Effects of azithromycin on alleviating airway inflammation in asthmatic mice by regulating airway microbiota and metabolites

Asthma is a chronic respiratory disease with increasing global prevalence, often linked to disrupted airway microbiota. Azithromycin has shown promise in asthma treatment, but whether its effect is owing to its antimicrobial capacity remains largely unknown. A house dust mite (HDM)-induced asthmatic mouse model was used to evaluate the effects of azithromycin on airway inflammation and microbiota. Mice were divided into control, HDM-induced asthma, HDM + azithromycin, and azithromycin-alone groups. Airway microbiota was analyzed using 16S rRNA sequencing, and metabolomic profiles were assessed via liquid chromatography-tandem mass spectrometry. Azithromycin alleviated type 2 airway inflammation in HDM-induced asthma, restoring microbiota diversity by modulating specific genera, including <i>Streptococcus</i>, <i>Staphylococcus</i>, <i>Ruminococcus</i>, <i>Coprococcus</i>, <i>Bifidobacterium,</i> etc. Combination analysis with metabolomics revealed that azithromycin significantly regulated airway microbiota-associated sphingomyelin metabolism. Azithromycin's therapeutic effects in asthma are associated with its ability to regulate airway microbiota and its associated sphingomyelin metabolism, highlighting the potential for microbiota-targeted therapies in asthma.IMPORTANCEAsthma, a prevalent chronic respiratory condition, poses a significant global health challenge due to its increasing prevalence and associated morbidity. The role of airway microbiota in asthma pathogenesis is gaining attention, with evidence suggesting that disruptions in this microbial community contribute to disease severity. Our study investigates the impact of azithromycin, a macrolide antibiotic, on airway inflammation and microbiota in a mouse model of asthma. The findings reveal that azithromycin not only alleviates airway inflammation but also restores microbiota diversity and modulates microbiota-associated sphingomyelin metabolism. This research underscores the potential of microbiota-targeted therapies in asthma management, offering a novel therapeutic strategy that could improve patient outcomes and reduce the healthcare burden associated with asthma.

Authors

Institutions

Publication Details

Journal
Microbiology Spectrum
Published
2025-02-11
DOI
https://doi.org/10.1128/spectrum.02217-24
Citations
2
Primary Topic
Asthma and respiratory diseases
Type
article
Field-Weighted Citation Impact
2.33

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effects of azithromycin on alleviating airway inflammation in asthmatic mice by regulating airway microbiota and metabolites

Haijin Zhao, Hangming Dong, Lishan Lin, Lingyan Xie et al.
2 citations
Microbiology Spectrum
Asthma and respiratory diseases
2.33
article

Effects of azithromycin on alleviating airway inflammation in asthmatic mice by regulating airway microbiota and metabolites

Haijin Zhao, Hangming Dong, Lishan Lin, Lingyan Xie, Tingyue Luo, Shaoxi Cai, Haohua Huang, Yuehua Chen, Hua Liao, Zhaojin Zeng, QianNan Ren, Xiaodan Chang, Danhui Hunag
article en
2 citations

Abstract

Asthma is a chronic respiratory disease with increasing global prevalence, often linked to disrupted airway microbiota. Azithromycin has shown promise in asthma treatment, but whether its effect is owing to its antimicrobial capacity remains largely unknown. A house dust mite (HDM)-induced asthmatic mouse model was used to evaluate the effects of azithromycin on airway inflammation and microbiota. Mice were divided into control, HDM-induced asthma, HDM + azithromycin, and azithromycin-alone groups. Airway microbiota was analyzed using 16S rRNA sequencing, and metabolomic profiles were assessed via liquid chromatography-tandem mass spectrometry. Azithromycin alleviated type 2 airway inflammation in HDM-induced asthma, restoring microbiota diversity by modulating specific genera, including <i>Streptococcus</i>, <i>Staphylococcus</i>, <i>Ruminococcus</i>, <i>Coprococcus</i>, <i>Bifidobacterium,</i> etc. Combination analysis with metabolomics revealed that azithromycin significantly regulated airway microbiota-associated sphingomyelin metabolism. Azithromycin's therapeutic effects in asthma are associated with its ability to regulate airway microbiota and its associated sphingomyelin metabolism, highlighting the potential for microbiota-targeted therapies in asthma.IMPORTANCEAsthma, a prevalent chronic respiratory condition, poses a significant global health challenge due to its increasing prevalence and associated morbidity. The role of airway microbiota in asthma pathogenesis is gaining attention, with evidence suggesting that disruptions in this microbial community contribute to disease severity. Our study investigates the impact of azithromycin, a macrolide antibiotic, on airway inflammation and microbiota in a mouse model of asthma. The findings reveal that azithromycin not only alleviates airway inflammation but also restores microbiota diversity and modulates microbiota-associated sphingomyelin metabolism. This research underscores the potential of microbiota-targeted therapies in asthma management, offering a novel therapeutic strategy that could improve patient outcomes and reduce the healthcare burden associated with asthma.

Microbiology SpectrumVol. 13(3)
Nanfang Hospital (CN), Southern Medical University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Basic and Applied Basic Research Foundation of Guangdong Province
Good health and well-being
Openalex Percentile: Top 14%
Asthma and respiratory diseases
2.33
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.