Multidrug-resistant Haemophilus influenzae cluster of severe asthma from sputum bacteriome-resistome
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Published version
Author(s)
Type
Journal Article
Abstract
Background
Severe asthma encompasses heterogeneous inflammatory phenotypes and airway bacteriome diversity but the state of its airway resistome remains understudied. We therefore evaluated the link between the airway microbiome and the antibiotic-resistant genes by determining the clusters from a bacteriome–resistome integration from sputum samples of patients with severe asthma.
Methods
Induced sputum samples from severe asthma (SA; n=96), mild–moderate asthma (MMA; n=23) and healthy controls (HCs; n=23) in the European U-BIOPRED asthma cohort were metagenomically sequenced. Respiratory bacteriome was evaluated by taxonomical and functional classification. The comprehensive antibiotic resistance database was used to determine airway resistome and Similarity Network Fusion to cluster integratively the bacteriome–resistome.
Results
More multidrug-resistance genes were present in SA compared with MMA and HCs with the hmrM, encoded in Haemophilus influenzae chromosome, being highest. Two of the three defined clusters were dominated by commensals with resistance genes from different classes but different in α- and β-diversities. The third cluster was dominated by multidrug-resistant H. influenzae, with SA characteristics of increased asthma duration, reduced pulmonary macrophages and decreased lung function. It had the highest signature expression of neutrophil activation, NETosis and of interleukin (IL)-5, IL-6, IL-13, IL-17 and IL-33 signalling pathways. These clusters were reproduced in an Asian-Singapore SA cohort including the multidrug-resistant H. influenzae cluster, but with an additional cluster of multidrug-resistant Pseudomonas aeruginosa.
Conclusion
The demonstration of U-BIOPRED multiresistant H. Influenzae and of Asian-Singapore multiresistant P. aeruginosa clusters highlights the potential importance of antibiotic-resistant genes in driving severe asthma.
Severe asthma encompasses heterogeneous inflammatory phenotypes and airway bacteriome diversity but the state of its airway resistome remains understudied. We therefore evaluated the link between the airway microbiome and the antibiotic-resistant genes by determining the clusters from a bacteriome–resistome integration from sputum samples of patients with severe asthma.
Methods
Induced sputum samples from severe asthma (SA; n=96), mild–moderate asthma (MMA; n=23) and healthy controls (HCs; n=23) in the European U-BIOPRED asthma cohort were metagenomically sequenced. Respiratory bacteriome was evaluated by taxonomical and functional classification. The comprehensive antibiotic resistance database was used to determine airway resistome and Similarity Network Fusion to cluster integratively the bacteriome–resistome.
Results
More multidrug-resistance genes were present in SA compared with MMA and HCs with the hmrM, encoded in Haemophilus influenzae chromosome, being highest. Two of the three defined clusters were dominated by commensals with resistance genes from different classes but different in α- and β-diversities. The third cluster was dominated by multidrug-resistant H. influenzae, with SA characteristics of increased asthma duration, reduced pulmonary macrophages and decreased lung function. It had the highest signature expression of neutrophil activation, NETosis and of interleukin (IL)-5, IL-6, IL-13, IL-17 and IL-33 signalling pathways. These clusters were reproduced in an Asian-Singapore SA cohort including the multidrug-resistant H. influenzae cluster, but with an additional cluster of multidrug-resistant Pseudomonas aeruginosa.
Conclusion
The demonstration of U-BIOPRED multiresistant H. Influenzae and of Asian-Singapore multiresistant P. aeruginosa clusters highlights the potential importance of antibiotic-resistant genes in driving severe asthma.
Date Issued
2026-03-01
Date Acceptance
2025-10-03
Citation
ERJ Open Research, 2026, 12 (2)
ISSN
2312-0541
Publisher
European Respiratory Society
Journal / Book Title
ERJ Open Research
Volume
12
Issue
2
Copyright Statement
©The authors 2026 This version is distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0. For commercial reproduction rights and permissions contact permissions@ersnet.org
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Publication Status
Published
Date Publish Online
2026-04-07