An immune-competent lung-on-a-chip for modelling the human severe influenza infection response

Severe influenza affects 3-5 million people worldwide each year, resulting in more than 300,000 deaths annually. However, standard-of-care antiviral therapeutics have limited effectiveness in these patients. Current preclinical models of severe influenza fail to accurately recapitulate the human immune response to severe viral infection. Here we develop an immune-competent, microvascularized, human lung-on-a-chip device to model the small airways, successfully demonstrating the cytokine storm, immune cell activation, epithelial cell damage, and other cellular- and tissue-level human immune responses to severe H1N1 infection. We find that interleukin-1β and tumour necrosis factor-α play opposing roles in the initiation and regulation of the cytokine storm associated with severe influenza. Furthermore, we discover the critical stromal-immune CXCL12-CXCR4 interaction and its role in immune response to infection. Our results underscore the importance of stromal cells and immune cells in microphysiological models of severe lung disease, describing a scalable model for severe influenza research. We expect the immune-competent human lung-on-a-chip device to enable critical discoveries in respiratory host-pathogen interactions, therapeutic side effects, vaccine potency evaluation, and crosstalk between systemic and mucosal immunity in human lung.

Authors

Institutions

Publication Details

Journal
Nature Biomedical Engineering
Published
2025-09-23
DOI
https://doi.org/10.1038/s41551-025-01491-9
Citations
7
Primary Topic
3D Printing in Biomedical Research
Type
article
Field-Weighted Citation Impact
4.72
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An immune-competent lung-on-a-chip for modelling the human severe influenza infection response

Drishti Maniar, Paramita Chatterjee, Krishnendu Roy, Rachel Ringquist et al.
7 citations
Nature Biomedical Engineering
3D Printing in Biomedical Research
4.72
article

An immune-competent lung-on-a-chip for modelling the human severe influenza infection response

Drishti Maniar, Paramita Chatterjee, Krishnendu Roy, Rachel Ringquist, Ankur Singh, Ahmet F. Coskun, Liana Kramer, Eshant Bhatia, Delta Ghoshal, Fang Zhou, Peter Franz, Abigail Ochal, Neha Sonthi, Savi Agarwal, Emma Downey, Joshua Canlas, Valeria Cuéllar, Grace Harrigan
article en
7 citations

Abstract

Severe influenza affects 3-5 million people worldwide each year, resulting in more than 300,000 deaths annually. However, standard-of-care antiviral therapeutics have limited effectiveness in these patients. Current preclinical models of severe influenza fail to accurately recapitulate the human immune response to severe viral infection. Here we develop an immune-competent, microvascularized, human lung-on-a-chip device to model the small airways, successfully demonstrating the cytokine storm, immune cell activation, epithelial cell damage, and other cellular- and tissue-level human immune responses to severe H1N1 infection. We find that interleukin-1β and tumour necrosis factor-α play opposing roles in the initiation and regulation of the cytokine storm associated with severe influenza. Furthermore, we discover the critical stromal-immune CXCL12-CXCR4 interaction and its role in immune response to infection. Our results underscore the importance of stromal cells and immune cells in microphysiological models of severe lung disease, describing a scalable model for severe influenza research. We expect the immune-competent human lung-on-a-chip device to enable critical discoveries in respiratory host-pathogen interactions, therapeutic side effects, vaccine potency evaluation, and crosstalk between systemic and mucosal immunity in human lung.

Nature Biomedical Engineering
Georgia Institute of Technology (US), Emory University (US), Vanderbilt University (US), The Wallace H. Coulter Department of Biomedical Engineering (US), Vanderbilt University Medical Center (US)
Openalex Percentile: Top 5%
3D Printing in Biomedical Research
4.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.