Composition and Diversity of Bacterial Community on the Ocular Surface of Patients With Meibomian Gland Dysfunction

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

PURPOSE

To investigate the differences in the eyelid and buccal microbiomes between patients receiving long-term prostaglandin analogs for open-angle glaucoma (PG-OAG) and naïve-OAG patients by using metagenomics.

METHODS

Eyelid and buccal samples were collected from 30 PG-OAG and 32 naïve-OAG patients. The taxonomic composition of the microbiome was obtained via 16S rRNA gene sequencing, operational taxonomic unit analysis, and diversity analysis. Differential gene expression analysis (DEG) and Bland-Altman (MA) plots were used to determine taxon differences between the microbiomes of PG-OAG and naïve-OAG patients.

RESULTS

The eyelid microbiome showed marginally significant differences, while the alpha-diversity of the buccal microbiome showed significant differences between PG-OAG and naïve-OAG patients. However, the beta-diversity of both eyelid and buccal microbiomes was higher in PG-OAG patients than in naïve-OAG patients. The MA plot showed cluster differences in the eyelid microbiome. DEG analysis of the eyelid microbiome revealed various taxa differences, including enrichment of Azomonas, Pseudomonas, and Granulicatella in PG-OAG patients over naïve-OAG patients, as well as significant depletion of Delftia and Rothia. In the buccal microbiome in PG-OAG patients, taxa such as Rikenella and Stenotrophomonas were significantly enriched.

CONCLUSION

Our findings suggest that the eyelid microbiome differs between PG-OAG and naïve-OAG patients, raising concerns regarding the eyelid environment in patients receiving these drugs. The overexpressed microbiome in the eyelid area suggests that microbiota may change after the administration of glaucoma medications in OAG.

Comparative analysis of ocular surface tissue microbiome in human, mouse, rabbit, and guinea pig

Animal models are a critical element of ocular surface research for investigating therapeutic drops, surgical implants, and infection research. This study was a comparative analysis of the microbial communities on conjunctival tissue samples from humans compared to several commonly used laboratory animals (BALB/c mice, New Zealand white rabbits and IMVS colored stock guinea pigs). Microbial communities were analyzed by extracting total DNA from conjunctival tissue and sequencing the 16 S rRNA gene using the Illumina MiSeq platform. Sequences were quality filtered using the UNOISE pipeline in USEARCH and taxonomically classified using GTDB database. Sequences associated with blank extraction and sampling negative controls were removed with the decontam R software package prior to downstream analysis. There was a difference in the diversity measures of richness (P = 0.0124) and Shannon index (P = 0.0002) between humans and rabbits but not between human, mouse and guinea pigs. There was a difference between the human and any animal for bacterial community structure (P = 0.006). There was a higher degree of similarity between the bacterial composition of the human and mouse samples with each dominated by the phyla Proteobacteria and Firmicutes. The use of mouse models may be more appropriate for studies investigating changes to the ocular microbiome due to interventions such as application of antibiotics due to greater similarities in bacterial community structure and composition to humans.

Effects of lid debris debridement combined with meibomian gland expression on the ocular surface MMP-9 levels and clinical outcomes in moderate and severe meibomian gland dysfunction

Background

To evaluate the effects of lid debris debridement and meibomian gland expression (MGX) on extracellular matrix metalloproteinase-9 (MMP-9) levels and clinical outcomes of moderate and severe MGD.

Methods

In this retrospective case series study, a total 48 eyes of 24 patients with moderate and severe MGD underwent one session of lid debris debridement using the BlephEx combined with MGX. We evaluated the tear film break-up time (TBUT), corneal and conjunctival fluorescein staining scores, Schirmer 1 test, biomicroscopic examination of lid margins and meibomian gland (MG), ocular surface disease index (OSDI) questionnaire score, and extracellular MMP-9 levels using a point-of-care MMP-9 immunoassay device before and 4 weeks after lid debris debridement and MGX. Linear mixed model and generalized estimating equations model were used to evaluate possible differences.

Results

There were significant improvements in the TBUT (P = 0.002), SICCA and Oxford staining scores (all P < 0.001), lid margin telangiectasia (P < 0.001 for upper and lower eyelids), lid thickness (P < 0.001 for upper and lower eyelids), MG orifice plugging (P < 0.001 for upper and lower eyelids), meibum color (P = 0.026 for upper eyelid, P < 0.001 for lower eyelid), meibum consistency (P < 0.001 for upper and lower eyelids), meibum grade (P < 0.001), MGD stage (P < 0.001), and OSDI score (P = 0.002). MMP-9 immunoassay positivity rate significantly decreased from 83.3 to 50.0% 4 weeks after treatment (P = 0.014).

Conclusions

In patients with moderate to severe MGD, lid debris debridement using the BlephEx combined with MGX improved clinical findings, subjective symptoms, meibomian gland function, along with ocular surface MMP-9 level. We hereby suggest lid debris debridement using BlephEx combined with MGX as an effective clinical strategy for treatment of moderate to severe MGD.

The ocular microbiome and microbiota and their effects on ocular surface pathophysiology and disorders

The ocular surface flora perform an important role in the defense mechanisms of the ocular surface system. Its regulation of the immunological activity and the barrier effect against pathogen invasion are remarkable. Composition of the flora differs according to the methods of investigation, because the microbiome, composed of the genetic material of bacteria, fungi, viruses, protozoa, and eukaryotes on the ocular surface, differs from the microbiota, which are the community of microorganisms that colonize the ocular surface. The observed composition of the ocular surface flora depends on harvesting and examining methods, whether with traditional culture or with more refined genetic analysis based on rRNA and DNA sequencing. Environment, diet, sex, and age influence the microbial flora composition, thus complicating the analysis of the baseline status. Moreover, potentially pathogenic organisms can affect its composition, as do various disorders, including chronic inflammation, and therapies applied to the ocular surface. A better understanding of the composition and function of microbial communities at the ocular surface could bring new insights and clarify the epidemiology and pathology of ocular surface dynamics in health and disease. The purpose of this review is to provide an up-to-date overview of knowledge about this topic.

Microbes of the human eye: Microbiome, antimicrobial resistance and biofilm formation

BACKGROUND

The review focuses on the bacteria associated with the human eye using the dual approach of detecting cultivable bacteria and the total microbiome using next generation sequencing. The purpose of this review was to highlight the connection between antimicrobial resistance and biofilm formation in ocular bacteria.

METHODS

Pubmed was used as the source to catalogue culturable bacteria and ocular microbiomes associated with the normal eyes and those with ocular diseases, to ascertain the emergence of anti-microbial resistance with special reference to biofilm formation.

RESULTS

This review highlights the genetic strategies used by microorganisms to evade the lethal effects of anti-microbial agents by tracing the connections between candidate genes and biofilm formation.

CONCLUSION

The eye has its own microbiome which needs to be extensively studied under different physiological conditions; data on eye microbiomes of people from different ethnicities, geographical regions etc. are also needed to understand how these microbiomes affect ocular health.

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

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%.

Alterations in the Ocular Surface Microbiome in Traumatic Corneal Ulcer Patients

Purpose

Corneal ulcers are a common eye inflammatory disease that can cause visual impairment or even blindness if not treated promptly. Ocular trauma is a major risk factor for corneal ulcers, and corneal trauma in agricultural work can rapidly progress to corneal ulcers. This study aims to evaluate the changes in the ocular surface (OS) microbiome of patients with traumatic corneal ulcer (TCU).

Methods

Among 20 healthy control (HC) subjects and 22 patients with TCU, 42 eyes were examined to investigate the OS microbial flora using metagenomic shotgun sequencing.

Results

At the taxonomic composition level, our findings showed that dysbiosis (alterations in richness and community structure) occurs in the OS microbiome of patients with TCU. Notably, Pseudomonas was present at a greater than 30% relative abundance in all individuals in the TCU group. At the species level, the abundance of Pseudomonas fluorescens and Pseudomonas aeruginosa was significantly elevated in the TCU group compared to the HC group. At the functional level, we identified significant differences in the HC and TCU groups. We observed that inflammation-related pathways involved in bacterial chemotaxis, flagellar assembly, and biofilm formation were significantly more abundant in the TCU group. Besides, the pathways related to biosynthesis, degradation, and metabolism were also increased significantly in the TCU group.

Conclusions

These findings indicate an altered OS microbiome in the affected eyes of patients with TCU. Further research is needed to determine whether these alterations contribute to the pathogenesis of TCU or impact disease progression.

Ocular Microbiota and Intraocular Inflammation

The term ocular microbiota refers to all types of commensal and pathogenic microorganisms present on or in the eye. The ocular surface is continuously exposed to the environment and harbors various commensals. Commensal microbes have been demonstrated to regulate host metabolism, development of immune system, and host defense against pathogen invasion. An unbalanced microbiota could lead to pathogenic microbial overgrowth and cause local or systemic inflammation. The specific antigens that irritate the deleterious immune responses in various inflammatory eye diseases remain obscure, while recent evidence implies a microbial etiology of these illnesses. The purpose of this review is to provide an overview of the literature on ocular microbiota and the role of commensal microbes in several eye diseases. In addition, this review will also discuss the interaction between microbial pathogens and host factors involved in intraocular inflammation, and evaluate therapeutic potential of targeting ocular microbiota to treat intraocular inflammation.

Research Trends and Hotspot Analysis of Conjunctival Bacteria Based on CiteSpace Software

OBJECTIVE

To sort out the literature related to conjunctival bacteria and summarize research hotspots and trends of this field.

MATERIALS AND METHODS

The relevant literature data from 1900 to 2019 was retrieved from the Web of Science Core Collection database. After manual selection, each document record includes title, author, keywords, abstract, year, organization, and citation. We imported the downloaded data into CiteSpace V (version 5.5R2) to draw the knowledge map and conduct cooperative network analysis, discipline and journal analysis, cluster analysis, and burst keyword analysis.

RESULTS

After manual screening, there were 285 relevant papers published in the last 28 years (from 1991 to 2019), and the number is increasing year by year. The publications of conjunctival bacteria were dedicated by 1381 authors of 451 institutions in 56 countries/regions. The United States dominates this field (82 literatures), followed by Germany (23 literatures) and Japan (23 literatures). Overall, most cited papers were published with a focus on molecular biology, genetics, nursing, and toxicology. Most papers fall into the category of ophthalmology, veterinary sciences, and pharmacology and pharmacy. The only organized cluster is the "postantibiotic effect," and the top 5 keywords with the strongest citation bursts include "postoperative endophthalmiti(s)," "infectious keratoconjunctiviti(s)," "conjunctiviti(s)," "resistance," and "diversity".

CONCLUSION

The global field of conjunctival bacteria has expanded in the last 28 years. The United States contributes most. However, there are little cooperation among authors and institutions. Overall, this bibliometric study organized one cluster, "postantibiotic effect", and identified the top 5 hotspots in conjunctival bacteria research: "postoperative endophthalmiti(s)," "infectious keratoconjunctiviti(s)," "conjunctiviti(s)," "resistance," and "diversity". Thus, further research focuses on these topics that may be more helpful to prevent ocular infection and improve prophylaxis strategies to bring a benefit to patients in the near future.

Ocular surface microbiota in patients with aqueous tear-deficient dry eye

PURPOSE

An altered ocular surface microbiota may contribute to the pathophysiology of dry eye disease. The aim of the study was to explore potential differences in microbiota diversity and composition in aqueous tear-deficient dry eye (with and without ocular graft-versus-host disease) compared with controls.

METHODS

Swab samples from the inferior fornix of the conjunctiva were obtained from patients with aqueous tear-deficient dry eye with and without ocular graft-versus-host disease (n = 18, n = 21, respectively) and controls (n = 28). Isolated bacterial DNA from swabs were analyzed with 16S rRNA gene amplicon sequencing.

RESULTS

Decreased microbiota diversity was observed in patients with aqueous tear-deficient dry eye (p ≤ 0.003) who also showed a difference in microbiota composition compared with controls (p = 0.001). Although several genera were less abundant in aqueous tear-deficient dry eye, a minimal core ocular surface microbiota comprising five genera was shared by >75% of the study participants: Enhydrobacter, Brevibacterium, Staphylococcus, Streptococcus and Cutibacterium. Pseudomonas was identified as a bacterial biomarker for controls and Bacilli for patients with aqueous tear-deficient dry eye.

CONCLUSIONS

Ocular surface microbiota in patients with aqueous tear-deficient dry eye was characterized by an aberrant microbiota composition in comparison to controls, with decreased diversity and reduced relative abundances of several genera. Additionally, a few genera were present in most of the study population, indicating that a minimal core ocular surface microbiota may exist.

Homeostasis and Defense at the Surface of the Eye. The Conjunctival Microbiota

The literature on ocular microbiome has grown tremendously over the past decade, and our knowledge of the different aspects and roles in homeostasis and protection is continuously growing. The development of 16 S rRNA sequencing has allowed the field to characterize communities of bacteria in health and ocular disease. Efforts should continue to further elucidate the interplay between microbiome and key players, such as age, comorbidities, and contact lens usage in order to have better control of the sight-threatening complications.