Role of the ocular surface microbiome in allergic disease

Cavuoto, Kara M.; Stradiotto, Allison

doi:10.1097/aci.0000000000000559

Cited by 17 publications

(11 citation statements)

References 58 publications

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“…The large fall out of articles was partly due to a high yield of research on the flower iris (publications n = 549) and publications on veterinarian topics (publications n = 859). Based on the inclusion criteria, 76 articles were included: 35 reported on original research (27 on human ocular surface amplicon sequencing, 5 on murine ocular surface amplicon sequencing (Terzulli et al 2015; de Paiva et al 2016; Kugadas et al 2016; St. Leger et al 2017; Wan et al 2018), 1 on intra‐ocular amplicon sequencing and 2 publications using shotgun sequencing), 14 reviews (Willcox 2013; Zegans & Van Gelder 2014; Kugadas & Gadjeva 2016; Lu & Liu 2016; Boost et al 2017; St. Leger & Caspi 2018; Wen et al 2018; Baim et al 2019; Borroni et al 2019; Gallon et al 2019; Watane et al 2019; Cavuoto et al, 2019a, 2019b, 2019c; Ozkan & Willcox 2019) and 27 abstracts (summarized in Table ). When taking into account only amplicon sequencing research on human ocular surface, there is an evident increase in original publications since 2016 (Fig.…”

Section: Resultsmentioning

confidence: 99%

Current knowledge on the human eye microbiome: a systematic review of available amplicon and metagenomic sequencing data

Delbeke

Younas

Casteels

et al. 2020

Acta Ophthalmologica

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Insights in the ocular surface microbiome are still at an early stage and many more questions remain unanswered compared with other human‐associated microbial communities. The current knowledge on the human microbiome changed our viewpoint on bacteria and human health and significantly enhanced our understanding of human pathophysiology. Also in ocular medicine, microbiome research might impact treatment. Here, we summarize the current knowledge on ocular microbiome research with a particular focus on potential confounding factors and their effects on microbiome composition. Moreover, we present the ocular surface core microbiome based on current available data and defined it as genera present in almost half of the published control cohorts with a relative abundance of at least 1%.

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Section: Resultsmentioning

confidence: 99%

Current knowledge on the human eye microbiome: a systematic review of available amplicon and metagenomic sequencing data

Delbeke

Younas

Casteels

et al. 2020

Acta Ophthalmologica

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“… 24 However, diseases may change the microbiota composition of the OS, negatively affecting the protective role of the microbiota and causing it to be harmful. 21 , 25 – 27 …”

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confidence: 99%

Ocular Surface Microbiota in Diabetic Patients With Dry Eye Disease

Zhang

Zou²,

Xue

et al. 2021

Invest. Ophthalmol. Vis. Sci.

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Purpose To investigate the ocular surface (OS) commensal bacteria profiles of patients with diabetes mellitus (DM) and dry eye disease (DED). Methods In the present study, subjects were assigned to four groups: 37 to the diabetic mellitus with dry eye disease (DM with DED) group, 22 to the diabetes mellitus (DM)-only group, 34 to the dry eye disease (DED)-only group, and 22 to the control group. Tear fluid was collected using Schirmer's tear secretion test paper. 16S ribosomal ribonucleic acid (rRNA) gene sequencing was used to analyze the bacterial microbiota. Results The DM with DED group showed the highest operational taxonomic unit (OTU) numbers and alpha diversity and the most different beta diversity. The groups shared the four most abundant phyla, accounting for over 96% of the total abundance. At the genus level, there were 10 types of overlap in the core microbiota in the groups. They showed significant differences between the groups. Additionally, the DM with DED group and the control group showed four unique core genera, respectively. Unclassified Clostridiales and Lactobacillus were the core microbiota members of the DM with DED group, the DM-only group, and the DED-only group, but not the control group. Conclusions In the present study, our results showed that the patients in the DM with DED group had a more complex and comprehensive ocular surface microbial composition. To the best of our knowledge, this is the first study to reveal the microbial profile of dry eye disease in patients with diabetes mellitus.

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“…Numerous studies have shown a close relationship of dysbiosis and development of allergic disease in different anatomical areas (12). In particular, several studies have related skin diseases, such as psoriasis and atopic dermatitis, to abundances of certain fungal and bacterial species, including Kocurias and Malassezia (34)(35)(36).…”

Section: The Microbiota's Contribution To Allergic Conjunctivitismentioning

confidence: 99%

“…Finally, the other main player emerging in recent years is the resident microbiota and its contribution to inflammatory response ( 10 ). Some authors report the existence of a kind of symbiosis between commensal microbiota, lymphocytes and epithelial cells ( 11 ) and suggest that the allergic response may be influenced by an ocular surface dysbiosis (microbial imbalance) affecting their physiology and integrity ( 12 ).…”

Section: Introductionmentioning

confidence: 99%

Conjunctival Intraepithelial Lymphocytes, Lacrimal Cytokines and Ocular Commensal Microbiota: Analysis of the Three Main Players in Allergic Conjunctivitis

et al. 2022

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Conjunctival intraepithelial lymphocytes, tear soluble molecules and commensal microbiota have important roles in the ocular mucosal immune response in healthy and diseased subjects. For the purpose of this study, the cellular and microbial populations of the conjunctiva and the lacrimal soluble molecules were analyzed to find the main biomarkers in allergic conjunctivitis. A total of 35 healthy subjects, 28 subjects with seasonal allergic conjunctivitis and 32 subjects with perennial allergic conjunctivitis were recruited to obtain peripheral blood, conjunctival brush cytology, tear fluid and microbiota samples. Flow cytometry for lymphocytes, multiplex bead assays for cytokines and high-throughput DNA sequencing for microbiome analysis were used. For perennial allergic conjunctivitis, an increased proportion of Th2 and NKT lymphocytes was found, while CD3+TCRγδ+ lymphocytes and double negative MAIT cells were decreased. In contrast, seasonal allergic conjunctivitis was distinguished by an increase in Th17 and Th22 cell proportions, while the Th1 cell proportion decreased. Among tear fluid, the vast majority of pro-inflammatory cytokines (especially Th2 and Th17 cytokines) in perennial allergies and MMP-9 together with IgA in seasonal allergies were increased. In contrast, TGF-β2 was decreased in both forms of conjunctivitis. Finally, fungal (Malassezia species) and bacterial (Kocuria and Propionobacterium acnes species) colonization were observed in the perennial allergic conjunctivitis group. These results provide the basis for the development of a disease profile for perennial allergic conjunctivitis and open the door to new therapeutic and diagnostic strategies.

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Role of the ocular surface microbiome in allergic disease

Cited by 17 publications

References 58 publications

Current knowledge on the human eye microbiome: a systematic review of available amplicon and metagenomic sequencing data

Current knowledge on the human eye microbiome: a systematic review of available amplicon and metagenomic sequencing data

Ocular Surface Microbiota in Diabetic Patients With Dry Eye Disease

Conjunctival Intraepithelial Lymphocytes, Lacrimal Cytokines and Ocular Commensal Microbiota: Analysis of the Three Main Players in Allergic Conjunctivitis

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