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An immunocompetent human iPSC-derived multicellular Alveolus-on-Chip reveals early pathological events of M. tuberculosis infection

GSE252601 Homo sapiens Expression profiling by high throughput sequencing 4 samples Submitted 2025/11/19 Platform GPL24676
Summary
Immunocompetent and experimentally accessible alveolar systems to study human respiratory diseases are lacking. Here, we combined cells derived from a single induced pluripotent stem cell (iPSC) source with microfluidic devices that mimic lung 3D mechanical stretching and air-liquid interface. This single donor iPSC-derived Lung-on-Chip (iLoC) combines four alveolar cell types, including alveolar epithelial cells Type II and I, vascular endothelial cells, and macrophages. A combination of imaging and scRNA-seq analysis revealed that the iLoC recapitulated cellular profiles of distal lung cells present in the human lung including a range of AT2-to-AT1 cellular states and alveolar macrophages. We show that the presence of an endothelial barrier in the iLoC impacted tissue immunity in both the epithelium and macrophages. Different from 2D cellular models, infection of iLoC with the human pathogen Mycobacterium tuberculosis (Mtb) showed that both infected macrophages and epithelial cells were infected but not permissive to bacterial replication. Stochastically, large macrophage clusters containing necrotic core-like structure and Mtb replication were observed. Building a genetically engineered autophagy deficient iLoC (GE-iLoC), we found that after Mtb infection, macrophage cell death was elevated upon ATG14 deficiency with a reduced endothelial barrier integrity. Altogether, we report the first of its kind genetically tractable human alveolar model to study infections in human distal lungs.
Published in
Autologous human iPSC-derived alveolus-on-chip reveals early pathological events of Mycobacterium tuberculosis infection
Luk CH, Conway GL, Goh KJ et al. · Science advances 2026 · PMID 41477823 · doi:10.1126/sciadv.aea9874
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Also filed as BioProject PRJNA1061489 and SRA study SRP482113. Searching any of these in the dataset finder brings you back here.

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