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. 2025 May;74(5):002013.
doi: 10.1099/jmm.0.002013.

Alterations of ocular surface microbiome in glaucoma and its association with dry eye

Affiliations

Alterations of ocular surface microbiome in glaucoma and its association with dry eye

Houyem Kamdougha et al. J Med Microbiol. 2025 May.

Abstract

Introduction. Alterations in ocular surface microbiota (OSM) have been noted in both dry eye disease (DED) and glaucoma. However, the combined effects of these conditions on OSM have not been explored.Hypothesis. We hypothesized that patients with both glaucoma and dry eye would exhibit distinct changes in OSM composition and diversity compared to those with only glaucoma, only dry eye or healthy individuals.Aim. We employed amplicon sequencing to investigate OSM profiles in patients with glaucoma and/or dry eye disease.Methods. Swab samples from the conjunctiva of both eyes were collected from 28 glaucomatous patients [13 without dry eye syndrome (G-only) and 15 with dry eye syndrome (G-DED)], 13 DED patients without glaucoma (DED-only) and 31 age-matched healthy controls (HCs). After V3-V4 16S rRNA sequencing, MOTHUR tools and R language were used to elucidate and compare OSM composition and diversity between groups.Results. Our data revealed very diverse bacterial communities with 28 phyla and 785 genera. All the groups shared the three most abundant phyla, Actinobacteria (67.47%), Firmicutes (17.14%) and Proteobacteria (13.73%). Corynebacterium (54.75%), Staphylococcus (10.71%), Cutibacterium (8.77%) and Streptococcus (3.20%) were the most abundant genera. Only the G-DED group showed higher alpha diversity than the HC group (P<0.05). However, significant differences in beta diversity were observed between all three patient groups and the HC group. The Differential Expression for Sequencing 2 (DESeq2) analysis unveiled an increased presence of opportunistic bacteria across all pathological groups, with the G-DED group demonstrating the most pronounced alterations.Conclusions. Our findings confirm the predominance of Gram-positive bacteria in normal OSM and the rise of opportunistic Gram-negative bacteria in glaucoma and dry eye disease. This is the first study to characterize OSM in glaucoma patients with DED.

Keywords: conjunctiva; dry eye disease; dysbiosis; glaucoma; microbiome; preservatives.

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Conflict of interest statement

The authors declare that there are no conflicts of interest.

Figures

Fig. 1.
Fig. 1.. (a–c) Boxplot visualization of alpha diversity (based, respectively, on the Shannon index and Simpson index) and richness (based on the Chao1 index) of the four study groups, tested by ANOVA, followed by paired t-tests with the P-value corrected by Bonferroni (threshold value of P=0.05). (d) NMDS model based on a Bray–Curtis dissimilarity matrix, with data projected into three-dimensional space (K=3) and a model stress of 0.1028451. The ellipses drawn around the groups show the 95% confidence intervals around the centroid of each group, illustrating the dispersion and concentration of the samples. (e) Boxplot visualizing the quantification of total bacterial 16S rDNA. The difference in bacterial load is tested by ANOVA, followed by paired t-tests with the P-value corrected by Bonferroni (threshold value of P=0.05). DED-only, dry eye group; G-only, glaucoma group; G-DED, glaucoma with dry eye group.
Fig. 2.
Fig. 2.. Taxonomy bar plot of microbial composition in the control (HC) and pathological groups [glaucomatous patients (G-only), glaucomatous patient with DED (G-DED) and dry eye syndrome group (DED-only)] eye samples. The most 18 abundant genera were represented in the figure. The relative abundance for each individual sample was initially computed by dividing the read counts assigned to each OTU linked to each microbe by the total read count of the sample. (a) Composition of the ocular microbiome at the phylum level with a comparison of phylum abundance between groups using DESeq2. The two groups G-DED and G-only contained a significantly higher abundance of Proteobacteria compared to the control and the DED-only groups (P<0.05). The G-DED group contained a significantly higher abundance of Firmicutes in contrast to the other three groups (P<0.05) and a significantly higher abundance of Bacteroidota in comparison with the HC and DED-only groups. (b, c) Composition of sample eye microbiota based on relative abundance at the genus level per sample and per group. The top six abundant genera in almost all groups were Corynebacterium, Staphylococcus, Cutibacterium, Escherichia-Shigella, Streptococcus and Neisseriaceae_ge.
Fig. 3.
Fig. 3.. Marker genera volcano plots depict bacterial taxa and their log2 fold change, comparing eye samples from patients in the G-only group, G-DED group and DE-only group to those of healthy controls by identifying the adjusted P-value. The log2 fold change and padj values are derived from the DESeq2 workflow. Genera exhibiting mean count with a significance level of P<0.05 are marked as red points (indicating a significant difference between groups), while black points signify no significant difference.
Fig. 4.
Fig. 4.. Stacked bar chart visualization of bacterial profiles of left and right eyes by group with ggplot from the R package (a). NMDS model based on a Bray–Curtis dissimilarity matrix, with data projected into three-dimensional space (K=3) and a model stress of 0.1028451 (b). Boxplot visualization of alpha diversity (based, respectively, on the Shannon index and Simpson index) and population richness (based on the Chao1 index) of the microbiota of left and right eyes, tested by Wilcoxon test (threshold value of P=0.05) (c). DED-only, dry eye group; G-only, glaucoma group; G-DED, glaucoma with dry eye group; L, left eye; R, right eye.
Fig. 5.
Fig. 5.. Bray–Curtis dendrogram of left and right eye microbiota of each participant based on the Bray–Curtis dissimilarity. >0.6, high dissimilarity score; <0.6, low dissimilarity score. DED-only, dry eye group; G-only, glaucoma group; G-DED, glaucoma with dry eye group; L, left eye; R, right eye.
Fig. 6.
Fig. 6.. Boxplot visualizing the alpha diversity [based, respectively, on the Shannon index (a) and Simpson index (b)] and richness [based on the Chao1 index (c)], tested by the t-test (threshold value of P=0.05). NMDS model (d) based on a Bray–Curtis dissimilarity matrix, with data projected into three-dimensional space (K=3) and a model stress of 0.1028451, tested by adonis2 (threshold value of P=0.05). F, female; M, male.
Fig. 7.
Fig. 7.. A synthetic representation of the alteration in OSM in patients with glaucoma and DED.

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