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. 2023 Mar 20:14:1079154.
doi: 10.3389/fimmu.2023.1079154. eCollection 2023.

Characterization of dysbiosis of the conjunctival microbiome and nasal microbiome associated with allergic rhinoconjunctivitis and allergic rhinitis

Yuan Wang  1   2   3 , Xuan Li  1   2   4 , Shuntong Gu  5   6 , Junhong Fu  7
Affiliations

Characterization of dysbiosis of the conjunctival microbiome and nasal microbiome associated with allergic rhinoconjunctivitis and allergic rhinitis

Yuan Wang et al. Front Immunol. .

Abstract

Background: Allergic rhinoconjunctivitis (ARC) and allergic rhinitis (AR) are prevalent allergic diseases. People are becoming increasingly aware of the impact of microbial disorders on host immunity and allergic diseases. Studies have demonstrated an association between allergic diseases and the microbiome, but much remains unknown. We assessed changes in the conjunctival microbiome and nasal microbiome in patients with ARC or AR.

Methods: Conjunctival swabs and nasal swabs were collected from each participant for 16S rRNA amplicon sequencing. Bacterial communities were analyzed.

Results: Forty patients with ARC, 20 patients suffering from AR, and 34 healthy controls (HCs) were recruited. This study found the abundance of conjunctival microbiome in patients with ARC or AR was significantly lower than that in HCs. The diversity of conjunctival microbiome in patients with AR was significantly lower than those in the other two groups. There is no significant difference in abundance of nasal microbiome between the three groups. The diversities of nasal microbiome in patients with ARC or AR were significantly lower than that in HCs. We found significant differences in microbiota compositions in patients with ARC or AR compared with those in HCs. However, no significant difference in microbiota compositions was found between patients with ARC and patients with AR. Microbiome functions in the ARC group and AR group were also altered compared with HCs.

Conclusions: We revealed changes in the composition and function of the conjunctival microbiome and nasal microbiome of patients with ARC or AR, which suggests that there is a relationship between allergic conditions and the local microbiome.

Keywords: 16s rRNA amplicon sequencing; allergic rhinitis; allergic rhinoconjunctivitis; conjunctival; microbiome; nasal.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Venn diagram showing overlaps of the operational taxonomic units (OTUs) among the three groups. (A) Venn diagram of conjunctival microbiome. (B) Venn diagram of nasal microbiome. HC.E, eye of healthy controls; HC.N, nose of healthy controls; ARC.E, eye of allergic rhinoconjunctivitis; ARC.N, nose of allergic rhinoconjunctivitis; AR.E, eye of allergic rhinitis; AR.N, nose of allergic rhinitis.
Figure 2
Figure 2
Alpha rarefaction represented by Chao1 index (A) and goods-coverage index (B). The horizontal axis represents the amount of sequencing data, and the vertical axis represents the corresponding alpha diversity index.
Figure 3
Figure 3
The alpha diversity of conjunctival microbiome represented by Chao1 index (A), Observed-otus index (B), Shannon index (C), and Simpson index (D). The alpha diversity of nasal microbiome represented by Shannon index (E) and Simpson index (F), *p < 0.05, **p < 0.01, ***p < 0.001.
Figure 4
Figure 4
Principal Coordinate Analysis (PCoA) of beta diversity based on the weighted UniFrac distances. (A) PCoA of conjunctival microbiome among ARC group, AR group, and healthy controls. (B) PCoA of nasal microbiome among ARC group, AR group, and healthy controls.
Figure 5
Figure 5
Box plots of the phylum and genus taxonomic levels in ARC, AR and healthy controls. (A) Top 10 phyla of conjunctival microbiome in the three groups. (B) Top 10 phyla of nasal microbiome in the three groups. (C) Top 10 genera of conjunctival microbiome in the three groups. (D) Top 10 genera of nasal microbiome in the three groups.
Figure 6
Figure 6
Bacterial biomarkers identified with the linear discriminant analysis effect size (LEfSe) algorithm. Linear discriminant analysis (LDL) scores with the LEfSe tool for taxa, with LDA score > 4 and P < 0.05 shown in the histogram. (A) Conjunctival bacterial biomarkers identified between ARC group and healthy controls. (B) Conjunctival bacterial biomarkers identified between AR group and healthy controls. (C) Nasal bacterial biomarkers identified between ARC group and healthy controls. (D) Nasal bacterial biomarkers identified between AR group and healthy controls.
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