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Microbiome profiling of nasal extracellular vesicles in patients with allergic rhinitis

BACKGROUND: Nasal microbiota is crucial for the pathogenesis of allergic rhinitis (AR), which has been reported to be different from that of healthy individuals. However, no study has investigated the microbiota in nasal extracellular vesicles (EVs). We aimed to compare the microbiome composition an...

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Detalles Bibliográficos
Autores principales: Chiang, Tsai-Yeh, Yang, Yu-Ru, Zhuo, Ming-Ying, Yang, Feng, Zhang, Ying-Fei, Fu, Chia-Hsiang, Lee, Ta-Jen, Chung, Wen-Hung, Chen, Liang, Chang, Chih-Jung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: World Allergy Organization 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386106/
https://www.ncbi.nlm.nih.gov/pubmed/36017065
http://dx.doi.org/10.1016/j.waojou.2022.100674
Descripción
Sumario:BACKGROUND: Nasal microbiota is crucial for the pathogenesis of allergic rhinitis (AR), which has been reported to be different from that of healthy individuals. However, no study has investigated the microbiota in nasal extracellular vesicles (EVs). We aimed to compare the microbiome composition and diversity in EVs between AR patients and healthy controls (HCs) and reveal the potential metabolic mechanisms in AR. METHODS: Eosinophil counts and serum immunoglobulin E (IgE) levels were measured in patients with AR (n = 20) and HCs (n = 19). Nasal EVs were identified using transmission electron microscopy and flow cytometry. 16S rRNA sequencing was used to profile the microbial communities. Alpha and beta diversities were analyzed to determine microbial diversity. Taxonomic abundance was analyzed based on the linear discriminant analysis effect size (LEfSe). Microbial metabolic pathways were characterized using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUst2) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. RESULTS: Eosinophils, total serum IgE, and IgE specific to Dermatophagoides were increased in patients with AR. Alpha diversity in nasal EVs from patients with AR was lower than that in HCs. Beta diversity showed microbiome differences between the AR and HCs groups. The microbial abundance was distinct between AR and HCs at different taxonomic levels. Significantly higher levels of the genera Acetobacter, Mycoplasma, Escherichia, and Halomonas were observed in AR patients than in HCs. Conversely, Zoogloea, Streptococcus, Burkholderia, and Pseudomonas were more abundant in the HCs group than in the AR group. Moreover, 35 microbial metabolic pathways recognized in AR patients and HCs, and 25 pathways were more abundant in the AR group. CONCLUSION: Patients with AR had distinct microbiota characteristics in nasal EVs compared to that in HCs. The metabolic mechanisms of the microbiota that regulate AR development were also different. These findings show that nasal fluid may reflect the specific pattern of microbiome EVs in patients with AR.