Ocular surface microbiota dysbiosis contributes to the high prevalence of dry eye disease in diabetic patients

Figures & data

Table 1. Studies comparing the OSM between patients with DED and healthy people using 16S rRNA gene sequencing.

Source	Country	Group (number)	Characteristic of DED	Age (years)	Sample collection	Dominant bacteria and their relative abundance in DED		Microbiota changes in DED compared with healthy people
						Phylum	Genus	Phylum	Genus
Zhang et al. (2021)	China	DED (n = 37) Control (n = 22)	DM-DED	DED: Male: 59.4 ± 3.5; Female: 62.5 ± 4.8 Control: Male: 56.8 ± 3.4; Female: 53.9 ± 4.5	Schirmer test strips were placed at the outer one-third of the temporal canthus of each eye for 5 min without anaesthesia	Proteobacteria 44.90% Firmicutes 31.84% Actinobacteria 9.31% Bacteroidetes 4.55%	Ochrobactrum 22.47% Corynebacterium 10.96% Bacillus 9.53% Cupriavidus 5.49% Lactococcus 4.07% Lactobacillus 3.65%	↑: Firmicutes, Bacteroidetes	↑: Amycolatopsis
Li, Gong, et al. (2019)	China	DED (n = 35) Control (n = 54)	DED	DED: 57 ± 14 Control: 52 ± 16	After topical anaesthesia, sterile dry cotton swabs were used to wipe the upper and lower palpebral, caruncle, and fornix conjunctiva of a random eye	Proteobacteria 47.62% Firmicutes 17.20% Bacteroidetes 16.54% Actinobacteria 6.24%	Pseudomonas 11.49% Acinetobacter 7.79% Bacillus 7.10% Chryseobacterium 2.25% Corynebacterium 2.61%	↑: Bacteroidetes ↓: Proteobacteria	↓: Pseudomonas
Dong et al. (2019)	China	DED (n = 47) Control (n = 42)	MGD	DED: 57.53 ± 15.10 Control: 62.76 ± 9.73	After topical anaesthesia, sterile dry cotton swabs were used to wipe the upper and lower conjunctival sac and eyelid margins of a random eye two times	Actinobacteria 34.17% Firmicutes 31.70% Proteobacteria 27.46% Bacteroidetes 2.21%	Staphylococcus 20.71% Corynebacterium 20.22% Propionibacterium 9.29% Sphingomonas 5.73% Snodgrassella 4.17% Streptococcus 2.80%	↑: Proteobacteria, Firmicutes ↓: Actinobacteria	↑: Sphingomonas, Staphylococcus ↓: Corynebacterium
Kittipibul et al. (2020)	Thailand	DED (n = 20) Control (n = 20)	SJS	DDE: 44.5 (20 ∼ 77) Control: 44.2 (24 ∼ 77)	After topical anaesthesia, sterile cotton swabs were applied from the medial to the lateral part of inferior fornix of the conjunctival sac of the worse eye three times without touching the eyelids or symblepharon area	Proteobacteria 34.8% Firmicutes 23.8% Bacteroidetes 13.1% Tenericutes 11.9% Actinobacteria 9.8%	NA	NA	↑: Acinetobacter, Bacillus, Bacteroides, Lactobacillus, Pseudomonas, Staphylococcus, Streptococcus

MGD: meibomian gland dysfunction; SJS: Stevens-Johnson syndrome; ↑: increased relative abundance; ↓: decreased relative abundance.

Figure 1. The “high glucose-OSM dysbiosis” pathway in the pathogenesis of DM-DED. Red lines refer to how a high-glucose environment leads to OSM dysbiosis, while green solid lines refer to how OSM dysbiosis contributes to the pathogenesis of DM-DED. Green dotted lines refer to the possible mechanisms that remain to be investigated. The high-glucose ocular surface environment leads to OSM dysbiosis in DM-DED through multiple pathways. (a) High glucose content offers sufficient energy for microbial growth. (b) Hyperosmolarity and the formation of AGEs induce ocular inflammation, which leads to massive microbial death. (c) Reduced blinking frequency delays the clearance of substances on the ocular surface. (d) Lacrimal gland dysfunction causes the reduced antibacterial activity of tears. Then, OSM dysbiosis (1) promotes ocular surface inflammation and (2) alters tear composition, which contributes to the pathogenesis of DM-DED. In addition, the OSM may also influence the homeostasis of the ocular surface by interacting with the ocular surface nervous system and converting hormones.

Zhang Z, Zou X, Xue W, Zhang P, Wang S, Zou H. 2021. Ocular surface microbiota in diabetic patients with dry eye disease. Invest Ophthalmol Vis Sci. 62(12):13.

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Li S, Yi G, Peng H, Li Z, Chen S, Zhong H, Chen Y, Wang Z, Deng Q, Fu M, et al. 2019. How ocular surface microbiota debuts in type 2 diabetes mellitus. Front Cell Infect Microbiol. 9:202.

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Dong X, Wang Y, Wang W, Lin P, Huang Y. 2019. Composition and diversity of bacterial community on the ocular surface of patients with meibomian gland dysfunction. Invest Ophthalmol Vis Sci. 60(14):4774–4783.

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Kittipibul T, Puangsricharern V, Chatsuwan T. 2020. Comparison of the ocular microbiome between chronic Stevens-Johnson syndrome patients and healthy subjects. Sci Rep. 10(1):4353.

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