Authors
Young, L.-M. G., Tostado, C. P., Koh Kok, J.-Y., Amaya Catano, J., DasGupta, R., Spann, K. M., Toh, Y.-C.
Abstract
Immune-epithelial interactions govern the initiation and progression of airway diseases, yet their heterogeneity is difficult to capture using existing in vitro models. Although conventional Transwell and lung-on-chip systems reproduce airway compartmentalisation and permit epithelial-immune interactions, they lack the spatial and analytical resolution needed to visualise dynamic immune behaviour during infection. Here, we present the "Single Cell resolved Airway-Immune Recruitment" (scAIR) platform designed to interrogate immune-epithelial interactions during airway infection. The scAIR device features a modular central chamber accommodating a Transwell insert with primary airway epithelial cells (AECs) pre-differentiated under air-liquid interface (ALI), flanked by immune compartments connected through a precision-patterned microchannel array. This architecture enables real-time single-cell imaging of immune cell migration while preserving epithelial physiology. The scAIR device coupled with a machine learning analysis (MLA) pipeline enables automated tracking and quantification of individual immune cell speed, direction, and behavioural heterogeneity. Using this platform, respiratory syncytial virus (RSV) infection is modelled to generate a type 1 inflammatory airway epithelium that drives neutrophil recruitment. TNF-alpha neutralisation with adalimumab reveals distinct migratory behaviours that are obscured by population-averaged measurements. This integrated platform quantifies airway immune responses during infection and therapeutic modulation, enabling mechanistic studies, drug evaluation, and precision modelling of airway inflammation.
Preprint server:
bioRxiv
The authors list and abstract were imported from bioRxiv on 26 Aug 2026.
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