The Microbiome of the Meibum and Ocular Surface in Healthy Subjects

Thermosensitive TRP Channels Are Functionally Expressed and Influence the Lipogenesis in Human Meibomian Gland Cells

While the involvement of thermosensitive transient receptor potential channels (TRPs) in dry eye disease (DED) has been known for years, their expression in the meibomian gland (MG) has never been investigated. This study aims to show their expression and involvement in the lipogenesis of the MG, providing a possible new drug target in the treatment of DED. Our RT-PCR, Western blot and immunofluorescence analysis showed the expression of TRPV1, TRPV3, TRPV4 and TRPM8 in the MG at the gene and the protein level. RT-PCR also showed gene expression of TRPV2 but not TRPA1. Calcium imaging and planar patch-clamping performed on an immortalized human meibomian gland epithelial cell line (hMGECs) demonstrated increasing whole-cell currents after the application of capsaicin (TRPV1) or icilin (TRPM8). Decreasing whole-cell currents could be registered after the application of AMG9810 (TRPV1) or AMTB (TRPM8). Oil red O staining on hMGECs showed an increase in lipid expression after TRPV1 activation and a decrease after TRPM8 activation. We conclude that thermo-TRPs are expressed at the gene and the protein level in MGs. Moreover, TRPV1 and TRPM8's functional expression and their contribution to their lipid expression could be demonstrated. Therefore, TRPs are potential drug targets and their clinical relevance in the therapy of meibomian gland dysfunction requires further investigation.

Composition and diversity of meibum microbiota in meibomian gland dysfunction and the correlation with tear cytokine levels

Meibomian gland dysfunction (MGD) leads to meibum stasis and pathogenic bacteria proliferation. We determined meibum microbiota via next-generation sequencing (NGS) and examined their association with tear cytokine levels in patients with MGD. This cross-sectional study included 44 moderate-severe patients with MGD and 44 healthy controls (HCs). All volunteers underwent assessment with the ocular surface disease index questionnaire, Schirmer without anesthesia, tear break-up time, Oxford grading of ocular surface staining, and lid and meibum features. Sample collection included tears for cytokine detection and meibum for 16S rRNA NGS. No significant differences were observed in the α-diversity of patients with MGD compared with that in HCs. However, Simpson's index showed significantly decreased α-diversity for severe MGD than for moderate MGD (p = 0.045). Principal coordinate analysis showed no significant differences in β-diversity in meibum samples from patients with MGD and HCs. Patients with MGD had significantly higher relative abundances of Bacteroides (8.54% vs. 6.00%, p = 0.015) and Novosphingobium (0.14% vs. 0.004%, p = 0.012) than the HCs. Significantly higher interleukin (IL)-17A was detected in the MGD group than in the HC group, particularly for severe MGD (p = 0.008). Although Bacteroides was more abundant in the MGD group than in the HC group, it was not positively correlated with IL-17A. The relationship between core meibum microbiota and tear cytokine levels remains unclear. However, increased Bacteroides and Novosphingobium abundance may be critical in MGD pathophysiology.

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

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

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.

Conjunctival microbiome changes in soft contact lens users and contact lens discomfort patients

INTRODUCTION

Contact lens discomfort (CLD) acts as a challenging problem, and the associated conjunctival microbiome changes were unclear.

MATERIAL AND METHODS

Conjunctival sac swab samples were collected from 12 eyes of nonwearers (NW), 12 eyes of asymptomatic contact lens (ACL) wearers, and 11 eyes of CLD. The V3-V4 region of the 16S rRNA gene sequencing was used to investigate differences among three groups.

RESULTS

No differences in alpha diversity were observed among the three groups. The beta diversity showed a distinct microbiome composition between ACL and CLD group (P = 0.018) with principal coordinate analysis. The relative abundance of Firmicutes was significantly higher in CLD (48.18%) than in ACL (13.21%) group (P = 0.018). The abundance of Bacillus in patients with ACL (0.05%) or with CLD (0.02%) were significantly lower than that in the NW (1.27%) group (P = 0.024, 0.028, respectively). Moreover, the abundance of Firmicutes was positively correlated with the OSDI scores in CLD patients (r = 0.817, P < 0. 01, Spearman).

DISCUSSIONS

Patients with CLD have various degrees of bacterial microbiota imbalance in the conjunctival sac, compared with NW and ACL groups.

CONCLUSION

Firmicutes may serve as a potential biomarker for the CLD patients.

Comparison of Conjunctival Sac Microbiome between Low and High Myopic Eyes

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

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.

Shotgun metagenomic sequencing analysis of ocular surface microbiome in Singapore residents with mild dry eye

The ocular surface microbiome has implications for ocular surface inflammation and immunology. Previous shotgun metagenomics analyses were performed in China, showing results that differed according to environment and age. Patients with Sjogren's syndrome were reported to have altered conjunctival microbiome, but such studies have not been done in milder dry eye. The aim of this study is to describe the conjunctival microbiome in people with mild dry eye in Singapore. Samples were collected from 14 participants with mild dry eye and 10 age-matched comparison participants recruited from Singapore National Eye Centre (SNEC) clinics. Shotgun metagenomic sequencing analysis was employed to evaluate the conjunctival microbiome composition. Proteobacteria formed the predominant phylum in the conjunctiva. As in a study from a coastal city in China, Achromobacter spp. was numerically most abundant. Compared to age-matched controls, the conjunctival microbial composition in mild dry eye was similar. Several microorganisms, including Streptococcus spp. increased in representation with age, and the abundance of Staphylococcus correlated with Schirmer readings. In addition, when cultured corneal epithelial cells were exposed to three strains of Achromobacter xylosoxidans, cytokines such as TNF-α and IL-6 were upregulated in the cell lysates and supernatants. Ourresults suggest that age is an important factor that affects composition of the conjunctival microbiome, and relative abundance of specific microorganism may vary according to the environment of the human host.

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.

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

Purpose

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

Methods

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

Results

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

Conclusions

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

Metagenomic profiling of ocular surface microbiome changes in Demodex blepharitis patients

Purpose

To compare the ocular surface and meibum microbial communities of humans with Demodex Blepharitis (DB) and healthy controls.

Methods

Conjunctival sac and meibum samples from 25 DB patients and 11 healthy controls were analyzed using metagenomic next-generation sequencing (mNGS).

Results

The alpha-diversity of the conjunctival sac microbiome of the DB group (observed, Chao1, ACE) was lower than that of the control group, whereas all meibum diversity indicators were similar. In conjunctival samples, the relative abundance (RA) of the phylum Proteobacteria was significantly higher (p=0.023), and the RA of both phyla Actinobacteria and Firmicutes was significantly lower (p=0.002, 0.025, respectively) in the DB group than that in the control group. In meibum samples, the RA of the phyla Proteobacteria and Actinobacteria were similar, whereas that of the phylum Firmicutes was significantly lower in the DB group (p=0.019) than that in the control group. Linear discriminant analysis with effect size measurement of the conjunctival and meibum microbiomes showed that Sphingobium sp. YG1 and Acinetobacter guillouiae were enriched in the DB group. Sphingobium sp. YG1, Acinetobacter guillouiae and Pseudomonas putida in the DB group were related to more severe ocular surface clinical parameters. Discriminative genera’s principal coordinate analysis separated all control and DB microbiomes into two distinct clusters.

Conclusions

Proteobacteria’s increased prevalence may indicate ocular microbial community instability. The species Sphingobium sp. YG1 and Acinetobacter guillouiae are potentially pathogenic bacterial biomarkers in DB. Demodex infection mainly affects the ocular surface microbiome rather than penetrating deeper into the meibomian gland.

DivCom: A Tool for Systematic Partition of Groups of Microbial Profiles Into Intrinsic Subclusters and Distance-Based Subgroup Comparisons

When analyzing microbiome data, one of the main objectives is to effectively compare the microbial profiles of samples belonging to different groups. Beta diversity measures the level of similarity among samples, usually in the form of dissimilarity matrices. The use of suitable statistical tests in conjunction with those matrices typically provides us with all the necessary information to evaluate the overall similarity of groups of microbial communities. However, in some cases, this approach can lead us to deceptive conclusions, mainly due to the uneven dispersions of the groups and the existence of unique or unexpected substructures in the dataset. To address these issues, we developed divide and compare (DivCom), an automated tool for advanced beta diversity analysis. DivCom reveals the inner structure of groups by dividing their samples into the appropriate number of clusters and then compares the distances of every profile to the centers of these clusters. This information can be used for determining the existing interrelation of the groups. The proposed methodology and the developed tool were assessed by comparing the response of anemic patients with or without inflammatory bowel disease to different iron replacement therapies. DivCom generated results that revealed the inner structure of the dataset, evaluated the relationship among the clusters, and assessed the effect of the treatments. The DivCom tool is freely available at: https://github.com/Lagkouvardos/DivCom.

Temporal impacts of topical ceftazidime and tobramycin-vancomycin mixtures on the ocular surface microbiota in rabbits

Antibiotics are one of the important factors that can alter the diversity and composition of ocular surface microbiota. At present, there are a few studies about the antibiotic effect on ocular surface microbiota, including its time-dependent changes. However, these limited studies have revealed various results, and more experiments are required. In this study, we used 16 S rRNA sequencing method to investigate the effects of topical ceftazidime and tobramycin-vancomycin mixtures on the ocular surface microbiota and the temporal changes of the microbiota after discontinuing antibiotic treatment in rabbits. Seventeen healthy rabbits were treated with 5% ceftazidime and a mixture of 0.3% tobramycin-5% vancomycin (CTV) eye drops on one eye four times a day for 7 days. Swab samples of conjunctiva sacs were collected before antibiotic treatment (D0), 12 h after the last antibiotic treatment (D8) and two further time points on Day 15 (D15) and Day 30 (D30). We found that the species diversity of the ocular surface microbiota increased significantly at D8 and was restored at D15, namely, one week after antibiotic cessation. The community structure of the ocular surface microbiota changed after treatment with CTV but recovered at D30. At D8, the relative abundances of 13 bacterial phyla of the initial top 20 phyla and 11 bacterial genera of the initial top 20 genera were significantly different from the relative abundances of the phyla and genera at D0. Furthermore, the relative abundance of the dominant phylum Epsilonbacteraeota obviously decreased, while Proteobacteria and Bacteroidetes markedly increased. For dominant genera, the relative abundance of Helicobacter notably decreased, while Acinetobacter and Pasteurella greatly increased. Thirteen altered bacterial phyla and 7 of 11 altered bacterial genera recovered to preantibiotic levels at D30. In addition, there was a group of nondominant and rare bacteria enriched at D8, and most of them were restored at D30. In conclusion, the species diversity, community structure and composition of the ocular surface microbiota changed greatly after exposure to CTV, but they tended to be restored within weeks after discontinuing antibiotic treatment.

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.

Fungi of the human eye: Culture to mycobiome

The focus of the current review is multi-fold and compares the diversity and abundance of fungi on the ocular surface by the conventional culture-based method with the more sensitive, high throughput, culture-independent NGS method. The aim is to highlight the existence of a core ocular mycobiome and explore the transition of the ocular fungal microbiota from the normal eye to the diseased eye. PubMed, Google Scholar and Medline were used to search for publications and reviews related to cultivable fungi and the mycobiome of the normal and diseased eye. The conventional cultivable approach and the NGS approach confirm that the eye has its own mycobiome and several confounding factors (age, gender, ethnicity etc.) influence the mycobiome. Further, dysbiosis in the mycobiome appears to be associated with ocular diseases and thus impacts the health of the human eye. Considering that the mycobiome of the eye is influenced by several confounding factors and also varies with respect to the disease status of the eye there is a need to extensively explore the mycobiome under different physiological conditions, different ethnicities, geographical regions etc. Such studies would unravel the diversity and abundance of the mycobiomes and contribute to our understanding of ocular health. Research focused on ocular mycobiomes may eventually help to build a targeted and individualized treatment.

Comparison of 16S rDNA Amplicon Sequencing With the Culture Method for Diagnosing Causative Pathogens in Bacterial Corneal Infections

Purpose

The purpose of this study was to explore if 16S rDNA amplicon sequencing can improve the conventional diagnosis of causative pathogens for bacterial corneal infection.

Methods

Corneal scraping and conjunctiva and eyelid margin swab samples from infected eyes of patients diagnosed with "bacterial corneal infection" and conjunctiva and eyelid margin swab samples from a random eye of healthy participants were collected. Each swab was used for both aerobic and anaerobic cultures and 16S rDNA amplicon sequencing. The V3 to V4 region of the 16S rDNA was amplified using polymerase chain reaction (PCR) and sequenced on the Illumina HiSeq 2500 Sequencing Platform.

Results

The overall culture positivity rate for all 72 samples was 69% (72% in the bacterial keratitis group and 67% in the healthy control group), whereas 1719 operational taxonomic units in total were generated using 16S rDNA amplicon sequencing with each sample showing 123 to 337 different genera. Staphylococcus, Corynebacterium, Propionibacterium, and Micrococcus most frequently appeared in culture, whereas Streptococcus, Acinetobacter, and Lactobacillus were the most common genera, with large ratios in 16S rDNA amplicon sequencing. The causative pathogens detected by the two methods were inconsistent for most samples, except for several corneal samples.

Conclusions

We suggest that a combination of different techniques, such as clinical observation, microscopic analysis, culture, and next-generation sequencing techniques including 16S rDNA amplicon sequencing, should be used to comprehensively analyze pathogens in corneal and external ocular infections.

Translational Relevance

This paper uses a basic research methodology for studying the microbiome in ocular samples to help improve the diagnostic accuracy of corneal and external ocular infections.

Mucosal immunology of the ocular surface

The eye is a sensory organ exposed to the environment and protected by a mucosal tissue barrier. While it shares a number of features with other mucosal tissues, the ocular mucosal system, composed of the conjunctiva, Meibomian glands, and lacrimal glands, is specialized to address the unique needs of (a) lubrication and (b) host defense of the ocular surface. Not surprisingly, most challenges, physical and immunological, to the homeostasis of the eye fall into those two categories. Dry eye, a dysfunction of the lacrimal glands and/or Meibomian glands, which can both cause, or arise from, sensory defects, including those caused by corneal herpes virus infection, serve as examples of these perturbations and will be discussed ahead. To preserve vision, dense neuronal and immune networks sense various stimuli and orchestrate responses, which must be tightly controlled to provide protection, while simultaneously minimizing collateral damage. All this happens against the backdrop of, and can be modified by, the microorganisms that colonize the ocular mucosa long term, or that are simply transient passengers introduced from the environment. This review will attempt to synthesize the existing knowledge and develop trends in the study of the unique mucosal and immune elements of the ocular surface.

Composition and Diversity of the Ocular Surface Microbiota in Patients With Blepharitis in Northwestern China

Purpose: To investigate the composition and diversity of the microbiota on the ocular surface of patients with blepharitis in northwestern China via 16S rDNA amplicon sequencing.

Methods: Thirty-seven patients with blepharitis divided into groups of anterior, posterior and mixed blepharitis and twenty healthy controls from northwestern China were enrolled in the study. Samples were collected from the eyelid margin and conjunctival sac of each participant. 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 in taxonomy and diversity among different groups were compared.

Results: The composition of the ocular surface microbiota of patients with blepharitis was similar to that of healthy subjects, but there were differences in the relative abundance of each bacterium. At the phylum level, the abundances of Actinobacteria, Cyanobacteria, Verrucomicrobia, Acidobacteria, Chloroflexi, and Atribacteria were significantly higher in the blepharitis group than in the healthy control group, while the relative abundance of Firmicutes was significantly lower (p < 0.05, Mann-Whitney U). At the genus level, the abundances of Lactobacillus, Ralstonia, Bacteroides, Akkermansia, Bifidobacterium, Escherichia-Shigella, Faecalibacterium, and Brevibacterium were significantly higher in the blepharitis group than in the healthy control group, while the relative abundances of Bacillus, Staphylococcus, Streptococcus, and Acinetobacter were significantly lower in the blepharitis group (p < 0.05, Mann-Whitney U). The microbiota of anterior blepharitis was similar to that of mixed blepharitis but different from that of posterior blepharitis. Lactobacillus and Bifidobacterium are biomarkers of posterior blepharitis, and Ralstonia is a biomarker of mixed blepharitis. There was no significant difference in the ocular surface microbiota between the eyelid margin and conjunctival sac with or without blepharitis.

Conclusion: The ocular surface microbiota of patients with blepharitis varied among different study groups, according to 16S rDNA amplicon sequencing analysis. The reason might be due to the participants being from different environments and having different lifestyles. Lactobacillus, Bifidobacterium, Akkermansia, Ralstonia, and Bacteroides may play important roles in the pathogenesis of blepharitis.

The evidence for placental microbiome and its composition in healthy pregnancies: A systematic review

OBJECTIVE

To assess the available scientific evidence regarding the placental microbial composition of a healthy pregnancy, the quality of this evidence, and the potential relation between placental and oral microbiome.

MATERIALS AND METHODS

Data sources: MEDLINE and EMBASE up to August 1, 2019.

STUDY ELIGIBILITY CRITERIA

Human subjects; healthy women; term deliveries; healthy normal birth weight; assessment of microorganisms (bacteria) in placental tissue; full research papers in English. The quality of the included studies was assessed by a modified Joanna Briggs Institute checklist for analytical cross-sectional studies.

RESULTS

57 studies passed the inclusion criteria. Of these, 33 had a high risk of quality bias (e.g., insufficient infection control, lack of negative controls, poor description of the healthy cases). The remaining 24 studies had a low (N = 12) to moderate (N = 12) risk of bias and were selected for in-depth analysis. Of these 24 studies, 22 reported microorganisms in placental tissues, where Lactobacillus (11 studies), Ureaplasma (7), Fusobacterium (7), Staphylococcus (7), Prevotella (6) and Streptococcus (6) were among the most frequently identified genera. Methylobacterium (4), Propionibacterium (3), Pseudomonas (3) and Escherichia (2), among others, although frequently reported in placental samples, were often reported as contaminants in studies that used negative controls.

CONCLUSIONS

The results support the existence of a low biomass placental microbiota in healthy pregnancies. Some of the microbial taxa found in the placenta might have an oral origin. The high risk of quality bias for the majority of the included studies indicates that the results of individual papers should be interpreted with caution.

Ocular microbial diversity, community structure, and function at high altitude

PURPOSE

To investigate the composition and function of ocular surface microbiome in healthy people from different altitudes.

METHODS

Thirty-two healthy people living in a high altitude region and 30 sex- and age-matched individuals living in a low altitude region were enrolled. Samples were collected from the lower conjunctival sac of one randomly chosen eye for each participant. 16S rRNA sequencing was conducted to study the bacterial community composition and predict gene function using PICRUSt software.

RESULTS

Microbial diversity and richness was significantly decreased in samples from highlanders as calculated by Abundance-based Coverage Estimator (ACE) index, Chao1 index, and observed-species index (all p < 0.01). Principle coordinate analysis (PCoA) suggested significantly distinct clustering of the conjunctival sac bacterial communities between two groups (p = 0.03), especially the dominant genera. The relative abundances of Corynebacterium, Staphylococcus, and Anaerococcus were significantly enriched in highlanders, while those of Pseudomonas and Massilia were significantly decreased as compared with lowlanders (p < 0.01). In the functional annotation analysis, we found that 74 gene pathways, mainly in metabolism, differed in abundance. Pathways related to immune system diseases and infectious diseases were also enriched in highlanders.

CONCLUSION

The composition and function of ocular surface microbiome in highlanders were distinct from those of lowlanders and our study may provide a reference catalog of the healthy conjunctival microbiome in highlanders.

Alteration in meibum lipid composition and subjective symptoms due to aging and meibomian gland dysfunction

PURPOSE

To investigate the alteration in lipid composition of meibum, objective clinical signs, and subjective symptoms associated with aging and meibomian gland (MG) dysfunction (MGD).

METHODS

In 10 MGD patients [4 males/6 females, mean age: 65.6 ± 7.9 years (range: 50-79 years)] and 24 healthy volunteer subjects [young subjects: 6 males/6 females, mean age: 25.7 ± 3.8 years (range: 20-35 years), elderly subjects: 6 males/6 females, mean age: 58.4 ± 7.5 years (range: 50-79 years)], three objective clinical signs were evaluated: MG orifice obstruction, meibum score, and tear film lipid layer interference pattern. Subjective symptoms were analyzed via a 15-item questionnaire. After careful collection of meibum samples, comprehensive lipid analysis was performed via liquid chromatography-mass spectrometry. Data was analyzed via JMP® ver. 13 (SAS Institute, Inc., Cary, NC) statistical analysis software.

RESULTS

In the MGD patients and elderly subjects, there was a significant decrease in non-polar lipids such as cholesterol esters (ChEs), while a significant increase in polar lipids [cholesterol (Ch), (O-acyl)-ω-hydroxy fatty acid (OAHFA), and free fatty acid (FA)] in total lipids (Tukey-Kramer test: p < 0.05). Triglyceride was significantly increased only in MGD patients (p < 0.05). Symptom scores representative of vision quality (i.e., blurred vision/haziness) were significantly negatively-correlated with the ratio of the non-polar lipid ChE, while significantly positively correlated with the polar lipids Ch, OAHFA, and FA (Spearman's rank correlation coefficient: p < 0.05).

CONCLUSIONS

Our findings revealed that both MGD and aging affect the composition ratio of major meibum lipids, resulting in the appearance of subjective symptoms.

Hyperkeratinization and Proinflammatory Cytokine Expression in Meibomian Glands Induced by Staphylococcus aureus

Purpose

This exploratory study aimed to investigate the morphological and pathological alterations of the meibomian gland (MG) with the Staphylococcus aureus crude extracts (SACEs) treatment.

Methods

Mouse MG explants were cultured and differentiated with or without SACEs for 48 hours. Explant's viability and cell death were determined by thiazolyl blue tetrazolium bromide (MTT) assay and TUNEL assay. MG morphology was observed by Hematoxylin and Eosin staining. Lipid droplet production was detected by Nile Red staining and LipidTox immunostaining. The pro-inflammatory cytokines were detected by ELISA. The relative gene and protein expression in MG explants was determined via quantitative RT-PCR, immunostaining, and immunoblotting. The components of the SACEs were analyzed by immunoblotting and silver staining.

Results

Our findings demonstrated that the SACEs treatment induced overexpression of keratin 1 (Krt1) in the ducts and acini of MG explants, accompanied by a decrease in viability and an increase in cell death in explants. Furthermore, the SACEs treatment dose-dependently increased the levels of TNF-α, IL-1β, and IL-6 in MG explants. The SACEs treatment induced activation of the nuclear factor kappa B (NF-κB) and AIM2 (absent in melanoma 2)/ASC (apoptosis-associated speck-like protein containing a caspase recruitment domain) inflammasome signaling pathway in explants. Further investigation showed expression of the key adipogenesis-related molecule peroxisome proliferator-activated receptor γ was decreased after SACEs treatment. However, no change was found in the lipid synthesis of MG explants after treatment with the SACEs. Staphylococcal enterotoxins B (SEB) was detected in the SACEs. SEB induced the overexpression of Krt1 and IL-1β in ducts and acini of MG explants.

Conclusions

Our findings confirm that Staphylococcus aureus induced hyperkeratinization and pro-inflammatory cytokines expression in MG explants ducts and acini. These effects might be mediated by SEB. Activation of the NF-κB and AIM2/ASC signaling pathway is involved in this process.

Features of the Skin Microbiota in Common Inflammatory Skin Diseases

Many relatively common chronic inflammatory skin diseases manifest on the face (seborrheic dermatitis, rosacea, acne, perioral/periorificial dermatitis, periocular dermatitis, etc.), thereby significantly impairing patient appearance and quality of life. Given the yet unexplained pathogenesis and numerous factors involved, these diseases often present therapeutic challenges. The term “microbiome” comprises the totality of microorganisms (microbiota), their genomes, and environmental factors in a particular environment. Changes in human skin microbiota composition and/or functionality are believed to trigger immune dysregulation, and consequently an inflammatory response, thereby playing a potentially significant role in the clinical manifestations and treatment of these diseases. Although cultivation methods have traditionally been used in studies of bacterial microbiome species, a large number of bacterial strains cannot be grown in the laboratory. Since standard culture-dependent methods detect fewer than 1% of all bacterial species, a metagenomic approach could be used to detect bacteria that cannot be cultivated. The skin microbiome exhibits spatial distribution associated with the microenvironment (sebaceous, moist, and dry areas). However, although disturbance of the skin microbiome can lead to a number of pathological conditions and diseases, it is still not clear whether skin diseases result from change in the microbiome or cause such a change. Thus far, the skin microbiome has been studied in atopic dermatitis, seborrheic dermatitis, psoriasis, acne, and rosacea. Studies on the possible association between changes in the microbiome and their association with skin diseases have improved the understanding of disease development, diagnostics, and therapeutics. The identification of the bacterial markers associated with particular inflammatory skin diseases would significantly accelerate the diagnostics and reduce treatment costs. Microbiota research and determination could facilitate the identification of potential causes of skin diseases that cannot be detected by simpler methods, thereby contributing to the design and development of more effective therapies.

A Janus-Faced Bacterium: Host-Beneficial and -Detrimental Roles of Cutibacterium acnes

The bacterial species Cutibacterium acnes (formerly known as Propionibacterium acnes) is tightly associated with humans. It is the dominant bacterium in sebaceous regions of the human skin, where it preferentially colonizes the pilosebaceous unit. Multiple strains of C. acnes that belong to phylogenetically distinct types can co-exist. In this review we summarize and discuss the current knowledge of C. acnes regarding bacterial properties and traits that allow host colonization and play major roles in host-bacterium interactions and also regarding the host responses that C. acnes can trigger. These responses can have beneficial or detrimental consequences for the host. In the first part of the review, we highlight and critically review disease associations of C. acnes, in particular acne vulgaris, implant-associated infections and native infections. Here, we also analyse the current evidence for a direct or indirect role of a C. acnes-related dysbiosis in disease development or progression, i.e., reduced C. acnes strain diversity and/or the predominance of a certain phylotype. In the second part of the review, we highlight historical and recent findings demonstrating beneficial aspects of colonization by C. acnes such as colonization resistance, immune system interactions, and oxidant protection, and discuss the molecular mechanisms behind these effects. This new insight led to efforts in skin microbiota manipulation, such as the use of C. acnes strains as probiotic options to treat skin disorders.

Acute Radiation Syndrome and the Microbiome: Impact and Review

Study of the human microbiota has been a centuries-long endeavor, but since the inception of the National Institutes of Health (NIH) Human Microbiome Project in 2007, research has greatly expanded, including the space involving radiation injury. As acute radiation syndrome (ARS) is multisystemic, the microbiome niches across all areas of the body may be affected. This review highlights advances in radiation research examining the effect of irradiation on the microbiome and its potential use as a target for medical countermeasures or biodosimetry approaches, or as a medical countermeasure itself. The authors also address animal model considerations for designing studies, and the potential to use the microbiome as a biomarker to assess radiation exposure and predict outcome. Recent research has shown that the microbiome holds enormous potential for mitigation of radiation injury, in the context of both radiotherapy and radiological/nuclear public health emergencies. Gaps still exist, but the field is moving forward with much promise.

Pathophysiology of Meibomian Glands - An Overview

Purpose: The meibomian glands are located in the tarsal plate of the upper and lower eyelid and are responsible for the production of a lipid-rich secretion, the meibum, which forms the outer component of the tear film. Meibomian gland dysfunction results in excessive evaporation of the tear film and is the leading cause of dry eye disease (DED). Despite the high prevalence of DED, the etiology of meibomian gland dysfunction is only basically understood. In addition, the molecular mechanisms of meibomian gland maturation and physiological function are currently the focus of research.Methods: A systematic literature search was performed using the main scientific databases, including all relevant published articles up to September 2020.Results: This article provides an overview of the current state of knowledge about meibomian gland stem cells, cell surface marker expression and PPARγ signaling, as well as the pathological causes of meibomian gland dysfunction.Conclusion: Androgen deficiency, hyperkeratinization, PPARγ signaling and inflammatory reactions including neutrophil extracellular traps (NETs) seem to be key factors within the pathological processes of the meibomian gland.

Infectious keratitis: an update on epidemiology, causative microorganisms, risk factors, and antimicrobial resistance

Corneal opacity is the 5th leading cause of blindness and visual impairment globally, affecting ~6 million of the world population. In addition, it is responsible for 1.5-2.0 million new cases of monocular blindness per year, highlighting an ongoing uncurbed burden on human health. Among all aetiologies such as infection, trauma, inflammation, degeneration and nutritional deficiency, infectious keratitis (IK) represents the leading cause of corneal blindness in both developed and developing countries, with an estimated incidence ranging from 2.5 to 799 per 100,000 population-year. IK can be caused by a wide range of microorganisms, including bacteria, fungi, virus, parasites and polymicrobial infection. Subject to the geographical and temporal variations, bacteria and fungi have been shown to be the most common causative microorganisms for corneal infection. Although viral and Acanthamoeba keratitis are less common, they represent important causes for corneal blindness in the developed countries. Contact lens wear, trauma, ocular surface diseases, lid diseases, and post-ocular surgery have been shown to be the major risk factors for IK. Broad-spectrum topical antimicrobial treatment is the current mainstay of treatment for IK, though its effectiveness is being challenged by the emergence of antimicrobial resistance, including multidrug resistance, in some parts of the world. In this review, we aim to provide an updated review on IK, encompassing the epidemiology, causative microorganisms, major risk factors and the impact of antimicrobial resistance.

The ocular surface immune system through the eyes of aging

Since the last century, advances in healthcare, housing, and education have led to an increase in life expectancy. Longevity is accompanied by a higher prevalence of age-related diseases, such as cancer, autoimmunity, diabetes, and infection, and part of this increase in disease incidence relates to the significant changes that aging brings about in the immune system. The eye is not spared by aging either, presenting with age-related disorders of its own, and interestingly, many of these diseases have immune pathophysiology. Being delicate organs that must be exposed to the environment in order to capture light, the eyes are endowed with a mucosal environment that protects them, the so-called ocular surface. As in other mucosal sites, immune responses at the ocular surface need to be swift and potent to eliminate threats but are at the same time tightly controlled to prevent excessive inflammation and bystander damage. This review will detail how aging affects the mucosal immune response of the ocular surface as a whole and how this process relates to the higher incidence of ocular surface disease in the elderly.

The porcine corneal surface bacterial microbiome: A distinctive niche within the ocular surface

Purpose

The ocular surface microbiome has been described as paucibacterial. Until now, studies investigating the bacterial community associated with the ocular surface through high-throughput sequencing have focused on the conjunctiva. Conjunctival samples are thought to reflect and be representative of the microbiome residing on the ocular surface, including the cornea. Here, we hypothesized that the bacterial community associated with the corneal surface was different from those of the inferonasal and superotemporal conjunctival fornices, and from the tear film.

Methods

Both eyes from 15 healthy piglets were sampled using swabs (inferonasal fornix, superotemporal fornix, and corneal surface, n = 30 each) and Schirmer tear test strips (STT, n = 30). Negative sampling controls (swabs and STT, n = 2 each) and extraction controls (n = 4) were included. Total DNA was extracted and high-throughput sequencing targeting the 16S rRNA gene was performed. Bioinformatic analyses included multiple contamination-controlling steps.

Results

Corneal surface samples had a significantly lower number of taxa detected (P<0.01) and were compositionally different from all other sample types (Bray-Curtis dissimilarity, P<0.04). It also harbored higher levels of Proteobacteria (P<0.05), specifically Brevundimonas spp. (4.1-fold) and Paracoccus spp. (3.4-fold) than other sample types. Negative control STT strip samples yielded the highest amount of 16S rRNA gene copies across all sample types (P<0.05).

Conclusions

Our data suggests that the corneal surface provides a distinct environmental niche within the ocular surface, leading to a bacterial community compositionally different from all other sample types.

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.

Physiological effects of inactivation and the roles of Elovl3/ELOVL3 in maintaining ocular homeostasis

Recently, elongase of very long chain fatty acids-3 (ELOVL3) was demonstrated to play a pivotal role in physiology and biochemistry of the ocular surface by maintaining a proper balance in the lipid composition of meibum. The goal of this study was to further investigate the effects of ELOVL3 ablation in homozygous Elovl3-knockout mice (E3hom) in comparison with age and sex matched wild-type controls (E3wt). Slit lamp examination of the ocular surface of mice, and histological examination of their ocular tissues, highlighted a severe negative impact of Elovl3 inactivating mutation on the Meibomian glands (MG) and conjunctiva of mice. MG transcriptomes of the E3hom and E3wt mice were assessed and revealed a range of up- and downregulated genes related to lipid biosynthesis, inflammation, and stress response, compared with E3wt mice. Heat stage polarized light microscopy was used to assess melting characteristics of normal and abnormal meibum. The loss of Elovl3 led to a 8°C drop in the melting temperature of meibum in E3hom mice, and increased its fluidity. Also noted were the excessive accumulation of lipid material and tears around the eye and severe ocular inflammation, among other abnormalities.

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.

Mucosa-Associated Lymphoid Tissue and Tertiary Lymphoid Structures of the Eye and Ear in Laboratory Animals

Mucosa-associated lymphoid tissue (MALT) of special senses is poorly described and can be confused with nonspecific mononuclear cell infiltrates and tertiary lymphoid structures (TLS). In the eye, MALT consists mostly of conjunctiva-associated lymphoid tissue (CALT) and lacrimal drainage-associated lymphoid tissue (LDALT). In humans, CALT and LDALT are important components of the normal eye-associated lymphoid tissue (EALT), but EALT is less frequently described in ocular tissues of animals. The EALT are acquired postnatally in preferential mucosal sites, expand with antigenic exposure, form well-developed lymphoid follicles, and are reported to senesce. Lymphoid follicles that are induced concurrently with chronic inflammation are more appropriately considered TLS but must be differentiated from inflammation in MALT. Less understood is the etiology for formation of lymphoid tissue aggregates in the ciliary body, limbus, or choroid of healthy eyes in animals and humans. In the healthy eustachian tube and middle ear of animals and humans, MALT may be present but is infrequently described. Concurrent with otitis media, lymphoid follicles in the eustachian tube are probably expanded MALT, but lymphoid follicles in the middle ear may be TLS. The purpose of this comparative review is to familiarize toxicologic pathologists with MALT in the special senses and to provide considerations for differentiating and reporting eye and ear MALT from immune or inflammatory cell infiltrates or inflammation in nonclinical studies, and the circumstances for reporting TLS in compartments of the eye and ear.

Seasonal patterns of incidence, demographic factors and microbiological profiles of infectious keratitis: the Nottingham Infectious Keratitis Study

PURPOSE

The purpose of this study is to examine the seasonal patterns of incidence, demographic factors and microbiological profiles of infectious keratitis (IK) in Nottingham, UK.

METHODS

A retrospective study of all patients who were diagnosed with IK and underwent corneal scraping during 2008-2019 at a UK tertiary referral centre. Seasonal patterns of incidence (in per 100,000 population-year), demographic factors, culture positivity rate and microbiological profiles of IK were analysed.

RESULTS

A total of 1272 IK cases were included. The overall incidence of IK was highest during summer (37.7, 95% confidence interval (CI): 31.3-44.1), followed by autumn (36.7, 95% CI: 31.0-42.4), winter (36.4, 95% CI: 32.1-40.8) and spring (30.6, 95% CI: 26.8-34.3), though not statistically significant (p = 0.14). The incidence of IK during summer increased significantly over the 12 years of study (r = 0.58, p = 0.049), but the incidence of IK in other seasons remained relatively stable throughout the study period. Significant seasonal variations were observed in patients' age (younger age in summer) and causative organisms, including Pseudomonas aeruginosa (32.9% in summer vs. 14.8% in winter; p < 0.001) and gram-positive bacilli (16.1% in summer vs. 4.7% in winter; p = 0.014).

CONCLUSION

The incidence of IK in Nottingham was similar among four seasons. No temporal trend in the annual incidence of IK was observed, as reported previously, but there was a significant yearly increase in the incidence of IK during summer in Nottingham over the past decade. The association of younger age, P. aeruginosa and gram-positive bacilli infection with summer was likely attributed to contact lens wear, increased outdoor/water activity and warmer temperature conducive for microbial growth.

A Genomic Approach to Investigating Ocular Surface Microorganisms: Monitoring Core Microbiota on Eyelid Margin with a Dot hybridization Assay

A sound ocular surface microbiota has been recognized as a part of ocular surface health following a growing body of evidence from next-generation sequencing technique and metagenomic analysis. However, even from the perspective of contemporary precision medicine, it is difficult to directly apply these new technologies to clinical practice. Therefore, we proposed a model based on dot hybridization assay (DHA) to bridge conventional culture with a metagenomic approach in investigating and monitoring ocular surface microbiota. Endophthalmitis, mostly caused by bacterial infection, is the most severe complication of many intraocular surgeries, such as cataract surgery. Hazardous microorganisms hiding and proliferating in the ocular surface microbiota not only increase the risk of endophthalmitis but also jeopardize the effectiveness of the preoperative aseptic procedure and postoperative topical antibiotics. The DHA model enables the simultaneous assessment of bacterial bioburden, detection of target pathogens and microorganisms, and surveillance of methicillin/oxacillin resistance gene mecA in the ocular surface microbiota. This assay revealed heavier bacterial bioburden in men, compatible with a higher risk of endophthalmitis in male patients who underwent cataract surgery. No occurrence of endophthalmitis for these patients was compatible with non-hazardous microorganisms identified by specific dots for target pathogens. Moreover, the mecA dot detected oxacillin-resistant strains, of which culture failed to isolate. Therefore, the DHA model could provide an alternative genomic approach to investigate and monitor ocular surface microorganisms in clinical practice nowadays.