The conjunctival microbiome in health and trachomatous disease: a case control study

High-throughput sequencing reveals differences in microbial community structure and diversity in the conjunctival tissue of healthy and type 2 diabetic mice

BACKGROUND

To investigate the differences in bacterial and fungal community structure and diversity in conjunctival tissue of healthy and diabetic mice.

METHODS

RNA-seq assays and high-throughput sequencing of bacterial 16 S rDNA and fungal internal transcribed spacer (ITS) gene sequences were used to identify differentially expressed host genes and fungal composition profiles in conjunctival tissues of diabetic BKS-db/db mice and BKS (control) mice. Functional enrichment analysis of differentially expressed genes and the correlation between the relative abundance of bacterial and fungal taxa in the intestinal mucosa were also performed.

RESULTS

Totally, 449 differential up-regulated genes and 1,006 down-regulated genes were identified in the conjunctival tissues of diabetic mice. The differentially expressed genes were mainly enriched in metabolism-related functions and pathways. A decrease in conjunctival bacterial species diversity and abundance in diabetic mice compared to control mice. In contrast, fungal species richness and diversity were not affected by diabetes. The microbial colonies were mainly associated with cellular process pathways regulating carbohydrate and lipid metabolism, as well as cell growth and death. Additionally, some interactions between bacteria and fungi at different taxonomic levels were also observed.

CONCLUSION

The present study revealed significant differences in the abundance and composition of bacterial and fungal communities in the conjunctival tissue of diabetic mice compared to control mice. The study also highlighted interactions between bacteria and fungi at different taxonomic levels. These findings may have implications for the diagnosis and treatment of diabetes.

Altered ocular surface microbiota in obesity: a case-control study

Purpose

This study aimed to investigate the composition of ocular surface microbiota in patients with obesity.

Methods

This case-control study, spanning from November 2020 to March 2021 at Henan Provincial People's Hospital, involved 35 patients with obesity and an equivalent number of age and gender-matched healthy controls. By employing 16S rRNA sequencing, this study analyzed the differences in ocular surface microbiota between the two groups. The functional prediction analysis of the ocular surface microbiota was conducted using PICRUSt2.

Results

The alpha diversity showed no notable differences in the richness or evenness of the ocular surface microbiota when comparing patients with obesity to healthy controls (Shannon index, P=0.1003). However, beta diversity highlighted significant variances in the microbiota composition of these two groups (ANOSIM, P=0.005). LEfSe analysis revealed that the relative abundances of Delftia, Cutibacterium, Aquabacterium, Acidovorax, Caulobacteraceae unclassified, Comamonas and Porphyromonas in patients with obesity were significantly increased (P<0.05). Predictive analysis using PICRUSt2 highlighted a significant enhancement in certain metabolic pathways in patients with obesity, notably xenobiotics metabolism via cytochrome P450 (CYP450), lipid metabolism, and the oligomerization domain (NOD)-like receptor signaling pathway (P<0.05).

Conclusions

Patients with obesity exhibit a distinct ocular surface core microbiome. The observed variations in this microbiome may correlate with increased activity in CYP450, changes in lipid metabolism, and alterations in NOD-like receptor signaling pathways.

How gut microbiota may impact ocular surface homeostasis and related disorders

Changes in the bacterial flora in the gut, also described as gut microbiota, are readily acknowledged to be associated with several systemic diseases, especially those with an inflammatory, neuronal, psychological or hormonal factor involved in the pathogenesis and/or the perception of the disease. Maintaining ocular surface homeostasis is also based on all these four factors, and there is accumulating evidence in the literature on the relationship between gut microbiota and ocular surface diseases. The mechanisms involved are mostly interconnected due to the interaction of central and peripheral neuronal networks, inflammatory effectors and the hormonal system. A better understanding of the influence of the gut microbiota on the maintenance of ocular surface homeostasis, and on the onset or persistence of ocular surface disorders could bring new insights and help elucidate the epidemiology and pathology of ocular surface dynamics in health and disease. Revealing the exact nature of these associations could be of paramount importance for developing a holistic approach using highly promising new therapeutic strategies targeting ocular surface diseases.

Leger AJ, Galor A. Living with your biome: how the bacterial microbiome impacts ocular surface health and disease

Introduction

Microbiome research has grown exponentially but the ocular surface microbiome (OSM) remains an area in need of further study. This review aims to explore its complexity, disease-related microbial changes, and immune interactions, and highlights the potential for its manipulation as a therapeutic for ocular surface diseases.

Areas Covered

We introduce the OSM by location and describe what constitutes a normal OSM. Second, we highlight aspects of the ocular immune system and discuss potential immune microbiome interactions in health and disease. Finally, we highlight how microbiome manipulation may have therapeutic potential for ocular surface diseases.

Expert Opinion

The ocular surface microbiome varies across its different regions, with a core phyla identified, but with genus variability. A few studies have linked microbiome composition to diseases like dry eye but more research is needed, including examining microbiome interactions with the host. Studies have noted that manipulating the microbiome may impact disease presentation. As such, microbiome manipulation via diet, oral and topical pre and probiotics, and hygienic measures may provide new therapeutic algorithms in ocular surface diseases.

Unique composition of ocular surface microbiome in the old patients with dry eye and diabetes mellitus in a community from Shanghai, China

BACKGROUND

This study investigates the variations in microbiome abundance and diversity on the ocular surfaces of diabetic patients suffering from dry eye within a community setting. The goal is to offer theoretical insights for the community-level prevention and treatment of dry eye in diabetic cohorts.

METHODS

Dry eye screening was performed in the Shanghai Cohort Study of Diabetic Eye Disease (SCODE) from July 15, 2021, to August 15, 2021, in the Xingjing community; this study included both a population with diabetes and a normal population. The population with diabetes included a dry eye group (DM-DE, n = 40) and a non-dry eye group (DM-NoDE, n = 39). The normal population included a dry eye group (NoDM-DE, n = 40) and a control group (control, n = 39). High-throughput sequencing of the 16 S rRNA V3-V4 region was performed on conjunctival swab from both eyes of each subject, and the composition of microbiome on the ocular surface of each group was analyzed.

RESULTS

Significant statistical differences were observed in both α and β diversity of the ocular surface microbiome among the diabetic dry eye, diabetic non-dry eye, non-diabetic dry eye, and normal control groups (P < 0.05).

CONCLUSIONS

The study revealed distinct microecological compositions on the ocular surfaces between the diabetic dry eye group and other studied groups. Firmicutes and Anoxybacillus were unique bacterial phyla and genera in the dry eye with DM group, while Actinobacteria and Corynebacterium were unique bacterial phyla and genera in the normal control group.

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.

Temporal dynamics and composition of ocular surface microbiota in C57BL/6J mice: uncovering a 12h ultradian rhythm

Purpose

This study aimed to investigate the presence of rhythmic fluctuations in the composition, abundance, and functions of commensal core bacteria on the ocular surface of C57BL/6J mice.

Methods

Male C57BL/6J mice, aged 12 weeks, were subjected to a 12-hour light/12-hour dark cycle. Ocular surface tissue samples were collected at four time points (ZT) over a 24-hour period at six-hour intervals. The core ocular surface microbiota's oscillation cycles and frequencies were assessed using 16S rRNA gene sequencing targeting the V3-V4 region, along with the JTK_CYCLE algorithm. Functional predictions of these bacteria were conducted using PICRUSt2.

Results

Deep sequencing of the ocular surface microbiota highlighted the high abundance of commensal bacteria, with Proteobacteria, Actinobacteriota, and Firmicutes collectively constituting over 90% of the total sample abundance. Among the 22 core bacterial genera, 11 exhibited robust 12-hour rhythms, including Halomonas, Pelagibacterium, Pseudomonas, Nesterenkonia, norank_f_Hyphomonadaceae, Stenotrophomonas, Anoxybacillus, Acinetobacter, Zoogloea, Brevibacillus, and Ralstonia. Further taxonomic analysis indicated significant intra-cluster similarities and inter-cluster differences at the order, family, and genus levels during ZT0/12 and ZT6/18. Community interaction networks and functional prediction analyses revealed synchronized 12-hour rhythmic oscillations in neural, immune, metabolic, and other pathways associated with symbiotic bacteria.

Conclusion

This study demonstrates the presence of ultradian rhythmic oscillations in commensal bacteria on the ocular surface of normal C57BL/6J mice, with a 12-hour cycle. These findings suggest a crucial role for ultradian rhythms in maintaining ocular surface homeostasis in the host.

The Microbiome, Ocular Surface, and Corneal Disorders

The ocular surface microbiome is an emerging field of study that seeks to understand how the community of microorganisms found on the ocular surface may help maintain homeostasis or can potentially lead to disease and dysbiosis. Initial questions include whether the organisms detected on the ocular surface inhabit that ecological niche and, if so, whether there exists a core microbiome found in most or all healthy eyes. Many questions have emerged around whether novel organisms and/or a redistribution of organisms play a role in disease pathogenesis, response to therapies, or convalescence. Although there is much enthusiasm about this topic, the ocular surface microbiome is a new field with many technical challenges. These challenges are discussed in this review as well as a need for standardization to adequately compare studies and advance the field. In addition, this review summarizes the current research on the microbiome of various ocular surface diseases and how these findings may impact treatments and clinical decision-making.

Ocular microbial dysbiosis and its linkage with infectious keratitis patients in Northwest China: A cross-sectional study

OBJECTIVES

To evaluate the alteration of ocular surface microbiome of patients with infectious keratitis in northwest of China.

METHODS

The corneal scrapings, eyelid margin and conjunctiva samples were collected from 57 participants, who were divided into bacterial keratitis, fungal keratitis, viral keratitis and control group. The V3-V4 region of bacterial 16S rDNA in each sample was amplified and sequenced on the Illumina HiSeq 2500 sequencing platform, and the differences among different groups were compared bioinformatically.

RESULTS

Significant alterations of the microbiome were observed in alpha-diversity and beta-diversity analysis between the keratitis groups and the control group (p < 0.05). There was no significant differences between eyelid margin and conjunctiva samples in Alpha-Diversity analysis, but a significant difference between eyelid margin and corneal scraping samples in the keratitis group (p < 0.05, independent t-test). The abundances of Bacillus, Megamonas, Acinetobacter, and Rhodococcu were significantly elevated, while the abundance of Staphylococcus was decreased in the keratitis group compared to the control group.

CONCLUSIONS

The abundance of the ocular microbiome in patients with bacterial keratitis, fungal keratitis, or viral keratitis was significantly higher than those in the control group. Keratitis patients may have ecological disorder on ocular surface microbiome compared with controls. We believe that the conjunctiva and eyelid margin microbiome combined analysis can more comprehensively reflect the composition and abundance of ocular surface microbiome.

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

People with diabetes mellitus (DM) are at an increased risk for developing dry eye disease (DED). However, the mechanisms underlying this phenomenon remain unclear. Recent studies have found that the ocular surface microbiota (OSM) differs significantly between patients with DED and healthy people, suggesting that OSM dysbiosis may contribute to the pathogenesis of DED. This hypothesis provides a new possible explanation for why diabetic patients have a higher prevalence of DED than healthy people. The high-glucose environment and the subsequent pathological changes on the ocular surface can cause OSM dysbiosis. The unbalanced microbiota then promotes ocular surface inflammation and alters tear composition, which disturbs the homeostasis of the ocular surface. This "high glucose-OSM dysbiosis" pathway in the pathogenesis of DED with DM (DM-DED) is discussed in this review.

Challenges and insights in the exploration of the low abundance human ocular surface microbiome

Purpose

The low microbial abundance on the ocular surface results in challenges in the characterization of its microbiome. The purpose of this study was to reveal factors introducing bias in the pipeline from sample collection to data analysis of low-abundant microbiomes.

Methods

Lower conjunctiva and lower lid swabs were collected from six participants using either standard cotton or flocked nylon swabs. Microbial DNA was isolated with two different kits (with or without prior host DNA depletion and mechanical lysis), followed by whole-metagenome shotgun sequencing with a high sequencing depth set at 60 million reads per sample. The relative microbial compositions were generated using the two different tools MetaPhlan3 and Kraken2.

Results

The total amount of extracted DNA was increased by using nylon flocked swabs on the lower conjunctiva. In total, 269 microbial species were detected. The most abundant bacterial phyla were Actinobacteria, Firmicutes and Proteobacteria. Depending on the DNA extraction kit and tool used for profiling, the microbial composition and the relative abundance of viruses varied.

Conclusion

The microbial composition on the ocular surface is not dependent on the swab type, but on the DNA extraction method and profiling tool. These factors have to be considered in further studies about the ocular surface microbiome and other sparsely colonized microbiomes in order to improve data reproducibility. Understanding challenges and biases in the characterization of the ocular surface microbiome may set the basis for microbiome-altering interventions for treatment of ocular surface associated diseases.

Targeting the Gut-Eye Axis: An Emerging Strategy to Face Ocular Diseases

The human microbiota refers to a large variety of microorganisms (bacteria, viruses, and fungi) that live in different human body sites, including the gut, oral cavity, skin, and eyes. In particular, the presence of an ocular surface microbiota with a crucial role in maintaining ocular surface homeostasis by preventing colonization from pathogen species has been recently demonstrated. Moreover, recent studies underline a potential association between gut microbiota (GM) and ocular health. In this respect, some evidence supports the existence of a gut-eye axis involved in the pathogenesis of several ocular diseases, including age-related macular degeneration, uveitis, diabetic retinopathy, dry eye, and glaucoma. Therefore, understanding the link between the GM and these ocular disorders might be useful for the development of new therapeutic approaches, such as probiotics, prebiotics, symbiotics, or faecal microbiota transplantation through which the GM could be modulated, thus allowing better management of these diseases.

Impact of Exposomes on Ocular Surface Diseases

Ocular surface diseases (OSDs) are significant causes of ocular morbidity, and are often associated with chronic inflammation, redness, irritation, discomfort, and pain. In severe OSDs, loss of vision can result from ocular surface failure, characterised by limbal stem cell deficiencies, corneal vascularisation, corneal opacification, and surface keratinisation. External and internal exposomes are measures of environmental factors that individuals are exposed to, and have been increasingly studied for their impact on ocular surface diseases. External exposomes consist of external environmental factors such as dust, pollution, and stress; internal exposomes consist of the surface microbiome, gut microflora, and oxidative stress. Concerning internal exposomes, alterations in the commensal ocular surface microbiome of patients with OSDs are increasingly reported due to advancements in metagenomics using next-generation sequencing. Changes in the microbiome may be a consequence of the underlying disease processes or may have a role in the pathogenesis of OSDs. Understanding the changes in the ocular surface microbiome and the impact of various other exposomes may also help to establish the causative factors underlying ocular surface inflammation and scarring, the hallmarks of OSDs. This review provides a summary of the current evidence on exposomes in various OSDs.

Perturbations of the ocular surface microbiome and their effect on host immune function

PURPOSE OF REVIEW

Current literature describing the ocular surface microbiome and host immunity are reviewed alongside experiments studying perturbations of the microbiome to explore the hypothesis that disruption of a healthy microbiome may predispose the ocular surface to inflammation and infection.

RECENT FINDINGS

The ocular surface of healthy subjects is colonized by stable, pauci-microbial communities that are tolerant to the host immune response and are dominated by the genera Corynebacterium , Propionibacterium , and Staphylococcus . In animal studies, commensal microbes on the ocular surface interact with toll-like receptors to regulate the immune system through immune cell and inflammatory cytokine production, promoting homeostasis and protecting against infection. Contact lens wear, lens wash solutions, and preserved topical medications can disrupt the native microbiome and alter the relative diversity and composition of microbes on the ocular surface.

SUMMARY

The ocular surface microbiome confers protection against pathogenic colonization and immune dysregulation. Disruption of this microbiome by exogenous factors may alter the resistance of the ocular surface to infection. Further study of the relationships between human ocular surface microbiome and the local immune response are needed.

An insight on the eye bacterial microbiota and its role on dry eye disease

The human ocular surface hosts a bacterial assemblage that integrates a diverse and complex microbiome. This bacterial microbiota is part of a healthy eye and plays a protective role in it. However, this ocular bacterial assemblage may alter the ocular surface inflammation response and can influence the development and progression of dry eye disease. For this reason, the present review describes the changes generated on the ocular surface by bacterial assemblages during the development of dry eye disease. Likewise, the interaction of this microbiota with the other inflammatory factors that influence the development of this disease is analyzed, as well as the use of treatments focused on modifying the bacteria on the ocular surface.

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.

Significantly different results in the ocular surface microbiome detected by tear paper and conjunctival swab

BACKGROUND

Great variation has been observed in the composition of the normal microbiota of the ocular surface, and therefore, in addition to differences in detection techniques, the method of collecting ocular surface specimens has a significant impact on the test results.The goal of this study is to ascertain whether the eye surface microbial communities detected by two different sampling methods are consistent and hence explore the feasibility of using tear test paper instead of conjunctival swabs to collect eye surface samples for microbial investigation.

MATERIALS AND METHODS

From July 15, 2021, to July 30, 2021, nonirritating tear test strips and conjunctival swabs of both eyes were used in 158 elderly people (> 60 years old) (79 diabetic and 79 nondiabetic adults) in Xinjing Community for high-throughput sequencing of the V3-V4 region of the 16S rRNA gene. The composition of the microbial communities in tear test paper and conjunctival swab samples was analyzed.

RESULTS

There was no statistically significant difference in Alpha diversity of ocular surface microorganisms represented by tear strip and conjunctival swab in diabetic group (P > 0.05), but there was statistically significant difference in Alpha diversity of ocular surface microorganisms detected by tear strip and conjunctival swab in nondiabetic group (P < 0.05). There were statistically significant differences in Beta diversity of ocular surface microorganisms detected by two sampling methods between diabetic group and nondiabetic group (P < 0.05). There were statistically significant differences in ocular surface microorganisms detected by tear strip method between diabetic group and nondiabetic group (P < 0.05), but there was no statistically significant difference in conjunctival swab method (P > 0.05).

CONCLUSIONS

Tear test paper and conjunctival swabs detect different compositions of microbes through two different techniques of eye surface microbe sampling. Tear test paper cannot completely replace conjunctival swab specimens for the study of microbes related to eye surface diseases.

Investigating the Ocular Surface Microbiome: What Can It Tell Us?

While pathogens of the eye have been studied for a very long time, the existence of resident microbes on the surface of healthy eyes has gained interest only recently. It appears that commensal microbes are a normal feature of the healthy eye, whose role and properties are currently the subject of extensive research. This review provides an overview of studies that have used 16s rRNA gene sequencing and whole metagenome shotgun sequencing to characterize microbial communities associated with the healthy ocular surface from kingdom to genus level. Bacteria are the primary colonizers of the healthy ocular surface, with three predominant phyla: Proteobacteria, Actinobacteria, and Firmicutes, regardless of the host, environment, and method used. Refining the microbial classification to the genus level reveals a highly variable distribution from one individual and study to another. Factors accounting for this variability are intriguing - it is currently unknown to what extent this is attributable to the individuals and their environment and how much is artifactual. Clearly, it is technically challenging to accurately describe the microorganisms of the ocular surface because their abundance is relatively low, thus, permitting substantial contaminations. More research is needed, including better experimental standards to prevent biases, and the exploration of the ocular surface microbiome's role in a spectrum of healthy to pathological states. Outcomes from such research include the opportunity for therapeutic interventions targeting the microbiome.

Characterization of dysbiosis of the conjunctival microbiome and nasal microbiome associated with allergic rhinoconjunctivitis and allergic rhinitis

Background

Allergic rhinoconjunctivitis (ARC) and allergic rhinitis (AR) are prevalent allergic diseases. People are becoming increasingly aware of the impact of microbial disorders on host immunity and allergic diseases. Studies have demonstrated an association between allergic diseases and the microbiome, but much remains unknown. We assessed changes in the conjunctival microbiome and nasal microbiome in patients with ARC or AR.

Methods

Conjunctival swabs and nasal swabs were collected from each participant for 16S rRNA amplicon sequencing. Bacterial communities were analyzed.

Results

Forty patients with ARC, 20 patients suffering from AR, and 34 healthy controls (HCs) were recruited. This study found the abundance of conjunctival microbiome in patients with ARC or AR was significantly lower than that in HCs. The diversity of conjunctival microbiome in patients with AR was significantly lower than those in the other two groups. There is no significant difference in abundance of nasal microbiome between the three groups. The diversities of nasal microbiome in patients with ARC or AR were significantly lower than that in HCs. We found significant differences in microbiota compositions in patients with ARC or AR compared with those in HCs. However, no significant difference in microbiota compositions was found between patients with ARC and patients with AR. Microbiome functions in the ARC group and AR group were also altered compared with HCs.

Conclusions

We revealed changes in the composition and function of the conjunctival microbiome and nasal microbiome of patients with ARC or AR, which suggests that there is a relationship between allergic conditions and the local microbiome.

DNA extraction protocol impacts ocular surface microbiome profile

Purpose

The aim of this study is to provide a reference frame to allow the comparison and interpretation of currently published studies on 16S ribosomal ribonucleic acid amplicon sequencing of ocular microbiome samples using different DNA extraction protocols. Alongside, the quantitative and qualitative yield and the reproducibility of different protocols has been assessed.

Methods

Both eyes of 7 eligible volunteers were sampled. Five commercially available DNA extraction protocols were selected based on previous publications in the field of the ocular surface microbiome and 2 host DNA depletion protocols were added based on their reported effective host DNA depletion without significant reduction in bacterial DNA concentration. The V3-V4 region of the 16S rRNA gene was targeted using Illumina MiSeq sequencing. The DADA2 pipeline in R was used to perform the bio-informatic processing and taxonomical assignment was done using the SILVA v132 database. The Vegdist function was used to calculate Bray-Curtis distances and the Galaxy web application was used to identify potential metagenomic biomarkers via linear discriminant analysis Effect Size (LEfSe). The R package Decontam was applied to control for potential contaminants.

Results

Samples analysed with PowerSoil, RNeasy and NucleoSpin had the highest DNA yield. The host DNA depletion kits showed a very low microbial DNA yield; and these samples were pooled per kit before sequencing. Despite pooling, 1 of both failed to construct a library.Looking at the beta-diversity, clear microbial compositional differences - dependent on the extraction protocol used - were observed and remained present after decontamination. Eighteen genera were consistently retrieved from the ocular surface of every volunteer by all non-pooled extraction kits and a comprehensive list of differentially abundant bacteria per extraction method was generated using LefSe analysis.

Conclusion

High-quality papers have been published in the field of the ocular surface microbiome but consensus on the importance of the extraction protocol used are lacking. Potential contaminants and discriminative genera per extraction protocol used, were introduced and a reference frame was built to facilitate both the interpretation of currently published papers and to ease future choice - making based on the research question at hand.

Conjunctival sac microbiome in anophthalmic patients: Flora diversity and the impact of ocular prosthesis materials

Purpose

To explore the changes of bacterial flora in anophthalmic patients wearing ocular prosthesis (OP) and the microbiome diversity in conditions of different OP materials.

Methods

A cross-sectional clinical study was conducted, involving 19 OP patients and 23 healthy subjects. Samples were collected from the upper, lower palpebral, caruncle, and fornix conjunctiva. 16S rRNA sequencing was applied to identify the bacterial flora in the samples. The eye comfort of each OP patient was determined by a questionnaire. In addition, demographics information of each participant was also collected.

Results

The diversity and richness of ocular flora in OP patients were significantly higher than that in healthy subjects. The results of flora species analysis also indicated that in OP patients, pathogenic microorganisms such as Escherichia Shigella and Fusobacterium increased significantly, while the resident flora of Lactobacillus and Lactococcus decreased significantly. Within the self-comparison of OP patients, compared with Polymethyl Methacrylate (PMMA), prosthetic material of glass will lead to the increased colonization of opportunistic pathogens such as Alcaligenes, Dermabacter and Spirochaetes, while gender and age have no significant impact on ocular flora.

Conclusions

The ocular flora of OP patients was significantly different from that of healthy people. Abundant colonization of pathogenic microorganisms may have an important potential relationship with eye discomfort and eye diseases of OP patients. PMMA, as an artificial eye material, demonstrated potential advantages in reducing the colonization of opportunistic pathogens.

Disturbances in the ocular surface microbiome by perioperative antimicrobial eye drops

We aimed to elucidate the effects of antimicrobial eye drops used in the perioperative period of ophthalmic surgery on the ocular surface microbiome by metagenomic analysis. Twenty-eight eyes from 15 patients (mean age 74.1 years) with no history of eye drop use within 3 months before cataract surgery were included in this study. Gatifloxacin eye drops were used in all patients in the perioperative period. The antimicrobial eye drops were started 3 days before surgery. They were discontinued after conjunctival sac specimen collection for 2 weeks after the surgery. Conjunctival sac specimens were collected to investigate the alterations in the ocular surface microbiome by meta-16S analysis targeting the V3-V4 region of the bacterial 16S rRNA gene. Principal coordinate analysis showed that the bacterial composition tended to be different before and 2 and 4 weeks after surgery. Individual observations on six eyes showed that the bacterial composition at 12 weeks after surgery was closer to that before surgery than to that at 4 weeks after surgery in two eyes, while the bacterial composition in the remaining four eyes was different at various time points. Before surgery, Firmicutes, Proteobacteria, and Bacteroidetes were predominant; however, 2 weeks after surgery, the proportion of Proteobacteria increased and that of Firmicutes decreased. A similar trend was noticed 4 weeks after surgery, although antibacterial eye drops had been discontinued 2 weeks after surgery. The Shannon-Weaver coefficient showed a decreasing trend at 2-, 4-, and 12-weeks post operation compared to that before operation. The diversity of the microbiome decreased significantly at 2- and 4-weeks after surgery when compared to that before surgery (p < 0.05). The ocular surface microbiome is easily disrupted by antimicrobial eye drops, and it needs recovery time. In such cases, the ocular surface microbiome is presumed to contain many antimicrobial-resistant bacteria. In some cases, it may not recover, and a new microbiome is formed.

Microbiological Characteristics of Ocular Surface Associated With Dry Eye in Children and Adolescents With Diabetes Mellitus

Purpose

To analyze the characteristics of ocular surface microbial composition in children and adolescents with diabetes mellitus and dry eye (DE) by tear analysis.

Methods

We selected 65 children and adolescents aged 8 to 16 years with DE and non-DE diabetes mellitus and 33 healthy children in the same age group from the Shanghai Children and Adolescent Diabetes Eye Study. Tears were collected for high-throughput sequencing of the V3 and V4 region of 16S rRNA. The ocular surface microbiota in diabetic DE (DM-DE; n = 31), diabetic with non-DE (DM-NDE; n = 34), and healthy (NDM; n = 33) groups were studied. QIIME2 software was used to analyze the microbiota of each group.

Results

The DM-DE group had the highest amplicon sequence variants, and the differences in α-diversity and β-diversity of micro-organisms in the ocular surfaces of DM-DE, diabetic with non-DE, and healthy eyes were statistically significant (P < 0.05). Bacteroidetes (15.6%), Tenericutes (9.3%), Firmicutes (21.8%), and Lactococcus (7.9%), Bacteroides (7.8%), Acinetobacter (3.9%), Clostridium (0.8%), Lactobacillus (0.8%) and Streptococcus (0.2%) were the specific phyla and genera, respectively, in the DM-DE group.

Conclusions

Compared with the patients with non-DE and healthy children, the microbial diversity of the ocular surface in children and adolescents with diabetes mellitus and DE was higher with unique bacterial phyla and genera composition.

Microbial Contamination of Soft Contact Lenses Among Medical School Students in Southern Iraq

Background

Contamination of CLs and accessories risks potentially devastating microbial keratitis. We aimed to explore the rate of microbial contamination and predisposing factors among a group of asymptomatic young medical students.

Methodology

The study included 115 healthy female medical students with a mean age of 21.64 ± 2.02 years between January and November 2021. Information about CL use, wear and care was gathered. Each participant’s CL and case were swabbed for microbiological identification. Univariable and multivariable analyses were conducted to look for associations with a range of factors.

Results

Overall, 91 participants (79.13%) had at least one contaminated sample (lens and/or case). The rates of contamination of CL and their cases were 66% and 76.5%, respectively. Higher contamination rates were caused by gram-negative bacteria (60% of the contaminated samples) with P. aeruginosa being the most common contaminant both for CL and cases, whereas S. epidermidis and S. aureus were the most common contaminants for the CL and cases, respectively, regarding gram-positive contamination. Multivariable analysis showed younger age as a significant predictor of pseudomonas contamination of the lenses and cases (OR: 12.302, 6.555 for CL & cases, respectively; P = 0.001 for both). Older age was a significant predictor of K. pneumoniae contamination (OR: 4.154, P = 0.007). Pseudomonas contamination of both lenses and cases was predicted by the type of solution used (OR: 10.8 and 13.5, P = 0.001 and 0.003 for bottled and distilled water vs commercially available solutions for CL; OR: 4.5 and 5.8, P = 0.045 and 0.004, respectively, for cases). Pseudomonas case contamination was associated with low frequency of solution change.

Conclusion

Microbial contamination rate of soft CL and their cases is high among young medical students in comparison to previously reported rates and was predisposed by several poor hygienic practices and wearing regimens.

The conjunctival microbiome before and after azithromycin mass drug administration for trachoma control in a cohort of Tanzanian children

Background

Trachoma, caused by ocular infection with Chlamydia trachomatis, is a neglected tropical disease that can lead to blinding pathology. Current trachoma control programmes have successfully used mass drug administration (MDA) with azithromycin to clear C. trachomatis infection and reduce transmission, alongside promoting facial cleanliness for better personal hygiene and environmental improvement. In areas of low-trachoma endemicity, the relationship between C. trachomatis infection and trachomatous disease weakens, and non-chlamydial bacteria have been associated with disease signs.

Methods

We enrolled a cohort of children aged 6-10 years from three adjacent trachoma endemic villages in Kilimanjaro and Arusha regions, Northern Tanzania. Children were divided into four clinical groups based on the presence or absence of ocular C. trachomatis infection and clinical signs of trachomatous papillary inflammation (TP). To determine the impact of treatment on the ocular microbiome in these clinical groups, we performed V4-16S rRNA sequencing of conjunctival DNA from children 3-9 months pre-MDA (n = 269) and 3 months post-MDA (n = 79).

Results

Chlamydia trachomatis PCR-negative, no TP children had the highest pre-MDA ocular microbiome alpha diversity, which was reduced in C. trachomatis infected children and further decreased in those with TP. Pre-MDA, Haemophilus and Staphylococcus were associated with C. trachomatis infection with and without concurrent TP, while Helicobacter was increased in those with TP in the absence of current C. trachomatis infection. Post-MDA, none of the studied children had ocular C. trachomatis infection or TP. MDA increased ocular microbiome diversity in all clinical groups, the change was of greater magnitude in children with pre-MDA TP. MDA effectively reduced the prevalence of disease causing pathogenic non-chlamydial bacteria, and promoted restoration of a normal, healthy conjunctival microbiome.

Conclusion

We identified Helicobacter as a non-chlamydial bacterium associated with the clinical signs of TP. Further investigation to determine its relevance in other low-endemicity communities is required. MDA was shown to be effective at clearing C. trachomatis infection and other non-chlamydial ocular pathogens, without any detrimental longitudinal effects on the ocular microbiome. These findings suggest that azithromycin MDA may be valuable in trachoma control even in populations where the relationship between clinical signs of trachoma and the prevalence of current ocular C. trachomatis infection has become dissociated.

Exploring the Healthy Eye Microbiota Niche in a Multicenter Study

Purpose: This study aims to explore and characterize healthy eye microbiota. Methods: Healthy subjects older than 18 years were selected for this descriptive cross-sectional study. Samples were collected with an eSwab with 1 mL of Liquid Amies Medium (Copan Brescia, Italy). Following DNA extraction, libraries preparation, and amplification, PCR products were purified and end-repaired for barcode ligation. Libraries were pooled to a final concentration of 26 pM. Template preparation was performed with Ion Chef according to Ion 510, Ion 520, and Ion 530 Kit-Chef protocol. Sequencing of the amplicon libraries was carried out on a 520 or 530 chip using the Ion Torrent S5 system (Thermo Fisher; Waltham, MA, USA). Raw reads were analyzed with GAIA (v 2.02). Results: Healthy eye microbiota is a low-diversity microbiome. The vast majority of the 137 analyzed samples were highly enriched with Staphylococcus, whereas only in a few of them, other genera such as Bacillus, Pseudomonas, and Corynebacterium predominate. We found an average of 88 genera with an average Shannon index of 0.65. Conclusion: We identified nine different ECSTs. A better understanding of healthy eye microbiota has the potential to improve disease diagnosis and personalized regimens to promote health.

Ocular surface microbiota: Ophthalmic infectious disease and probiotics

Recently, increasing studies have emphasized the importance of commensal bacteria in humans, including microbiota in the oral cavity, gut, vagina, or skin. Ocular surface microbiota (OSM) is gaining great importance as new methodologies for bacteria DNA sequencing have been published. This review outlines the current understanding and investigation of OSM and introduces the new concept of the gut–eye axis. Moreover, we have collected current studies that focus on the relationship between ophthalmic infectious disease and alterations in the OSM or human gut microbiota. Finally, we discuss the current application of probiotics in ophthalmic infectious disease, its limitations to date, and futural directions.

More than Antibiotics: Latest Therapeutics in the Treatment and Prevention of Ocular Surface Infections

Ocular surface infections have been common issues for ophthalmologists for decades. Traditional strategies for infection include antibiotics, antiviral agents, and steroids. However, multiple drug-resistant bacteria have become more common with the prevalence of antibiotic use. Furthermore, an ideal treatment for an infectious disease should not only emphasize eliminating the microorganism but also maintaining clear and satisfying visual acuity. Immunogenetic inflammation, tissue fibrosis, and corneal scarring pose serious threats to vision, and they are not attenuated or prevented by traditional antimicrobial therapeutics. Herein, we collected information about current management techniques including stem-cell therapy, probiotics, and gene therapy as well as preventive strategies related to Toll-like receptors. Finally, we will introduce the latest research findings in ocular drug-delivery systems, which may enhance the bioavailability and efficiency of ocular therapeutics. The clinical application of improved delivery systems and novel therapeutics may support people suffering from ocular surface infections.

Characterization and Comparison of Ocular Surface Microbiome in Newborns

The ocular microbiome is of fundamental importance for immune eye homeostasis, and its alteration would lead to an impairment of ocular functionality. Little evidence is reported on the composition of the ocular microbiota of term infants and on the impact of antibiotic prophylaxis. Methods: A total of 20 conjunctival swabs were collected from newborns at birth and after antibiotic treatment. Samples were subjected to 16S rRNA sequencing via system MiSeq Illumina. The data were processed with the MicrobAT software and statistical analysis were performed using two-way ANOVA. Results: Antibiotic prophylaxis with gentamicin altered the composition of the microbiota. In detail, a 1.5- and 2.01-fold reduction was recorded for Cutibacterium acnes (C. acnes) and Massilia timonae (M. timonae), respectively, whereas an increase in Staphylococcus spp. of 6.5 times occurred after antibiotic exposure. Conclusions: Antibiotic prophylaxis altered the ocular microbiota whose understanding could avoid adverse effects on eye health.

The Current Knowledge on the Pathogenesis of Tissue and Medical Device-Related Biofilm Infections

Biofilm is the trigger for the majority of infections caused by the ability of microorganisms to adhere to tissues and medical devices. Microbial cells embedded in the biofilm matrix are highly tolerant to antimicrobials and escape the host immune system. Thus, the refractory nature of biofilm-related infections (BRIs) still represents a great challenge for physicians and is a serious health threat worldwide. Despite its importance, the microbiological diagnosis of a BRI is still difficult and not routinely assessed in clinical microbiology. Moreover, biofilm bacteria are up to 100–1000 times less susceptible to antibiotics than their planktonic counterpart. Consequently, conventional antibiograms might not be representative of the bacterial drug susceptibility in vivo. The timely recognition of a BRI is a crucial step to directing the most appropriate biofilm-targeted antimicrobial strategy.

Crosstalk between Body Microbiota and the Regulation of Immunity

The microbiome corresponds to the genetic component of microorganisms (archaea, bacteria, phages, viruses, fungi, and protozoa) that coexist with an individual. During the last two decades, research on this topic has become massive demonstrating that in both homeostasis and disease, the microbiome plays an important role, and in some cases, a decisive one. To date, microbiota have been identified at different body locations, such as the eyes, lung, gastrointestinal and genitourinary tracts, and skin, and technological advances have permitted the taxonomic characterization of resident species and their metabolites, in addition to the cellular and molecular components of the host that maintain a crosstalk with local microorganisms. Here, we summarize recent studies regarding microbiota residing in different zones of the body and their relationship with the immune system. We emphasize the immune components underlying pathological conditions and how they interact with local (and distant) microbiota.

Profiling of the Conjunctival Bacterial Microbiota Reveals the Feasibility of Utilizing a Microbiome-Based Machine Learning Model to Differentially Diagnose Microbial Keratitis and the Core Components of the Conjunctival Bacterial Interaction Network

Both healthy and diseased human ocular surfaces possess their own microbiota. If allowed, opportunistic pathogens within the ocular microbiota may cause microbial keratitis (MK). However, the nonpathogenic component of the ocular microbiota has been proven to undermine the performance of culture, the gold standard of the etiological diagnosis for MK. As the conjunctival bacterial microbiota generates unique alterations with various oculopathies, this study aimed to evaluate the feasibility of distinguishing MK using machine learning based on the characteristics of the conjunctival bacterial microbiome associated with various types of MK. This study also aimed to reveal which bacterial genera constitute the core of the interaction network of the conjunctival bacterial microbiome. Conjunctival swabs collected from the diseased eyes of MK patients and the randomly chosen normal eyes of healthy volunteers were subjected for high-throughput 16S rDNA sequencing. The relative content of each bacterial genus and the composition of bacterial gene functions in every sample were used to establish identification models with the random forest algorithm. Tenfold cross validation was adopted. Accuracy was 96.25% using the bacterial microbiota structure and 93.75% using the bacterial gene functional composition. Therefore, machine learning with the conjunctival bacterial microbiome characteristics might be used for differentiation of MKs as a noninvasive supplementary approach. In addition, this study found that Actinobacteria, Lactobacillus, Clostridium, Helicobacter, and Sphingomonas constitute the core of the interaction network of the conjunctival bacterial microbiome.

Ocular surface toll like receptors in ageing

Background

To evaluate changes in Toll Like Receptors (TLRs) expression at the ocular surface of healthy volunteers within different age groups.

Methods

Fifty-one healthy volunteers were enrolled in a pilot observational study. Clinical function tests (OSDI questionnaire, Schirmer test type I and Break Up time) were assessed in all subjects. Temporal Conjunctival imprints were performed for molecular and immunohistochemical analysis to measure TLRs expression (TLR2, 4, 3, 5, 7, 8, 9 and MyD88).

Results

Immunofluorescence data showed an increased TLR2 and decreased TLR7 and TLR8 immunoreactivity in old conjunctival imprints. Up-regulation of TLR2 and down-regulation of TLR7, TLR8 and MyD88 transcripts expression corroborated the data. A direct correlation was showed between increasing ICAM-1 and increasing TLR2 changes with age. Within the age OSDI score increases, T-BUT values decrease, and goblet cells showed a decreasing trend.

Conclusion

Changes in TLRs expression are associated with ageing, suggesting physiological role of TLRs in modulating ocular surface immunity. TLRs age related changes may participate to the changes of ocular surface homeostatic mechanisms which lead to inflammAging.

Analysis of Conjunctival Sac Microbiome in Dry Eye Patients With and Without Sjögren's Syndrome

Purpose

To analyze the conjunctival sac microbial communities in patients with Sjögren's syndrome-associated dry eyes (SSDE) and non-Sjögren's syndrome-associated dry eyes (NSSDE), compared with normal controls (NC).

Methods

Conjunctival sac swab samples from 23 eyes of SSDE, 36 eyes of NSSDE, and 39 eyes of NC were collected. The V3–V4 region of the 16S ribosomal RNA (rRNA) gene high-throughput sequencing was performed on an Illumina MiSeq platform and analyzed using Quantitative Insights Into Microbial Ecology (QIIME). Alpha diversity was employed to analyze microbiome diversity through Chao1 and Shannon indexes. Beta diversity was demonstrated by the principal coordinates analysis (PCoA) and Partial Least Squares Discrimination Analysis (PLS-DA). The relative abundance was bioinformatically analyzed at the phylum and genus levels.

Results

The alpha diversity was lower in patients with dry eye disease (Shannon index: NC vs. SSDE: P = 0.020, NC vs. NSSDE: P = 0.029). The beta diversity showed divergent microbiome composition in different groups (NC vs. SSDE: P = 0.001, NC vs. NSSDE: P = 0.001, NSSDE vs. SSDE: P = 0.005). The top 5 abundant phyla were Firmicutes, Proteobacteria, Actinobacteriota, Bacteroidota, and Cyanobacteria in all three groups. The top five abundant genera included Acinetobacter, Staphylococcus, Bacillus, Corynebacterium, and Clostridium_sensu_stricto_1. The relative microbiome abundance was different between groups. The Firmicutes/Bacteroidetes (F/B) ratio was 6.42, 7.31, and 9.71 in the NC, NSSDE, and SSDE groups, respectively (NC vs. SSDE: P = 0.038, NC vs. NSSDE: P = 0.991, SSDE vs. NSSDE: P = 0.048).

Conclusion

The diversity of conjunctival sac microbiome in patients with NSSDE and SSDE was diminished compared with NC. The main microbiome at the phylum and genus level were similar between groups, but the relative abundance had variations. The Firmicutes/Bacteroidetes ratio was higher in the SSDE group.

Streptococcus pneumoniae exerts oxidative stress, subverts antioxidant signaling and autophagy in human corneal epithelial cells that is alleviated by tert-Butylhydroquinone

Streptococcus pneumoniae is one of the leading causes of bacterial keratitis in the developing world and globally. In the current study, we have determined oxidative stress as pathogenesis of S. pneumoniae infection in corneal tissues and human corneal epithelial cells (HCEC) and explored host immune response of HCEC towards S. pneumoniae. We also determined whether treatment with tert-Butylhydroquinone (tBHQ), a Nrf2 inducer, could alleviate oxidative stress and reduce bacterial cytotoxicity in these cells. Oxidative stress was determined in corneal tissues of patients and HCEC by immunohistochemistry and immunofluorescence analysis, respectively. The expression of antioxidant genes, cytokines and antimicrobial peptides was determined by quantitative PCR. Infection of HCEC by S. pneumoniae was determined by colony-forming units. The autophagy and cell death were determined by fluorescence microscopy. The phosphorylation of signaling proteins was evaluated by immunoblot analysis. S. pneumoniae induced oxidative stress during corneal infections and inhibited antioxidant signaling pathways and immune responses like autophagy. tBHQ aided in restoring Nrf2 activation, reduced reactive oxygen species generation and prevented cytotoxicity and cell death in S. pneumoniae-infected HCEC. tBHQ also induced autophagy in a Nrf2-dependent manner and reduced bacterial survival in HCEC. Increased expression of antimicrobial peptides by tBHQ might have contributed to a reduction of bacterial load and cytotoxicity, as exemplified in LL-37 depleted corneal epithelial cells exposed to S. pneumoniae compared to control siRNA-transfected cells. tBHQ mediates alleviation of oxidative stress induced by S. pneumoniae by activating Nrf2-mediated antioxidant signaling in corneal epithelial cells. tBHQ also enhances expression of antimicrobial peptides in corneal cells and aids in inhibition of bacterial survival and cytotoxicity of HCEC.

Effect of polymicrobial interactions on antimicrobial resistance: an in vitro analysis in human ocular infections

Purpose: Investigate the effect of polymicrobial interactions on antimicrobial resistance (AMR) of ocular pathogens in polymicrobial settings, compared with monomicrobial infections. Methods: Polymicrobial interactions were labeled as antagonistic, synergistic or indifferent based on a reduction, an increase or no change, respectively, in antibiotics' MIC by the Vitek 2 compact system, compared with monomicrobial pathogens. Results: Staphylococcus epidermidis showed antagonistic polymicrobial interactions (22.6%); Pseudomonas aeruginosa showed synergistic interactions (62.5%); multidrug-resistant Acinetobacter baumannii showed increased susceptibility to select antibiotics; Serratia ficaria (inherently colistin resistant) became colistin-susceptible in polymicrobial combinations. Conclusion: Both antagonistic and synergistic interactions exist among human pathogens in polymicrobial settings. Gram-positive pathogens had significantly higher antagonistic polymicrobial interactions (increased MICs: 20.4%) compared with Gram-negative ones (synergistic: 59.4%).

The Effect of Topical Anesthetics on 16S Ribosomal Ribonucleic Acid Amplicon Sequencing Results in Ocular Surface Microbiome Research

PURPOSE

To clarify the short-term effect of topical anesthetics on 16S ribosomal ribonucleic acid amplicon sequencing results in ocular surface microbiome research.

METHODS

Both eyes of 24 eligible volunteers undergoing general anesthesia were sampled. Before sampling, a drop of artificial tears or a drop of topical anesthetic was applied in a randomized way. By using artificial tears as a control, we assured blinding of the executer and took a potential diluting effect into account. Bacterial DNA was extracted using the QIAGEN RNeasy PowerMicrobiome Kit with specific adaptations. Amplified DNA was sequenced with the Illumina MiSeq sequencing platform.

RESULTS

Four sample pairs were excluded due to low yield of bacterial DNA. In the remaining 20 sample pairs, no differences were observed with topical anesthetics at the levels of amplicon sequence variants (ASVs), phylum, genera, or alpha and beta diversity. Weighted UniFrac distance confirmed that the intraindividual distance between the right and left eye was smaller than the effect of the topical anesthetic. Interestingly, however, we identified Cutibacterium as a potential discriminative biomarker for topical anesthetic use. Overall, a significantly higher number of observed reads were assigned to genera with Gram-positive characteristics.

CONCLUSIONS

Based on our targeted, double-blinded, within-subject study, topical anesthetics do not affect the overall sequencing results but display a specific effect on Cutibacterium. When comparing research results, the impact of topical anesthetics on prevalence and abundance of Cutibacterium should be considered.

TRANSLATIONAL RELEVANCE

Understanding and standardization of sampling techniques are indispensable to properly execute clinical microbiome research.

The Microbiome of Meibomian Gland Secretions from Patients with Internal Hordeolum Treated with Hypochlorous Acid Eyelid Wipes

Objective

The aims of our experiment were to compare the microorganisms in meibomian gland secretions from patients with internal hordeolum before and after treatment using hypochlorous acid eyelid wipes, to elucidate the mechanism underlying hypochlorous acid eyelid wipe treatment of internal hordeolum.

Methods

This was a prospective, matched-pair study. A total of eight patients with internal hordeolum who attended the ophthalmology clinic of our hospital from April to August 2020 were included. Meibomian gland secretions were collected from subjects before treatment (Group A) and from patients cured after eyelid cleaning with hypochlorous acid eyelid wipes for 7 days (Group B). Samples were submitted to 16S rRNA high-throughput sequencing, and the resulting data were analyzed to compare the differences in the structure and composition of meibomian gland secretion microbial flora before and after treatment of internal hordeolum.

Results

A total of 2127 operational taxonomic units were obtained from the two groups of samples, and there was no significant difference in alpha diversity before and after eyelid cleaning. At the phylum level, there was no significant difference between the two groups. The predominant phyla in Group A included the following: Firmicutes (32.78% ± 20.16%), Proteobacteria (26.73% ± 7.49%), Acidobacteria (10.58% ± 11.45%), Bacteroidetes (9.05% ± 6.63%), Actinobacteria (8.48% ±1.77%), and Chloroflexi (3.15% ± 3.12%), while those in Group B were the following: Proteobacteria (31.86% ± 9.69%), Firmicutes (29.07% ± 24.20%), Acidobacteria (11.33% ± 7.53%), Actinobacteria (7.10% ± 1.98%), Bacteroidetes (5.39% ± 5.17%), and Chloroflexi (3.89% ± 3.67%). Starting from the class level, significant differences in microbial communities were detected before and after eyelid cleaning (P < 0.05). Linear discriminant analysis effect size analysis showed the core flora in Group A microbiome comprising Actinobacteria, Staphylococcus, Staphylococcaceae, Staphylococcus aureus, Ruminococcacea UCg-014, Ruminococcacea-UCG-014, Halomonadaceae, Neisseria, Methylobacterium, Frankiales, and Neisseria sicca, while those in Group B microbial were Streptococcus sp., Blautia, Bifidobacterium pseudocatenulatum, Subdoligranulum, Subdoligranulum variabile, Faecalibacterium, and Faecalibacterium prausnitzii.

Conclusion

Eyelid cleaning with hypochlorous acid eyelid wipes does not change the biodiversity in the meibomian gland secretions of patients with internal hordeolum. Hypochlorous acid eyelid wipes may affect the internal hordeolum through broad-spectrum antibacterial action to effectively reduce the relative abundance of symbiotic pathogens, such as Staphylococcus, Neisseria, Actinomycetes, and Ruminococcus and increase that of Faecalibacterium prausnitzii and other symbiotic probiotics with anti-inflammatory effects.

Characterization of Conjunctival Sac Microbiome from Patients with Allergic Conjunctivitis

Conjunctival sac microbiome alterations have been reported to be closely associated with many ocular diseases. However, the characteristic of conjunctival sac microbiome in allergic conjunctivitis (AC) was scarcely described. In this study, we aimed to identify the differences of the conjunctival sac microbiome composition in AC patients compared with normal controls (NCs) using high-throughput 16S rDNA sequencing metagenomic analysis. The conjunctival sac microbiome samples from 28 AC patients and 39 NC patients were collected. The V3-V4 region of 16S rRNA gene high-throughput sequencing was performed on the illumina MiSeq platform. Alpha diversity, beta diversity and the relative abundance at the phylum and genus levels were analyzed using QIIME. Alpha diversity demonstrated by Chao1, Observed_species and PD_whole_tree indexes did not show significant difference between the AC and NC groups, while the Shannon index was higher in the AC group. Beta diversity showed divergent microbiome composition in different groups (p < 0.005). The top five abundant phyla were Firmicutes, Proteobacteria, Actinobacteriota, Bacteroidota and Cyanobacteria in both groups. The top five abundant genera were Bacillus, Staphylococcus, Corynebacterium, Acinetobacter and Ralstonia in the AC group and Acinetobacter, Staphylococcus, Bacillus, Clostridium_sensu_stricto_1, Corynebacterium and Geobacillus in the NC group. The Firmicutes/Bacteroidetes (F/B) ratio at the phylum level was similar between groups (p = 0.144). The Bacillus/Acinetobacter (B/A) ratio at the genus level was higher in the AC group (p = 0.021). The dysbiosis detected in this study might provide further evidence to investigate the mechanism and treatment methods for allergic conjunctivitis.

Effects of Sodium Hyaluronate Eye Drops With or Without Preservatives on Ocular Surface Bacterial Microbiota

Purpose

This study aimed to determine the composition and diversity of bacterial communities on the ocular surface before and after the intervention with sodium hyaluronate eye drops (with or without preservatives) using 16S rRNA gene amplicon sequencing.

Methods

Sixteen healthy adults were randomly divided into two groups and treated with sodium hyaluronate eye drops with or without preservatives for 2 weeks. The individuals used the same artificial tears in both eyes. The microbial samples from the conjunctival sac of each participant were collected at baseline and 2 weeks after intervention. The diversity and taxonomic differences among different groups before and after intervention were compared by sequencing the V3–V4 region of the 16S rRNA gene.

Results

The similarity in the binocular microbial community was high in 1 of the 16 volunteers (Bray-Curtis dissimilarity score < 0.3). At the genus level, 11 bacteria were detected in all samples with an average relative abundance of more than 1%. The bacterial community changed significantly after the use of sodium hyaluronate eye drops (with or without preservatives), whether within individuals or between individuals in different groups (P < 0.05, PERMANOVA). Different dosage forms of sodium hyaluronate eye drops significantly decreased the relative abundance of Flavobacterium caeni and Deinococcus antarcticus, respectively (P < 0.05).

Conclusions

Healthy people had a rich diversity of the bacterial microbiota on the ocular surface, but the bacterial communities between the eyes were not completely similar. Irrespective of containing benzalkonium chloride (BAC), sodium hyaluronate eye drops can change the bacterial community on the ocular surface.

Bacterial distribution on the ocular surface of patients with primary Sjögren's syndrome

Many studies have shown that gut microbial dysbiosis is a major factor in the etiology of autoimmune diseases but none have suggested that the ocular surface (OS) microbiome is associated with Sjögren’s syndrome (SS). In this prospective study, we analyzed bacterial distribution on the OS in patients with primary SS. Among the 120 subjects included in this study, 48 patients (group A) had primary SS, whereas 72 subjects (group B) had dry eye symptoms that were unrelated to SS. We evaluated clinical dry eye parameters such as the OS disease index, ocular staining score (OSS), Schirmer’s I test, and tear break-up time (TBUT). Conjunctival swabs were used to analyze the microbial communities from the two groups. Bacterial 16S rRNA genes were sequenced using the Illumina MiSeq platform, and the data were analyzed using the QIIME 1.9.1 program. The Shannon index was significantly lower in group A than in group B microbiota (p < 0.05). An analysis of similarity using the Bray–Curtis distance method found no difference in beta-diversity between the two groups (p > 0.05). In group A, Actinobacteria at the phylum level and Corynebacteria at the genus level exhibited low abundance than group B, but the differences were not statistically significant (p > 0.05). SS apparently decreases the diversity of the OS microbial community. These observations may be related to the pathophysiology of SS and should be investigated in future studies.

Human microbiota research in Africa: a systematic review reveals gaps and priorities for future research

BACKGROUND

The role of the human microbiome in health and disease is an emerging and important area of research; however, there is a concern that African populations are under-represented in human microbiome studies. We, therefore, conducted a systematic survey of African human microbiome studies to provide an overview and identify research gaps. Our secondary objectives were: (i) to determine the number of peer-reviewed publications; (ii) to identify the extent to which the researches focused on diseases identified by the World Health Organization [WHO] State of Health in the African Region Report as being the leading causes of morbidity and mortality in 2018; (iii) to describe the extent and pattern of collaborations between researchers in Africa and the rest of the world; and (iv) to identify leadership and funders of the studies.

METHODOLOGY

We systematically searched Medline via PubMed, Scopus, CINAHL, Academic Search Premier, Africa-Wide Information through EBSCOhost, and Web of Science from inception through to 1st April 2020. We included studies that characterized samples from African populations using next-generation sequencing approaches. Two reviewers independently conducted the literature search, title and abstract, and full-text screening, as well as data extraction.

RESULTS

We included 168 studies out of 5515 records retrieved. Most studies were published in PLoS One (13%; 22/168), and samples were collected from 33 of the 54 African countries. The country where most studies were conducted was South Africa (27/168), followed by Kenya (23/168) and Uganda (18/168). 26.8% (45/168) focused on diseases of significant public health concern in Africa. Collaboration between scientists from the United States of America and Africa was most common (96/168). The first and/or last authors of 79.8% of studies were not affiliated with institutions in Africa. Major funders were the United States of America National Institutes of Health (45.2%; 76/168), Bill and Melinda Gates Foundation (17.8%; 30/168), and the European Union (11.9%; 20/168).

CONCLUSIONS

There are significant gaps in microbiome research in Africa, especially those focusing on diseases of public health importance. There is a need for local leadership, capacity building, intra-continental collaboration, and national government investment in microbiome research within Africa. Video Abstract.

Bacterial keratitis: identifying the areas of clinical uncertainty

Bacterial keratitis is a common corneal infection that is treated with topical antimicrobials. By the time of presentation there may already be severe visual loss from corneal ulceration and opacity, which may persist despite treatment. There are significant differences in the associated risk factors and the bacterial isolates between high income and low- or middle-income countries, so that general management guidelines may not be appropriate. Although the diagnosis of bacterial keratitis may seem intuitive there are multiple uncertainties about the criteria that are used, which impacts the interpretation of investigations and recruitment to clinical studies. Importantly, the concept that bacterial keratitis can only be confirmed by culture ignores the approximately 50% of cases clinically consistent with bacterial keratitis in which investigations are negative. The aetiology of these culture-negative cases is unknown. Currently, the estimation of bacterial susceptibility to antimicrobials is based on data from systemic administration and achievable serum or tissue concentrations, rather than relevant corneal concentrations and biological activity in the cornea. The provision to the clinician of minimum inhibitory concentrations of the antimicrobials for the isolated bacteria would be an important step forward. An increase in the prevalence of antimicrobial resistance is a concern, but the effect this has on disease outcomes is yet unclear. Virulence factors are not routinely assessed although they may affect the pathogenicity of bacteria within species and affect outcomes. New technologies have been developed to detect and kill bacteria, and their application to bacterial keratitis is discussed. In this review we present the multiple areas of clinical uncertainty that hamper research and the clinical management of bacterial keratitis, and we address some of the assumptions and dogma that have become established in the literature.

Investigation of effects of orthokeratology and povidone iodine disinfecting solution on the conjunctival microbiome using MALDI-TOF mass spectrometry

Purpose

To determine organisms present in the conjunctiva of children before and after orthokeratology lens wear, using MALDI-TOF mass spectrometry.

Methods

Conjunctival samples were collected from children aged 8-12 years (inclusive) at baseline and on three occasions over the first six months of orthokeratology treatment. All lenses were disinfected using the povidone iodine-based solution every day after use. Specimens were cultured and all isolated colonies were identified using MALDI-TOF mass spectrometry. Numbers of organisms and diversity were compared over the study period and the presence of any ocular pathogens noted and participants informed, where appropriate, to enhance their compliance with lens care routine.

Results

Organisms isolated from 76 children were generally similar to other studies employing culture methods. However, MALDI-TOF results yielded a wider range of species of micrococci and corynebacteria, as well as a few less frequently reported organisms. Only one culture yielded fungi. Ocular pathogens were only isolated from 9 subjects (4 before lens wear and 5 after lens wear), each on one occasion only. Diversity and numbers of organisms fell slowly over the period of the study, but the changes were not significant.

Conclusions

Lens wear did not affect the overall content of the ocular microbiome, but the diversity was somewhat reduced. The incidence of ocular pathogens was low, suggesting that risk of ocular infection was not substantially increased by orthokeratology treatment using a povidone-iodine disinfecting solution.

Microbiota and Ocular Diseases

Recent advances have identified significant associations between the composition and function of the gut microbiota and various disorders in organ systems other than the digestive tract. Utilizing next-generation sequencing and multiomics approaches, the microbial community that possibly impacts ocular disease has been identified. This review provides an overview of the literature on approaches to microbiota analysis and the roles of commensal microbes in ophthalmic diseases, including autoimmune uveitis, age-related macular degeneration, glaucoma, and other ocular disorders. In addition, this review discusses the hypothesis of the "gut-eye axis" and evaluates the therapeutic potential of targeting commensal microbiota to alleviate ocular inflammation.

Changes in Conjunctival Microbiota Associated With HIV Infection and Antiretroviral Therapy

Purpose

HIV infection is associated with a variety of ocular surface diseases. Understanding the difference of the ocular microbiota between HIV-infected and healthy individuals as well as the influence of antiretroviral therapy will help to investigate the pathogenesis of these conditions.

Methods

A cross-sectional study was conducted on subjects including HIV-negative individuals, untreated HIV-infected individuals, and HIV-infected individuals with antiretroviral therapy. Conjunctival microbiota was assessed by bacterial 16S rRNA sequencing of the samples obtained from the conjunctival swab.

Results

The microbial richness in ocular surface was similar in HIV-negative, untreated HIV-positive, and highly active antiretroviral therapy (HAART) subjects. The bacterial compositions were similar in the two HIV infection groups but were significantly different from the HIV-negative group. HAART changed the beta diversity of bacterial community as determined by Shannon index. CD4+ T cell count had no significant influence on the diversity of ocular microbiota in HIV-infected individuals.

Conclusions

The data revealed the compositional and structural difference in conjunctival microbial community in subjects with and without HIV infection, indicating that HIV infection or its treatment, may contribute to ocular surface dysbiosis.

Demodex Infection Changes Ocular Surface Microbial Communities, in Which Meibomian Gland Dysfunction May Play a Role

INTRODUCTION

Demodex and bacteria are both components of the ocular surface micro-ecology, constituting a complex interaction. This study aims to explore how ocular surface Demodex infestation (DI) affects ocular surface microbial communities and diversity.

METHODS

We recruited 255 subjects, and examined the correlation between ocular surface mite infestation and clinical indicators such as age, blood glucose level, dry eye symptoms, and blood pressure. 16S rRNA sequencing was performed on the conjunctival swab samples of 14 patients with ocular DI (P group) and 17 healthy people (N group). For further analysis, the subjects were divided into four subgroups, i.e. N-NMGD (n = 11), N-MGD (n = 6), P-NMGD (n = 6), and P-MGD (n = 8), according to meibomian gland dysfunction (MGD) or no MGD (NMGD).

RESULTS

There was no difference in the α-diversity of ocular surface microbial communities between the DI and healthy control groups. In linear discriminant analysis effect size (LEfSe), there were more Acinetobacter, Novosphingobium, and Anoxybacillus in the DI group and fewer Novosphingobium, Lactobacillus, and Candidatus Microthrix in the healthy control group. P-NMGD had more Thermaceae and fewer Pseudomonas than P-MGD. There were more Bacteroidetes in N-NMGD than in N-MGD. The α-diversity of P-NMGD was lower than that of N-NMGD (Shannon index, P = 0.027). At the same time, the α-diversity of N-MGD was lower than that of N-NMGD (Shannon, Simpson, and dominance index, P = 0.048). There was no significant difference in β-diversity or in the primary flora at the phylum and genus levels between groups and subgroups.

CONCLUSION

DI had no significant effect on the diversity of ocular surface microbial communities. DI primarily changed the dominant flora and relative abundance of ocular surface microbial communities. MGD may play an important role in this process.