillation. Furthermore, using a guinea pig model and a recombinant PR8 virus expressing Gaussia luciferase (PR8-Gluc), we demonstrated that pulmonary aerosol inhalation resulted in both more homogeneous spatial distribution and higher viral loads across lung tissues. Our results demonstrate that animals are more sensitive to lung-delivery inhaled virus than virus delivered by intranasal instillation. This study provides an optimized, economical, and technically straightforward aerosol challenge method with controlled administered dosing for viral infection models.