Differences in the eyelid and buccal microbiome of glaucoma patients receiving long-term administration of prostaglandin analog drops

Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

Effects of Carboxymethylcellulose Artificial Tears on Ocular Surface Microbiome Diversity and Composition, A Randomized Controlled Trial

Purpose

Carboxymethylcellulose is an artificial tear ingredient known to decrease gut microbiome diversity when ingested. This study examines the effect of carboxymethylcellulose on ocular surface microbiome diversity and composition.

Methods

Healthy adult participants without significant ophthalmic disease or concurrent carboxymethylcellulose artificial tear use were allocated randomly to take carboxymethylcellulose or control polyethylene glycol artificial tears for seven days. Conjunctival swabs were collected before and after artificial tear treatment. This trial is registered at clinicaltrials.gov (NCT05292755). Primary outcomes included abundance of bacterial taxa and microbiome diversity as measured by the Chao-1 richness estimate, Shannon's phylogenetic diversity index, and UniFrac analysis. Secondary outcomes included Ocular Surface Disease Index scores and artificial tear compliance.

Results

Of the 80 enrolled participants, 66 completed the trial. Neither intervention affected Chao-1 richness (analysis of variance [ANOVA], P = 0.231) or Shannon's diversity index (ANOVA, P = 0.224). Microbiome samples did not separate by time point (permutation multivariate analysis of variance [PERMANOVA], P = 0.223) or intervention group (PERMANOVA, P = 0.668). LEfSe taxonomic analysis revealed that carboxymethylcellulose depleted several taxa including Bacteroides and Lachnoclostridium, but enriched Enterobacteriaceae, Citrobacter, and Gordonia. Both interventions decreased OSDI scores (Wilcoxon signed rank test, P < 0.05), but there was no significant difference between interventions (Mann-Whitney U, P = 0.54).

Conclusions

Carboxymethylcellulose artificial tears increased Actinobacteriota but decreased Bacteroides and Firmicutes bacteria. Carboxymethylcellulose artificial tears do not affect ocular surface microbiome diversity and are not significantly more effective than polyethylene glycol artificial tears for dry eye treatment.

Translational Relevance

The 16S microbiome analysis has revealed small changes in the ocular surface microbiome associated with artificial tear use.

Validation of 16S rRNA Gene Sequencing of the Periocular Microbiome and Lack of Alteration by Topical Eyedrops

Purpose

Genomic techniques for characterizing the ocular microbiome require further validation. We compared the microbiome of patients' eyelids through both conventional culture and 16S rRNA analysis and analyzed the impact of eyedrop use on microbiome diversity.

Methods

Ninety-eight patients followed for management of glaucoma or suspicion of glaucoma had eyelid swabs performed with Isohelix MS Mini DNA Swabs (98 participants) and ESwabs (49 participants) for 16S rRNA analysis and conventional culture, respectively. The effect of preservative-containing eyedrops on the microbiomes detected using these two techniques were analyzed and compared across techniques.

Results

Forty-five of the 50 (non-unique) genera (90%) identified by conventional culture were also identified by each individual's 16S rRNA analysis within the top 14 most abundant organisms present based on operational taxonomic unit. All conventional cultures performed had at least one or more genera also identified by each participant's 16S rRNA analysis. There was no difference in the conventional culture positivity rate or proportion of participants with a particular genus present on conventional culture based on whether preservative-containing eyedrops were regularly used. Similarly, in eyes using versus not using eyedrops, no differences were observed in the proportions of participants with a particular genus present or the Shannon index as determined by 16S rRNA analysis.

Conclusions

16S rRNA analysis correlates well with conventional culture results for the eyelid microbiome, with results from neither technique demonstrating an association of microbiome composition and eyedrop use. The clinical relevance of the large numbers of microbes detected via 16S rRNA analysis requires further study.

Translational Relevance

16S rRNA analysis of the periocular microbiome is consistent with conventional culture and enables further study of physiologic and pathologic ocular processes possibly related to microbiome diversity.

Topical Glaucoma Therapy Is Associated With Alterations of the Ocular Surface Microbiome

Purpose

To investigate the ocular surface microbiome of patients with unilateral or asymmetric glaucoma being treated with topical ophthalmic medications in one eye and to determine whether microbial community changes were related to measures of ocular surface disease.

Methods

V3-V4 16S rRNA sequencing was conducted on ocular surface swabs collected from both eyes of 17 subjects: 10 patients with asymmetric/unilateral glaucoma using topical glaucoma therapy on only one eye and seven age-matched, healthy controls with no history of ocular disease or eyedrop use. Samples were categorized into three groups: patients’ glaucomatous eye treated with eyedrops, patients’ contralateral eye without eyedrops, and healthy control eyes. Comparisons were made for microbial diversity and composition, with differences in composition tested for association with ocular surface disease measures including tear meniscus height, tear break-up time, and Dry Eye Questionnaire.

Results

Samples obtained from the patients’ treated and untreated eyes both had significantly greater alpha-diversity and relative abundance of gram-negative organisms compared to healthy controls. The microbial composition of patient eyes was associated with decreased tear meniscus height and tear break-up time, whereas metagenomic predictions, based on 16S rRNA data, suggested increased synthesis of lipopolysaccharide.

Conclusions

The ocular surface microbiome of patients taking unilateral preserved glaucoma drops is characterized by a highly diverse array of gram-negative bacteria that is significantly different from the predominantly gram-positive microbes detected on healthy control eyes. These compositional differences were associated with decreased tear film measures and distinct inferred protein synthesis pathways, suggesting a potential link between microbial alterations and ocular surface inflammation.

16S rRNA nanopore sequencing for the diagnosis of ocular infection: a feasibility study

Objective

We conducted a feasibility study to verify the effectiveness of 16S ribosomal RNA (rRNA) gene analysis using the nanopore sequencer MinION for identifying causative bacteria in several types of ocular infections.

Methods and Analysis

Four cases of corneal ulcers, one case of endophthalmitis and one case of a conjunctival abscess were included in this study. DNA was extracted from corneal scraping, vitreous samples and secretions from the conjunctival abscess. We conducted 16S rRNA gene amplicon sequencing using MinION and metagenomic DNA analysis. The efficacy of bacterial identification was verified by comparing the conventional culture method with smear observations.

Results

16S rRNA gene sequencing analysis with MinION identified the causative organisms promptly with high accuracy in approximately 4 hours, from ophthalmic specimens. The results of the conventional culture method and 16S rRNA gene sequencing were consistent in all cases. In four of the six cases, a greater variety of organisms was found in the 16S rRNA gene analysis than in bacterial culture.

Conclusion

Using our workflow, 16S rRNA gene analysis using MinION enabled rapid and accurate identification possible in various kinds of bacterial ocular infections.

The microbiomes of the eyelid and buccal area of patients with uveitic glaucoma

Background

The microbiome could trigger inflammation leading to epigenetic changes and is involved in the pathophysiology of eye diseases; however, its effect on uveitic glaucoma (UG) has not been fully investigated. This study analysed the differences in eyelid and buccal microbiomes in patients with UG using next-generation sequencing.

Methods

The eyelid and buccal specimens of 34 UG and 25 control patients were collected. The taxonomic composition of the microbiome was obtained via 16S ribosomal DNA sequencing. Diversity and differential gene expression analyses (DEG) determined taxon differences between the microbiomes of UG and control groups.

Results

In both the eyelid and buccal microbiomes, alpha-diversity was lower in UG patients than controls, while beta-diversity in patients with UG was higher than in controls. DEG analysis of the eyelid microbiome revealed various taxa differences, including enrichment of Paenibacillus and Dermacoccus (p-value, 1.31e⁻⁶ and 1.55e⁻⁷, respectively) and depletion of Morganella and Lactococcus (p-value, 6.26e⁻¹² and 2.55e⁻⁶, respectively) in patients with UG. In the buccal microbiome, taxa such as Lactococcus was significantly depleted (p-value, 1.31e⁻¹⁷), whereas Faecalibacterium was enriched in patients with UG (p-value, 6.12e⁻⁸).

Conclusions

The eyelid and buccal microbiomes in patients with UG differ from controls, which raises concerns surrounding environmental influences on the pathogenesis of UG. The reduced Lactococcus in the eyelid and buccal area suggest that microbiota dysbiosis is associated with UG.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12886-022-02395-x.

The gut microbiota in retinal diseases

The gut microbiota is a complex ecosystem that inhabits the gastrointestinal tract and consists of archaea, fungi, viruses, and bacteria, with bacteria being dominant. From birth onwards, it coevolves dynamically together with the host. The composition of the gut microbiota is under the influence of a complex interplay between both host and environmental factors. Scientific advances in the past few decades have shown that it is essential in maintaining homeostasis and tipping the balance between health and disease. In addition to its role in food digestion, the gut microbiota is implicated in regulating multiple physiological processes in the host gut mucosa and in distant organs such as the brain. Persistent imbalance between gut microbial communities, termed "dysbiosis," has been associated with several inflammatory and metabolic diseases as well as with central nervous system disorders. In this review, we present the state of the art of current knowledge on an emerging concept, the microbiota-retina axis, and the potential role of its disturbance in the development of retinopathies. We also describe several microbiota-targeting strategies that could constitute preventive and therapeutic tools for retinopathies.