August 2018
Volume 59, Issue 10
Open Access
Immunology and Microbiology  |   August 2018
Identification and Visualization of a Distinct Microbiome in Ocular Surface Conjunctival Tissue
Author Affiliations & Notes
  • Jerome Ozkan
    School of Optometry and Vision Science, University of New South Wales, Sydney, Australia
    School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, Australia
  • Minas Coroneo
    Department of Ophthalmology, Faculty of Medicine, University of New South Wales, Sydney, Australia
  • Mark Willcox
    School of Optometry and Vision Science, University of New South Wales, Sydney, Australia
  • Bernd Wemheuer
    School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, Australia
    Department of Genomic and Applied Microbiology, University of Göttingen, Göttingen, Germany
  • Torsten Thomas
    School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, Australia
  • Correspondence: Jerome Ozkan, Lab 263, Biological Sciences Building D26, Sydney, NSW 2052, Australia; j.ozkan@unsw.edu.au
  • Footnotes
     JO and MC contributed equally to the work presented here and should therefore be regarded as equivalent authors.
Investigative Ophthalmology & Visual Science August 2018, Vol.59, 4268-4276. doi:10.1167/iovs.18-24651
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      Jerome Ozkan, Minas Coroneo, Mark Willcox, Bernd Wemheuer, Torsten Thomas; Identification and Visualization of a Distinct Microbiome in Ocular Surface Conjunctival Tissue. Invest. Ophthalmol. Vis. Sci. 2018;59(10):4268-4276. doi: 10.1167/iovs.18-24651.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: Knowledge of whether microorganisms reside in protected niches of the conjunctiva is potentially significant in terms of minimizing risks of contact lens inflammation/infection and endophthalmitis. We define if and how microbial communities from limbal and forniceal conjunctival tissue differ from those on the conjunctival surface.

Methods: Human limbal and forniceal conjunctival tissue was obtained from 23 patients undergoing pterygium surgery and analyzed with data from a recent study of conjunctival surface swabs (n = 45). Microbial communities were analyzed by extracting total DNA from tissue samples and surface swabs and sequencing the 16S rRNA gene using the Illumina MiSeq platform. Sequences were quality filtered, clustered into operational taxonomic units (OTUs) at 97% similarity. OTUs associated with blank extraction and sampling negative controls were removed before analysis. Fluorescent in situ hybridization (FISH) was performed on cyrosections of limbal and forniceal conjunctival tissue.

Results: There was a significant difference in bacterial community structure between the conjunctival surface and fornix (P = 0.001) and limbus (P = 0.001) tissue. No difference was found in bacterial communities between the limbus and fornix (P = 0.764). Fornix and limbal samples were dominated by OTUs classified to the genus Pseudomonas (relative abundance 79.9%), which were found only in low relative abundances on conjunctival surfaces (6.3%). Application of FISH showed the presence of Pseudomonas in the forniceal tissue sample.

Conclusions: There is a discrete tissue-associated microbiome in freshly-collected human limbal and fornix tissue, which is different from the microbial community structure and composition of the ocular surface microbiome.

Numerous regions of the body contain infolded regions and crypt structures, which support microbial communities different from nearby communities. In mucosal tissues, such as the human gut, specific microbial communities have been found to reside in small infolded areas. For example, Swidsinski et al.1 found bacteria (predominantly Bacteroides) in colonic crypts of patients with inflammatory bowel disease more frequently than in control subjects. The submucosal intestinal tissue in patients with advanced Crohn's disease has been reported to have a distinct microbiome with increased Firmicutes and Proteobacteria compared to the mucosal surfaces.2 Crypt structures in the tonsils also have been reported to have a distinct microbiota.3 Overall, these studies show that specific microorganisms can colonize infolded tissue and, thus, possibly take advantage of resisting removal by liquid flows, such as intestinal or oral fluids. 
Recent studies have shown that microorganisms are able to exist in the ocular mucosa, where they promote pathogen immunity by facilitating neutrophil recruitment.46 Culture-independent microbiome studies have shown that the ocular surface has a richer microbial diversity than previously estimated by culture-based studies.79 The conjunctiva also has infoldings in the fornix and the corneal limbus contains crypt-like structures, called the Palisades of Vogt. However, it is not known whether these conjunctival infoldings or similar niches harbor a distinct microbiota from that of the conjunctival surface. 
The most devastating postoperative complication from cataract surgery or intravitreal injections is exogenous endophthalmitis, which is caused by direct inoculation of the ocular microbiota into the posterior vitreous cavity. Studies have shown that even with extensive sterilization of the ocular surface, sterile needles become contaminated with bacteria from intravitreal injections.10 However, it is possible that bacteria reside within protected intercellular niches of the conjunctiva and, hence, could escape removal. Dong et al.7 suggested the possibility of a depth-stratified conjunctival microbiome, because an increased abundance of Proteobacteria was observed in swabs applied with firm pressure compared to those applied with soft pressure, which had a greater abundance of Firmicutes and Actinobacteria. Therefore, it is important to know if and what kind of microbes colonize the protected niches of the conjunctiva to evaluate their role and risk in endophthalmitis, contact lens-related adverse events, or idiopathic ocular surface disorders with an inflammatory component (e.g., dry eye syndrome, episcleritis, chronic follicular conjunctivitis, or Thygeson's disease). 
Therefore, we investigated if a distinct microbial community exists in the physically enclosed regions of the conjunctiva. For this, conjunctival samples were collected from patients undergoing pterygium surgery. The microbial community of these samples was assessed using sequencing of the bacterial 16S rRNA gene and fluorescence in situ hybridization. 
Methods
The protocol used in this study was approved by the Human Research Ethics Committee of the University of New South Wales (HC15014) and the research followed the tenets of the Declaration of Helsinki. Informed consent was obtained before enrollment of subjects into the study. Specimens were obtained from patients who were undergoing pterygium surgeries with autoconjunctival graft, considered the gold standard treatment.11 Patients were required to be over 18 years of age and were excluded from the study if they had received antibiotics one month before sample collection or were being treated with immunosuppressive drugs. However, patients were permitted to use topical cyclosporine as part of their preoperative treatment regimen, which was ceased before surgery. Patients using systemic medication were included in the study provided the medication was not an antibiotic or immunosuppressant. 
Tissue Sampling
Clinically healthy human limbal and fornix conjunctival tissue was sampled from the superior conjunctiva, remote from the pterygium, from 23 patients undergoing pterygium surgery. During this surgery, grafts were taken from the superior conjunctiva of the same eye from which the pterygium was excised as a reconstructive step. At operation, collected tissue samples were placed on a sterile filter paper strip and placed into a sterile collection tube and immediately frozen at −20°C. Samples were collected from surgery within 48 hours and transported on dry ice to the laboratory and stored at −80°C. Sample controls consisted of a piece of sterile filter paper collected in the same manner, but without the tissue sample. 
DNA Extraction
Genomic DNA was extracted from tissue samples using the NucleoSpin Tissue XS kit (Machery-Nagel, Düren, Germany), including an additional lysis step as described previously by our group.9 Four extractions, consisting of two sample controls (section of sterile filter paper without exposure to tissue samples) and two blank extractions were processed and served as sample- and reagent-negative controls in downstream applications. 
16S rRNA Gene Amplification and Sequencing
The gene amplification and sequencing has been reported previously by our group.9 Briefly, the V4 region of the 16S rRNA gene was amplified by PCR using Illumina tagged primers 515F (5′-GTG BCA GCM GCC GCG GTA A-3′) and 806R (5′-GGA CTA CHV GGG TAT CTA ATC C-3′).12 PCR consisted of 0.2 pmol each of forward and reverse primer (Integrated DNA Technologies, Coralville, IA, USA), 7.5 μL nuclease-free water (Thermo Fisher Scientific, Coralville, MA, USA), 12.5 μL EconoTaq Plus Green 2x MasterMix (Lucigen, Middleton, WI, USA), and 4 μL DNA extracts. A touchdown PCR protocol was used to increase primer annealing specificity and yield.13 The success of the PCR was checked by agarose gel electrophoresis. A 1 kB DNA ladder (Gene Ruler, Thermo Fisher Scientific, Waltham, MA, USA) was used to estimate the size and approximate amount of the PCR product. Gels were imaged with a Gel Doc XR+ (Bio-Rad Laboratories, Hercules, CA, USA). No negative control showed any PCR bands. 
PCR products were purified and libraries were prepared using Illumina sequencing adaptors and dual indices (Nextera XT v2 DNA library preparation kit; Illumina, San Diego, CA, USA). Paired-end amplicon sequencing (MiSeq Reagents kit v2 2 × 250 base pairs [bp] Nano) was performed on the Illumina MiSeq platform at the Ramaciotti Centre for Genomics (University of New South Wales, Sydney, Australia). 
Sequence Analysis
The 16S rRNA gene sequences from the limbal and forniceal tissue were analyzed together with data from our recent study of the conjunctival surface.9 In that study, 45 individuals had ocular surface swabs of the superior and inferior bulbar conjunctiva taken at three time points over 3 months and the identical extraction, amplification, and sequencing protocol was used. Only contamination-free sequencing reads from the first time point were used in the analysis, as our previous study showed no effect of time on community structure or composition.9 
Sequences were quality trimmed using Trimmomatic version 0.3614 and merged with USEARCH version 10.0.240.15 Sequences shorter than 200 or longer than 400 positions as well as low-quality reads and reads with one or more ambiguous base were removed. Remaining sequences were clustered into operational taxonomic units (OTUs) at 97% similarity using the UPARSE algorithm implemented in USEARCH. Chimeric sequences were removed with UCHIME16 de novo during OTU clustering and subsequently also removed with a reference-based comparison against the SSU SILVA NR database version 128 (available in the public domain at www.arb-silva.de).17 OTUs were classified taxonomically against the SILVA database18 using UBLAST. Sequences classified as chloroplasts, mitochondria, eukaryotes, or producing no blast hit were removed, as were OTUs appearing with only one sequence in the entire dataset. 
Rarefaction analysis was used to determine if a complete representation of the fornix, limbus, and surface microbiome had been achieved given the observed sequence sampling depths. Analysis of low-biomass samples increases the potential for DNA contamination giving a false-positive signal for certain microorganisms, particularly when PCR amplification is involved in the analysis,9,19 The study used sample controls and blank extractions and used the indicspecies R package to identify OTUs associated with sample and blank extraction-negative controls.20 Every OTU associated with the negative controls was removed and only OTUs associated with the tissue samples were retained for analysis. Microbial α- and β-diversities were assessed using functions within the vegan R package for community ecology analysis.21 The microbial species diversity (α diversity) was described by the metrics of richness and Shannon index. As the samples were independent, microbial α diversity was compared using linear mixed models (R package lme4) with sampled region, age, and sex as fixed effects and individuals as a random factor. ANOVA was used to test for significance. Residual plots showed no obvious deviations from the assumptions of parametric statistics. The Kruskal-Wallis test was used to compare the relative abundance of bacterial phyla, genera, and OTUs between groups and a post hoc Wilcoxon rank sum test was performed to test for pairwise differences. The microbial β-diversity was compared using the Bray-Curtis (structure) and Jaccard (composition) dissimilarity. Microbial β diversity was compared between the microbiomes of the limbus, fornix, and ocular surface swabs by permutational analysis of variance (PERMANOVA) in vegan. To determine if the use of systemic medication or topical cyclosporine had an effect on the microbial community, a linear mixed model (systemic medication/topical cyclosporine, sampled region, age and sex as fixed factors and individuals as a random factor) was used to assess α diversity (richness and Shannon Diversity Index). The effect of systemic medication or cyclosporine use on β-diversity (structure and composition) was assessed using PERMANOVA. Statistical analysis of the results was performed using the R version 3.1.3 (available in the public domain at http://cran.r-project.org/). Differences were considered statistically significant with P ≤ 0.05. 
Tissue Fixation and Histologic Staining
Three limbal and three fornix tissue specimens (from three different patients) from surgery were immediately placed in ice-cold 4% paraformaldehyde and fixed for 1 hour at 4°C. The tissue subsequently was rinsed with molecular biology-grade ×1 PBS (Thermo Fisher Scientific) for 2 minutes, then cryoprotected by placing it in a 15% sucrose solution (until tissue sank) and 30% sucrose solution (overnight). The tissue was rinsed with PBS, embedded in a cryomold filled with Tissue-Tek OCT compound (Sakura, Tokyo, Japan), frozen by placing cryomold in a dry ice/100% ethanol slurry, and immediately stored at −80°C. Cryosections were performed on specimens at 7 μm and placed on Superfrost-coated slides (Thermo Fisher Scientific). 
Several tissue sections were stained with 0.1% Mayer's hematoxylin for 7 minutes, followed by a cold MilliQ water rinse. Sections were dipped in 0.5% eosin three times and rinsed with MilliQ water for 30 seconds. Finally, sections were serially dehydrated in 50%, 70%, 95%, and 100% ethanol, treated with xylene and mounted. 
Fluorescence In Situ Hybridization (FISH)
The universal bacterial probe EUB338 (5′-GCTGCCTCCCGTAGGAGT-3′)22 and the probe PSE1284 (5′-GATCCGGACTACGATCGGTT-3′),23 which is specific to the Pseudomonas genus, were tested on slides containing limbal and fornix tissue sections. Fixed, frozen cryosections were dehydrated in an ethanol series (50%, 80%, 98%), then air dried. A total of 100 ng/μL of the 16S rRNA-targeted genus-specific and universal oligonucleotides probes (Biomers, Ulm, Germany; Table) was added in 9 μL hybridization buffer (900 mM NaCL, 20 mM Tris-HCl, pH 7.2, 0.01% SD, 30% [vol/vol] formamide) and applied to tissue sections. Samples were incubated for 6 hours at 46°C in the hybridization buffer. Slides then were rinsed with a small volume of prewarmed washing buffer (215 mM NaCL, 20 mM Tris-HCl, 5 mM EDTA, pH 7.2, 0.01% SDS) and immediately transferred into the washing buffer for 20 minutes at 48°C. Slides then were immersed in 4°C MilliQ water for 3 seconds, immediately dried using compressed air, counterstained with 4′,6-diamidino-2-phenylindole (DAPI; 0.1 mg/ml in PBS), rinsed with 4°C MilliQ, allowed to air dry, and mounted in ProLong Gold Antifade mountant (Thermo Fisher Scientific), and allowed to cure for 24 hours in the dark at room temperature before being imaged. Slides were examined under a Nikon A1 spectral confocal microscope and images were processed using ImageJ software.24 
Table
 
Probes Used in the Study
Table
 
Probes Used in the Study
Results
Comparison of Community Structure and Composition Between Fornix, Limbus, and Surface
Healthy limbal and forniceal conjunctival tissue samples from the superior limbus and fornix (remote from the pterygium), were collected from 23 subjects (12 female, 11 male; mean age, 51 ± 18 years) and compared to 45 surface swab samples. After quality and contaminant filtering, there were 1,198,179 sequences with an average of 13,169 sequences per sample. These clustered into 267 OTUs at 97% sequence identity. The calculated rarefaction curves, based on rarefied data (Supplementary Fig. S1) revealed that the majority of the bacterial community was recovered by the surveying effort. 
Assessment of the α diversity metric of richness showed 19.9 ± 4.0 OTUs in the fornix, 24.2 ± 4.6 OTUs in the limbus, and 42.8 ± 10.5 OTUs on the surface (Supplementary Fig. S2). There was no significant variation for the number of OTUs for sex (P = 0.517) or age (P = 0.893), but there was a significant variation between individuals (P = 0.036) and sampling region (P < 0.001). Pairwise comparison showed no difference in richness between the limbus-fornix (P = 0.167), but a difference between the limbus-surface and fornix-surface comparisons (both P < 0.001). The Shannon diversity in the fornix was 1.3 ± 0.4, limbus 1.3 ± 0.4, and on the surface 2.1 ± 0.6 (Supplementary Fig. S3). There was no significant variation in Shannon diversity between individuals (P = 1.000) or for sex (P = 0.542) or age (P = 0.075), but there was a difference for sampling region (P < 0.001). Pairwise comparison showed no difference in Shannon diversity between the limbus-fornix (P = 0.967), but a difference between the limbus-surface and fornix-surface comparisons (both P < 0.001). 
There was a significant difference in bacterial community structure and composition between the surface microbiome and fornix (both analyses PERMANOVA P = 0.001) and the limbus (PERMANOVA P = 0.001; Fig. 1). Comparison between the limbus and fornix found no difference in bacterial community structure (PERMANOVA P = 0.764) or composition (PERMANOVA P = 0.740). Analysis of the microbial dispersion found greater variation in the bacterial communities in the surface samples compared to the fornix and limbus (homogeneity of multivariate dispersions [PERMDISP] P = 0.001). 
Figure 1
 
Nonmetric multidimensional scaling (nMDS) ordination of the limbus tissue fornix tissue microbiome communities compared to surface conjunctiva microbiome (from previous study database) using Bray-Curtis dissimilarity of transformed OTU data (stress 0.17).
Figure 1
 
Nonmetric multidimensional scaling (nMDS) ordination of the limbus tissue fornix tissue microbiome communities compared to surface conjunctiva microbiome (from previous study database) using Bray-Curtis dissimilarity of transformed OTU data (stress 0.17).
There was no effect of systemic medication use on the α diversity metrics of richness (P = 0.316) and Shannon Diversity Index (P = 0.971) or on microbial community structure (PERMANOVA P = 0.070) or composition (PERMANOVA P = 0.066). Furthermore, there was no effect of topical cyclosporine use on richness (P = 0.614), Shannon Diversity Index (P = 0.879), community structure (PERMANOVA P = 0.062), or composition (PERMANOVA P = 0.065). 
Contaminant filtering reduced the number of OTUs from 478 to 432, which could be classified into 13 phyla and 125 genera. There was no difference in relative abundance of phyla between the limbus/fornix and surface (P = 0.271). Of the 125 genera detected, 16 had a relative abundance >1% (Fig. 2). There was a significant difference in relative abundance of genera among the three groups (P < 0.001). Pairwise comparison showed a difference between all groups; limbus and fornix (P = 0.045), surface and limbus (P < 0.001), and surface and fornix (P < 0.001). Sequences assigned to the genus Pseudomonas dominated the fornix (average relative abundance of 80.8%) and limbus (79.9%) compared to the surface (6.3%). In contrast, sequences assigned to the genera Corynebacterium, Streptococcus, and Serratia were found in relatively high abundance in surface samples (13.5%, 4.8%, 8.7%, respectively), but in low abundance in the fornix (0.04%, 0.005%, 1.9%, respectively) and limbus (0.4%, 0.003%, 1.4%, respectively) samples. Genera with similar relative sequence abundance across groups include Acinetobacter (limbus 5.4%, fornix 6.9%, surface 4.3%, respectively), and Thermoanerobacterium (limbus 1.4%, fornix 2.0%, surface 3.9%, respectively). 
Figure 2
 
Relative abundance at the genera-level for the microbial communities of the fornix, limbus, and conjunctival surface. Only genera >1% relative abundance are shown.
Figure 2
 
Relative abundance at the genera-level for the microbial communities of the fornix, limbus, and conjunctival surface. Only genera >1% relative abundance are shown.
There were 18 OTUs with relative abundance >1% (Fig. 3). There was a significant difference in OTUs among the three groups (P < 0.001). Pairwise comparison showed a difference among the three sample groups; limbus and fornix (P = 0.004), surface and limbus, and surface and fornix (both P < 0.001). Analysis of the data at the OTU level revealed again a dominance of OTUs assigned to Pseudomonas in fornix and limbal samples, which was represented by six different OTUs (OTU19, OTU361, OTU343, OTU154, OTU90, OTU294) and which were absent from surface samples (Fig. 3). In contrast Corynebacterium (OTU5), Streptococcus (OTU9), Sphingomonas (OTU7), and Neisseriaceae (OTU10, OTU12) OTUs had a higher relative abundance in surface samples compared to fornix/limbal samples. Some OTUs were clearly shared between the two sample types including Geobacillus (OTU3) and Thermoanerobacterium (OTU6) (Fig. 3). 
Figure 3
 
Relative abundance at the OTU-level for the microbial communities of the fornix, limbus, and conjunctival surface. Only OTUs >1% relative abundance are shown.
Figure 3
 
Relative abundance at the OTU-level for the microbial communities of the fornix, limbus, and conjunctival surface. Only OTUs >1% relative abundance are shown.
Localization of Microorganisms in Fornix and Limbus Tissue
The sequencing data showed a dominance of Pseudomonas in fornix and limbal conjunctival tissue and we next aimed to verify this by FISH. We used the universal bacterial probe EUB33821 and the genus-specific probe PSE1284,23 which targeted the Pseudomonas genus. Fornix and limbal samples were observed by confocal laser scanning microscopy. Although rare, bacteria were observed in tissue samples, as indicated by the sparse signals from the universal bacterial probe (Fig. 4B). Rod-shaped bacteria approximately 1 μm long and 0.5 μm wide hybridized to the Pseudomonas probe and were detected sparingly in some tissue sections and appeared to be deeply embedded in the fornix tissue (Figs. 4C, 4D). 
Figure 4
 
(A) Hematoxylin-eosin staining of a representative fornix tissue section; fluorescence micrographs of section of conjunctival forniceal tissue with fluorescence signal of (B) universal bacterial probe EUB338 (red signal [Cy3]; FISH) and (C, D) Pseudomonas-specific oligonucleotide probe PSE1284 (green signal [6-Pham]; FISH) within tissue; DAPI-stained eukaryotic cellular DNA (blue signal).
Figure 4
 
(A) Hematoxylin-eosin staining of a representative fornix tissue section; fluorescence micrographs of section of conjunctival forniceal tissue with fluorescence signal of (B) universal bacterial probe EUB338 (red signal [Cy3]; FISH) and (C, D) Pseudomonas-specific oligonucleotide probe PSE1284 (green signal [6-Pham]; FISH) within tissue; DAPI-stained eukaryotic cellular DNA (blue signal).
Discussion
This study assessed for the presence of bacteria in freshly collected human limbal and forniceal conjunctival tissue samples and, to our knowledge, is first to investigate eye tissues from these two regions. A comparison of microbiome derived from these tissues showed no difference in microbial community structure or composition between the fornix and limbus, but a clear distinction to the ocular surface microbiomes we analyzed previously.9 This indicated that there may be a discrete tissue-associated microbiome within this tissue. 
The greater richness and diversity of the ocular surface likely represents the greater environmental exposure to transient bacteria of the ocular surface tears (from which samples were taken by swabs). Conversely, the lower richness and diversity of the tissue samples likely represent the result of exposure to the antibiotics/antisepsis preoperatively and the hostile, antimicrobial surface of the eye. The majority of OTUs found in limbal and forniceal tissue samples belong to the Proteobacteria followed by Firmicutes and Actinobacteria, which was broadly comparable to previous ocular microbiome studies.7,9 The most consistently detected genus in the limbus and forniceal conjunctival tissue samples was Pseudomonas, while this was only inconsistently detected at a lower abundance in surface swab. Corynebacterium (phylum Actinobacteria) was the predominant genus on the ocular surface over time9 and previously has been shown to have the highest statistical likelihood of originating from the conjunctiva and not derived from the environment.8 In contrast, microbial community analysis of deeper conjunctival tissue showed low abundances of Corynebacterium and greater relative abundance of Pseudomonas. This difference in microorganisms detected from the surface and deeper layers of the conjunctiva appears to support the findings from a pilot investigation by Dong et al.,7 which used soft versus firm swabbing of the conjunctival surface and found higher abundances of Proteobacteria (Bradyrhiobium, Delftia, and Sphingomonas) with firm swabbing (deeper level) and greater representation of Firmicutes (Staphyloccoci) and Actinobacteria (Corynebacteria spp.) with soft swabbing (surface). Our finding supports the notion that microbiomes on the conjunctival surface are different from those of the deeper tissue, suggesting, indeed, that there is a spatially stratified conjunctival microbiota. 
Pseudomonas is a known ocular pathogen, with P. aeruginosa being the most virulent and most frequently isolated pathogen from contact lens–related keratitis,25 and often is associated with visual impairment,26 P. aeruginosa has a high proportion of regulatory genes, which are thought to permit the organism to adapt to environmental changes and resist antimicrobial substances.27 Perhaps this permits some Pseudomonas bacteria to persist within protected conjunctival niches even after the ocular surface has been rinsed with antiseptic before pterygium surgery. In terms of the normal cultivable microbiota of the ocular surface, Pseudomonas typically is isolated only sporadically from conjunctival swabs (average 2.8% across studies) and slightly more frequently from worn contact lenses (4% across studies).28 Previous work has shown that corneal epithelial cells are able to internalize (and shed) Pseudomonas bacteria.29,30 The visualization of Pseudomonas, although rare and sparsely present, postoperatively on the conjunctiva surface and in the intercellular space in forniceal tissue samples using FISH provides evidence that microorganisms are present on the ocular surface and in surface niche tissue. The finding that these niches contain Pseudomonas sp. may have implications for contact lens wear and ocular surgery. Although the conjunctival tissue was remote from the pterygium of the patients, it is possible that this condition may have influenced the microbiome. Whether the Pseudomonas occupies these protected niches or was surgically introduced is unclear. Furthermore, it remains unknown whether the Pseudomonas was viable at tissue collection (surgery) or had succumbed to the antimicrobial elements in the tears and/or after exposure to the antisepsis/antibiotics associated with the pterygium surgery. Other microorganisms, associated with ocular complications, detected in lower abundances in conjunctival tissue were Serratia (1.6%) and Stenotrophomonas (0.2%). Serratia sp., which has not been noted previously as being part of the normal ocular surface microbiota, has been found on the human skin.31 On the ocular surface Serratia sp. typically have been associated with contact lens–related inflammation and infection32 and with endophthalmitis following cataract surgery33 and intravitreal injections.34 Stenotrophomonas also has been identified as a rare cause of severe infection (endophthalmitis) following cataract surgery.35 
Despite the low abundance of microorganisms present in conjunctival tissue collected during pterygium surgery, detection of Pseudomonas, Serratia, Acinetobacter, and Stenotrophomonas within the conjunctival tissue samples is potentially concerning as these microorganisms are opportunistic human pathogens and emerging as a cause of nosocomial infections.3639 Exogenous endophthalmitis, direct inoculation of the ocular microbiota into the posterior vitreous cavity, can have severe visual consequences for patients. Although the rates of postoperative exogenous endophthalmitis are low, ranging from 0.025% to 0.2%,40 aging-related demographic changes have resulted in increased cataract surgery and increased use of intravitreal injections for treatment of age-related macular degeneration, with a recent study finding more cases of endophthalmitis following intravitreal injections than from cataract surgery.41 de Caro et al.10 found that even after prophylactic swabbing of the bulbar conjunctiva with povidone-iodine and topical antibiotic, 2% of sterile needles were contaminated (using standard culturing methods) with bacteria after intravitreal injections. They postulated that the mechanism for endophthalmitis was possibly due to direct inoculation of the surface bacteria into the posterior chamber or that following injection, the opening made by the injection provides an entry portal for surface bacteria. The possibility exists that bacteria residing within protected niches or micro-habitats in the conjunctiva may be responsible for this contamination. 
Although this study sampled healthy conjunctival tissue remote from the pterygium, there is a potential confounding effect in that the conjunctiva of patients with pterygium may be different from conjunctiva of patients with no pterygium. However, considering that the healthy conjunctival tissue used in this study was the same tissue that was transplanted onto the site of the excised pterygium, and for which studies have found to have low recurrence rate,42 suggests that this is, indeed, healthy conjunctival tissue. Also, as the studies were conducted approximately 6 months apart, there is the possibility of a temporal confounding effect. However, previous investigation of the ocular surface microbiome showed no significant changes over a 3-month period.9 Interestingly, we found no effect of systemic medication or topical cyclosporine use on the ocular microbiome of the conjunctival tissue. A previous culture-based study on cyclosporine treatment in dogs with keratoconjunctivitis sicca found no effect of cyclosporine use on the frequency of bacterial isolation from the ocular surface swabs in nonresponders, but found decreased frequency of bacterial isolation in the responders group.43 
Some microorganisms detected in conjunctival tissue also have been associated with biologic response modifiers, including Serratia, which has an indirect effect on stem cells,44 and Acinetobacter (part of the crypt-specific core microbiota in the gut45), which is capable of modulating epithelia via lipopolysaccharide production.46 Furthermore, maintenance of ocular stem cell regenerative capacity at the limbus and in the fornix is critical to ocular surface health, with failure of either or both, potentially resulting in corneal blindness. While there have been advances in understanding mechanisms that promote stem cell maintenance,47 only recently has the potential role of the microbiome been explored. It appears that in the gut, cecal crypts devoid of their microbiota display loss of their regenerative capacity.48 Whereas the gut has a relatively complicated niche structure,49 the ocular surface may be less so and more accessible and may be an ideal place to investigate these interactions. 
Acknowledgments
The authors thank Michael Carnell, PhD, from the Biomedical Imaging Facility, University of New South Wales, for expert advice regarding laser confocal microscopy and image analysis. 
Supported by a Faculty Research Grant from the Faculty of Science, University of New South Wales. and an Australian Government National Health and Medical Research Council (NHMRC) Peter Doherty Biomedical Fellowship (APP1112537, JO). The authors alone are responsible for the content and writing of the paper. 
Disclosure: J. Ozkan, None; M. Coroneo, None; M. Willcox, None; B. Wemheuer, None; T. Thomas, None 
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Figure 1
 
Nonmetric multidimensional scaling (nMDS) ordination of the limbus tissue fornix tissue microbiome communities compared to surface conjunctiva microbiome (from previous study database) using Bray-Curtis dissimilarity of transformed OTU data (stress 0.17).
Figure 1
 
Nonmetric multidimensional scaling (nMDS) ordination of the limbus tissue fornix tissue microbiome communities compared to surface conjunctiva microbiome (from previous study database) using Bray-Curtis dissimilarity of transformed OTU data (stress 0.17).
Figure 2
 
Relative abundance at the genera-level for the microbial communities of the fornix, limbus, and conjunctival surface. Only genera >1% relative abundance are shown.
Figure 2
 
Relative abundance at the genera-level for the microbial communities of the fornix, limbus, and conjunctival surface. Only genera >1% relative abundance are shown.
Figure 3
 
Relative abundance at the OTU-level for the microbial communities of the fornix, limbus, and conjunctival surface. Only OTUs >1% relative abundance are shown.
Figure 3
 
Relative abundance at the OTU-level for the microbial communities of the fornix, limbus, and conjunctival surface. Only OTUs >1% relative abundance are shown.
Figure 4
 
(A) Hematoxylin-eosin staining of a representative fornix tissue section; fluorescence micrographs of section of conjunctival forniceal tissue with fluorescence signal of (B) universal bacterial probe EUB338 (red signal [Cy3]; FISH) and (C, D) Pseudomonas-specific oligonucleotide probe PSE1284 (green signal [6-Pham]; FISH) within tissue; DAPI-stained eukaryotic cellular DNA (blue signal).
Figure 4
 
(A) Hematoxylin-eosin staining of a representative fornix tissue section; fluorescence micrographs of section of conjunctival forniceal tissue with fluorescence signal of (B) universal bacterial probe EUB338 (red signal [Cy3]; FISH) and (C, D) Pseudomonas-specific oligonucleotide probe PSE1284 (green signal [6-Pham]; FISH) within tissue; DAPI-stained eukaryotic cellular DNA (blue signal).
Table
 
Probes Used in the Study
Table
 
Probes Used in the Study
Supplement 1
Supplement 2
Supplement 3
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