Comparison of the ocular surface microbiota between thyroid-associated ophthalmopathy patients and healthy subjects

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

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.

Multi-cohort analysis identifying core ocular surface microbiome and bacterial alterations in eye diseases

PURPOSE

Inconsistency exists among reported studies on the composition of human ocular surface microbiome (OSM). The roles of OSM in ocular diseases remain uncertain. In this study, we aimed to determine the composition of OSM and to evaluate its potential roles and functions from multiple cohorts.

METHODS

Raw 16 s sequencing data were obtainable from publicly available repositories, sourced from 17 published studies. Employing a standardized method, we processed the data and conducted a cross-cohort analysis. Through bioinformatics pipelines QIIME2 and PICRUSt2, we processed a total of 1875 ocular surface samples. Core microbiome analyses, genera comparisons, and MetaCyc pathway analyses were performed within each cohort independently. The results were then combined to identify shared patterns across different datasets.

RESULTS

The core OSM comprised seven genera: Corynebacterium, Staphylococcus, Acinetobacter, Streptococcus, Pseudomonas, Cutibacterium and Bacillus. Corynebacterium and Staphylococcus are the most abundant genera on ocular surface. Most ocular diseases showed OSM alterations and eight genera demonstrated a non-specific, shared response among two or more ocular diseases. Moreover, changes in various metabolic pathways were predicted following OSM alteration, indicating potential roles of OSM in biological processes.

CONCLUSION

We refined the core OSM candidates combining multiple cohorts. The common pattern shared by different cohorts is worth further investigation. Changes in metabolic pathways based on bioinformatic analysis indicated a role of OSM on ocular diseases. Our results help extend the knowledge and encourage further investigations on the associations between OSM and ocular diseases.

Multi-Omics Approaches to Discover Biomarkers of Thyroid Eye Disease: A Systematic Review

Thyroid eye disease (TED) is an organ-specific autoimmune disorder that significantly impacts patients' visual function, appearance, and well-being. Despite existing clinical evaluation methods, there remains a need for objective biomarkers to facilitate clinical management and pathogenesis investigation. Rapid advances in multi-omics technologies have enabled the discovery and development of more informative biomarkers for clinical use. This systematic review synthesizes the current landscape of multi-omics approaches in TED research, highlighting the potential of genomics, transcriptomics, proteomics, metabolomics, and microbiomics to uncover novel biomarkers. Our review encompasses 69 studies involving 1,363 TED patients and 1,504 controls, revealing a wealth of biomarker candidates across various biological matrices. The identified biomarkers reflect alterations in gene expression, protein profiles, metabolic pathways, and microbial compositions, underscoring the systemic nature of TED. Notably, the integration of multi-omics data has been pivotal in enhancing our understanding of TED's molecular mechanisms and identifying diagnostic and prognostic markers with clinical potential.

Bacterial Insights: Unraveling the Ocular Microbiome in Glaucoma Pathogenesis

This review explores the connection between the ocular surface microbiome and glaucoma, highlighting its impact on disease progression. Beginning with an overview of global glaucoma significance, it emphasizes the importance of understanding the cellular characteristics and microbiology of the ocular microbiome. A search was conducted on the PubMed and Cochrane Library databases using the phrase "ocular microbiome glaucoma". 0 records were returned from the Cochrane Library while 21 were returned from PubMed. A total of 21 results were retrieved from 2017 to 2024. This comprised one opinion paper, four original research articles, and 16 reviews. This review covered the anatomy of the ocular surface, advanced analysis methods, and the ocular microbiome. It also delved into dysbiosis in glaucoma, addressing altered microbial communities and their potential role in disease progression. The intricate interplay between the ocular microbiome and the host's immune system is explored, emphasizing crosstalk and inflammatory responses. The review concludes by discussing therapeutic implications, including modulating ocular microbiota and potential future treatment strategies. Understanding the microbiome in healthy and glaucomatous eyes can help researchers and clinicians in innovative approaches to ocular health.

Effects of dietary imbalances of micro- and macronutrients on the ocular microbiome and its implications in dry eye disease

Dry eye disease (DED) is a complex and multifactorial ocular surface disease affecting a large proportion of the population. There is emerging evidence of the impact of the microbiomes of the ocular surface and gut on the symptoms of DED, with many parallels being drawn to inflammatory diseases of other organ systems. A key factor involved in the promotion of healthy microbiomes, and which has been associated with ocular surface disease, is micro- and macronutrient deficiency. A comprehensive review of how these deficiencies can contribute to DED is absent from the literature. This review reports the composition of healthy ocular and gut microbiomes, and how nutrient deficiencies may impact these floral populations, with linkage to the subsequent impact on ocular health. The review highlights that vitamin B1 and iron are linked to reduced levels of butyrate, a fatty acid implicated in inflammatory conditions such as ulcerative colitis which itself is a condition known to be associated with ocular surface diseases. Vitamin B12 has been shown to have a role in maintaining gut microbial eubiosis and has been linked to the severity of dry eye symptoms. Similar beneficial effects of gut microbial eubiosis were noted with vitamin A and omega-3 polyunsaturated fatty acids. Selenium and calcium have complex interactions with the gut microbiome and have both been implicated in the development of thyroid orbitopathy. Further, diabetes mellitus is associated with ocular surface diseases and changes in the ocular microbiome. A better understanding of how changes in both the gut and eye microbiome impact DED could allow for an improved understanding of DED pathophysiology and the development of new, effective treatment strategies.

Alterations of conjunctival microbiota associated with orthokeratology lens wearing in myopic children

BACKGROUND

Orthokeratology (OK) lens wear increases the risk of bacterial infection, but little is known about the microbiota of the conjunctival sac in myopic children wearing OK lenses. This study aimed to investigate the changes of conjunctival microbiota in children after treatment with OK lenses using 16 S rDNA sequencing.

METHODS

Twenty-eight myopic children who had been continuously wearing OK lenses for 12 to 13 months were enrolled in this prospective study. Twenty-two gender- and age-matched myopic children who had not worn OK lenses or discontinued OK lens wear at least 1 year ago were recruited as controls. Conjunctival swabs from each participant were collected for exploration of the microbiota profiles, targeting the V3-V4 regions of the 16 S rRNA gene by MiSeq sequencing. The differences in the microbial community structure and diversity were also compared between groups.

RESULTS

The bacterial alpha diversity indices in the OK lens group were not different from those in the non-wearer group (P > 0.05, Wilcoxon test), while beta diversity examined using principle coordinate analysis of unweighted UniFrac divided the two groups into different clusters. Proteobacteria, Bacteroidetes, and Firmicutes were the abundant phyla in the conjunctival sac microbiota in both groups (P < 0.05, Mann-Whitney U test). Among children in the OK lens group, the Linear discriminant analysis Effect Size identified the compositional changes in OK lens-associated bacteria. Key functional genera such as Blautia, Parasutterella, and Muribaculum were enriched, whereas Brevundimonas, Acinetobacter, Proteus, and Agathobacter decreased significantly (P < 0.05, Mann-Whitney U test). Phylogenetic investigation of communities by reconstruction of unobserved states also showed altered bacterial metabolic pathways in OK lens-associated microbiota. Moreover, using receiver operating characteristic curves, Brevundimonas, Acinetobacter, Proteus, and Agathobacter alone (the area under the curve was all > 0.7500) or in combination (the area under the curve was 0.9058) were revealed to discriminate OK lens wearers from controls.

CONCLUSIONS

The relative abundance of the microbial community in the conjunctival sac of myopic children can alter after OK lens wear. Brevundimonas, Acinetobacter, Proteus, and Agathobacter may be candidate biomarkers to distinguish between OK lens wearers and non-wearers.

Contact lenses and ocular dysbiosis, from the transitory to the pathological

Normal ocular microbiota is composed of different Gram-negative and positive bacterial communities that act as commensals on the ocular surface. An imbalance in the homeostasis of the native species or dysbiosis triggers functional alterations that can eventually lead to ocular conditions, indicating the use of contact lenses as the most relevant predisposing factor. Through a bibliographic review that added scientific articles published between 2018 and 2022, the relationship between healthy ocular microbiota and dysbiosis associated with the use of contact lenses that trigger ocular conditions was analyzed. The ocular microbiota in healthy individuals is mainly composed of bacteria from the phyla: Proteobacteria, Actinobacteria and Firmicutes. These bacterial communities associated with the use of contact lenses develop dysbiosis, observing an increase in certain genera such as Staphylococcus spp. and Pseudomonas spp., which under normal conditions are commensals of the ocular surface, but as their abundance is increased, they condition the appearance of various ocular conditions such as corneal infiltrative events, bacterial keratitis and corneal ulcer. These pathologies tend to evolve rapidly, which, added to late detection and treatment, can lead to a poor visual prognosis. It is suggested that professionals in the ophthalmology area learn about the composition of the communities of microorganisms that make up this ocular microbiota, in order to correctly distinguish and identify the causative agent, thereby providing a adequate and effective treatment to the user.

Comparison of Conjunctival Sac Microbiome between Low and High Myopic Eyes

Microbial communities played a vital role in maintaining homeostasis of ocular surface. However, no studies explored the myopia-associated conjunctiva microbiota changes until now. In this study, conjunctival sac swab specimens were collected from 12 eyes of low myopia (LM), and 14 eyes of high myopia (HM) patients. The V3-V4 region of the 16S rRNA gene was amplified and then sequenced. Statistical analysis was performed to investigate differences in the taxonomy and diversity between two groups. Compared to LM, higher Ocular Surface Disease Index (OSDI) scores were observed in HM group. The Shannon index of the HM was lower than that of the LM group (P = 0.017). Principle coordinate analysis and Partial Least Squares Discrimination Analysis showed distinct microbiome composition between two groups. At the phylum level, there were higher relative abundances of Proteobacteria (68.27% vs 38.51%) and lower abundances of Actinobacteria (3.71% vs 9.19%) in HM, compared to LM group (P = 0.031, 0.010, respectively). At the genus level, the abundances of Acinetobacter in HM (18.16%) were significantly higher than the LM (6.52%) group (P = 0.011). Actinobacteria levels were negatively correlated with the myopic spherical equivalent and OSDI scores. Moreover, positive correlations were found between Proteobacteria levels and OSDI scores, Acinetobacter levels were positively correlated with myopic spherical equivalent and OSDI scores. In conclusion, HM Patients have bacterial microbiota imbalance in the conjunctival sac, compared with LM patients. Proteobacteria, Actinobacteria, Acinetobacter may play roles in the HM associated ocular surface irritation.