Microbiome profiling of nasal extracellular vesicles in patients with allergic rhinitis

Tsai-Yeh Chiang; Yu-Ru Yang; Ming-Ying Zhuo; Feng Yang; Ying-Fei Zhang; Chia-Hsiang Fu; Ta-Jen Lee; Wen-Hung Chung; Liang Chen; Chih-Jung Chang

doi:10.1016/j.waojou.2022.100674

Microbiome profiling of nasal extracellular vesicles in patients with allergic rhinitis

World Allergy Organ J. 2022 Aug 6;15(8):100674. doi: 10.1016/j.waojou.2022.100674. eCollection 2022 Aug.

Authors

Tsai-Yeh Chiang^{1

2}, Yu-Ru Yang¹, Ming-Ying Zhuo¹, Feng Yang¹, Ying-Fei Zhang¹, Chia-Hsiang Fu^{3

4}, Ta-Jen Lee^{1

3

4}, Wen-Hung Chung^{2

5

6

7

8

9}, Liang Chen^{2

10

11}, Chih-Jung Chang^{2

5

7

12}

Affiliations

¹ Department of Otorhinolaryngology, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
² Xiamen Chang Gung Allergology Consortium, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
³ Department of Otolaryngology-Head and Neck Surgery, Linkou Chang Gung Memorial Hospital, Taoyuan City, Taiwan.
⁴ Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan City, Taiwan.
⁵ Medical Research Center, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
⁶ Department of Dermatology, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
⁷ Department of Dermatology and Drug Hypersensitivity Clinical and Research Center, Chang Gung Memorial Hospital, Linkou, Taipei and Keelung, Taiwan.
⁸ Cancer Vaccine and Immune Cell Therapy Core Laboratory, Department of Medical Research, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan.
⁹ Whole-Genome Research Core Laboratory of Human Diseases, Chang Gung Memorial Hospital, Keelung, Taiwan.
¹⁰ Department of Respiratory and Critical Care Medicine, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
¹¹ Department of Allergy and Immunology, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
¹² School of Medicine, Huaqiao University, Quanzhou, Fujian, China.

Abstract

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.

Keywords: 16S rRNA sequencing; AR, Allergic rhinitis; ASV, Amplicon sequence variant; Allergic rhinitis; EVs, Extracellular vesicles; Extracellular vesicle; FITC, Fluorescein isothiocyanate; GPI, Glycosylphosphatidylinositol; HCs, Healthy controls; HDM, House dust mite; KEGG, Kyoto Encyclopedia of Genes and Genomes; LEfSe, Linear discriminant analysis (LDA) effect size; LPS, Lipopolysaccharide; MAMPs, Microorganism-associated molecular patterns; MRPP, Multiple response permutation procedure; Microbiota; OMVs, Outer membrane vesicles; PBS, Phosphate-buffered saline; PCoA, Principal coordinate analysis; PLS–DA, Partial least squares discriminant analysis; PRRs, Pattern recognition receptors; TEM, Transmission electron microscopy; UPGMA, Unweighted pair-group method with arithmetic means.