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Review Article

Ocular Surface Microbiome in Health and Disease

Gomes, José Álvaro P. MD, PhD; Frizon, Luciana MD; Demeda, Vanessa F. MD

Author Information
Asia-Pacific Journal of Ophthalmology: November-December 2020 - Volume 9 - Issue 6 - p 505-511
doi: 10.1097/APO.0000000000000330
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Humans and our microbiomes have most likely coevolved to form a physiological community that is composed of distinct body site niches. The convergence and divergence of these niches (made up of collective germs like bacteria, fungi, and viruses) result in metabolically and antigenically vibrant diverse communities of microbes. These microbes include mutualists (symbiotically beneficial microbes), commensals (microbes neither harmful nor beneficial to the host), and pathogens (microbes detrimental to the host).1,2 Our current knowledge of the human microbiome has arisen through complex analyses carried out with genome technology (Tables 1 and 2).

TABLE 1 - Distribution of the Typical Microbiome of the Ocular Surface, According to Culture-Based and 16S rRNA Sequencing Studies
Culture-Based Studies20–24 16S rRNA Sequencing Studies17,18
Commonly detected genera Coagulase-negative staphylococci PropionibacteriumCorynebacteriumStaphylococcus aureusStreptococcus CorynebacteriumAcinetobacterPseudomonasStaphylococcusPropionibacteriumStreptococcus
Phylum level:-Actinobacteria (53%): Corynebacterium and Propionibacterium-Proteobacteria (39%): Pseudomonas and Acinetobacter-Firmicutes (8%): Staphylococcus and Streptococcus-Bacteriodetes
Sporadically detected genera Pseudomonas aeruginosaHaemophilus influenzaeMegasphaera elsdeniiBacteroides ureolyticusBacteroides pneumosintesStomatococcus sp.17,18,20 Bacillus
rRNA indicates ribosomal ribonucleic acid.

TABLE 2 - Distribution of Microbiome in Selected Diseases
Disease Microbiota-Associated
Diabetes No difference between diabetes and controls50,51Increased Staphylococcus aureus52More diversity and increased Proteobacteria53Increased Bacteriodetes, decreased Proteobacteria54
Alcoholism Increased Staphylococcus55
Dry eye and meibomian gland dysfunction Blepharitis: Increased Staphylococcus, Streptophyta, Corynebacterium, Enhydrobacter, and a decrease of Propionibacterium56Meibomian gland dysfunction: Increased frequency of Propionibacterium acnes, decreased Staphylococcus57Dry eye: Increased Staphylococcus aureus, Corynebacterium, and Propionibacterium58Increased Rhodococcus and Klebsiella oxytoca5,59
Sjögren syndrome No difference between Sjögren and controls10
Trachoma Increased Corynebacterium and Streptococcus, lower diversity40
Stevens-Johnson syndrome Increased coagulase-negative staphylococci and Corynebacterium, more pathogenic species61Coagulase-negative Staphylococcus62Corynebacterium, Streptococcus, more pathogenic species24
Chronic limbal stem cell deficiency Staphylococcus epidermidis, Staphylococcus aureus, Pseudomonas aeruginosa63
Chronic ocular graft-versus-host disease Staphylococcus, alpha-haemo Streptococcus, Corynebacterium, Propionibacterium acnes, aerobic gram-positive cocci, Haemophilus influenzae, and aerobic gram-positive rod64
Allergic conjunctivitis Lower alpha diversity65
Behçet disease Staphylococcus aureus, Moraxella, Streptococcus66

The Human Microbiome Project has analyzed the largest cohort and set of 5 major areas of our bodies: the oral cavity, airways, the skin, the gastrointestinal tract, and the vagina.1,3,4 Each mucosal region represents a distinct microbial niche within the human body, where the microbiomes are determined by host site factors that include pH and oxygen levels. The microbiome is further refined through interactions with its environment, including diet and antibiotic exposure. Some mucosal sites, such as the gastrointestinal tract, have a bacterial genome >100 times the size of the human genome.3 Other surfaces, such as the ocular surface, are paucibacterial, with approximately 0.06 bacterium per human cell.3,5,6 Although the human genome contains approximately 20,000 genes, the microbiome, however, contains approximately 8 million genes. It is important to note that the microbiome is not composed of only bacteria; rather, viruses and fungi are also present in the microbiome of healthy people.3,5,6 In the future, describing the nonbacterial components of the microbiome will be an increasingly important avenue of research.5,7,8

Humans require commensal microbes for vital functions, which include developmental, defensive, nutritional, and physiologic processes. For example, bacteria help us extract nutrients from food, defend against pathogens, and maintain the immune system in check.5,9 Indeed, preliminary studies of the gut have shown that these commensal bacteria contribute to maintaining homeostasis and shaping immunity.5,7,8 For example, Clostridium difficile colitis, irritable bowel syndrome, and inflammatory bowel disease are all believed to involve dysregulation of the gut microbiome. Therefore, the successful treatment of C. difficile colitis with fecal microbiota transplantation provides strong evidence to support the therapeutic manipulation of gut microbes.10 Importantly, additional studies have also linked the microbiota to risks of a variety of other diseases that include colon cancer, diabetes, obesity, and most recently, inflammatory diseases such as rheumatoid arthritis. It is thought that these diseases arise through the alteration of large-scale host immune relationships.2,5,11

The gut-eye axis is especially relevant to the field of ophthalmology, as gut bacteria seem to influence immunity at distant sites, which includes the eye.12 A variety of ocular conditions, such as Sjögren-associated dry eye, glaucoma, diabetic retinopathy, infectious keratitis, and macular degeneration, have all been associated with gut microbiome abnormalities.5,10

Although it is true that the tear film is a critical physical barrier between the eye and its environment, it should be noted that the commensal bacteria on the ocular surface also play a role in both adaptive and innate immunity. Indeed, the eye has fostered a harmonious relationship with commensal bacteria on the ocular surface. For example, in a cell-culture model, the healthy epithelial cells of the cornea and conjunctiva did not produce an inflammatory response to commensal bacteria such as Staphylococcus epidermidis or Propionibacterium acnes. Conversely, epithelial cells of the eye produced inflammatory cytokines (IL-6 and IL-8) when they were exposed to pathogens, such as Pseudomonas aeruginosa.5,13

Previous studies describing surface microbes used the only available technique at the time, the conventional culture-based approach. After specimens are collected, they are seeded on some type of solid media (typically blood or chocolate agar) or liquid medium (thioglycolate broth or brain heart infusion). The specimens are then generally incubated at 37°C, examined daily for bacterial growth for 1 week, and subjected to weekly examinations for up to 1 month. Cultures that showcase growth of at least 2 strains of bacteria on any plate, or changes in the color or turbidity of the broth medium, are considered to be positive. Liquid broth specimens considered positive are subcultured on blood agar plates to identify the microbe. The microbes’ phenotypes are then arrived through observing the isolated colonies and their morphotinctorial characteristics through a bacterioscope after Gram staining, and under optical microscopy.14,15 Although this approach identifies viable bacteria, the bacteria that it does detect are only those that grow in these standardized laboratory conditions. Bacterial growth is highly dependent on the incubation conditions that are used, which include the type of media, the atmospheric conditions (ie, aerobic, microaerophilic, and anaerobic), and the duration of the incubation period. It has been estimated that the vast majority of bacteria have not been cultivated within the laboratory.15,16

By contrast, however, culture-independent methods are used to target specific genes present only within bacteria. The 16S ribosomal ribonucleic acid (rRNA) gene, for example, is the standard technique in prokaryotic community sampling. After collecting the specimens, deoxyribonucleic acid (DNA) is extracted from the complex microbial communities through an established process; subsequently, primers are utilized to target the conserved parts. After the targeting of the conserved parts, variable regions of these genes can be amplified simultaneously into taxonomically different bacteria or fungi. The amplified DNA is further sequenced, quality filtered, and clustered into operational taxonomic units. The operational taxonomic units are then annotated using reference databases that include the Ribosomal Database Project, SILVA, Greengenes, and the National Center for Biotechnology Information GenBank database.16–18 This method not only allows an entire microbial community to be described, but it further defines the relative abundance of these communities spatially and temporally. However, it should be specified that 16S rRNA gene sequencing does not distinguish between viable and nonviable microbes. Less frequently employed methods for characterizing microbial communities include whole genome sequencing (more commonly used for analyzing microbial metabolic and functional pathways) and in silico karyotyping.17

Recently, ophthalmologists have become interested in quantifying the composition of the ocular surface microbiome and its role in ocular surface physiology. Here we summarize the literature about ocular surface microbiome by conventional culture-based and 16S rRNA sequencing.


The first description in the literature of the ocular surface microbiota dates back to the 1930s. At this time, researchers used culture-dependent techniques to identify microbial species. At that time, coagulase-negative staphylococci, Propionibacterium spp., Corynebacterium spp., Staphylococcus aureus, and Streptococcus were thought to make up the bulk of the ocular surface microbiome.18,19 The microbiome composition, measured through culture-dependent methods, varied little between the 1930s and the present day, and between regions, as reported in studies conducted in Brazil, Japan, Korea, United States, Finland, Uganda, and rural populations of Sierra Leone.20–24 Some variations described as commensal microbes of ocular microbiome included P. aeruginosa, Haemophilus influenzae,20Megasphaera elsdenii, Bacteroides ureolyticus, Bacteroides pneumosintes, and Stomatococcus sp.25

A recent systematic review of 11 published controlled cohorts used 16S rRNA sequencing to define, at a phylum level, the most commonly present bacteria or the core genera. The review found that Corynebacterium was present in all publications (11/11), comprising a median proportion of 10% of the species found in the eye microbiome. Corynebacterium was followed by Acinetobacter (9/11; 6%), Pseudomonas (8/11; 19%), Staphylococcus (7/11; 6%), Propionibacterium (7%), and Streptococcus (3%) (both 5/11). Bacillus, although not considered to be part of the core microbiome (4/11), was fairly abundant (8%) when present.18 The major phyla were found to be Proteobacteria (Pseudomonas), Actinobacteria (Corynebacterium and Propionibacterium), Firmicutes (Staphylococcus and Streptococcus), and Bacteroidetes, with the first 2 being the most abundant.2,5,7,17,18,26–36


Culture-based studies have highlighted changes in the microbiota isolated during life. Immediately after birth, the neonatal conjunctiva has a higher level of positive cultures and a greater diversity of species compared with other moments in the human lifecycle. Although coagulase-negative Staphylococcus and Propionibacterium dominate it, the conjunctiva also contains microbiota similar to that of the cervix, and after 2 days, fewer microbes (including pathogenic bacteria) are isolated from the conjunctiva.17,37,38 From 3 to 90 years of age, aerobic cocci and Propionibacterium are the most common in the younger age group, decreasing with age. However, Corynebacterium and an increased proportion of anaerobic cocci among anaerobes become more frequent with age.17,25

Using 16S rRNA sequencing, 1 study found differences in the microbiome of adults over the age of 18 years, with a mean of 38 ± 10 years.39 However, another research study indicated that although there was no impact of sex on the microbial diversity, there was a significantly higher richness and Shannon index exhibited in children.40

In 2017, Wen et al found that male and female groups differed only in the beta diversity of bacterial communities. This same study found that younger adults were dramatically different from older adults in terms of beta diversity. Age groups, however, showed significant differences in bacterial composition and metabolic functions. Moreover, several antibiotic resistance genes were enriched in the conjunctival microbiome of old adults. These results suggested that the aging process is a risk factor that changes the immune homeostasis of the ocular surface through alterations of its commensal microbiome.32 Previous reports have indicated that a sex-steroid imbalance after menopause initiates profound changes in the ocular surface microenvironment, thereby predisposing women to many autoimmune, inflammatory, and allergic ocular diseases, including dry eye syndrome.32,41

A publication using 16S rRNA sequencing described the phyla levels of the microbiome core at a pediatric level (younger than 18 years’ old). The 3 main phyla were Actinobacteria, which represented 53% of bacteria, Proteobacteria, which represented 39%, and Firmicutes, which represented 8%. No core genera belong to the phylum Bacteroidetes.18 Cavuoto et al, in 2018, found that samples from children younger than 18 years consistently had a greater overall abundance of bacteria compared with adults.42

16S rRNA sequencing studies of the ocular region in healthy cohorts have been conducted globally in countries that have included the United States, China, South Korea, Australia, The Gambia, and Northern Ireland.17 Even with this climatic and geographic variation, however, the majority of studies showed remarkable similarity at the phylum level with Proteobacteria, Firmicutes, and Actinobacteria predominating. At the genus level, Corynebacterium, Staphylococcus, Streptococcus, and Propionibacterium were detected consistently, with variances in the relative abundance, in all studies. Interestingly, Pseudomonas and Acinetobacter were consistently detected across geographic regions by most studies, albeit with differences in the relative abundance.17


Ozkan et al, in 2018, described the microbial communities that reside in various microhabitats on the ocular surface: limbal, fornix conjunctival tissue, eyelid margin tissue, and facial skin swabs.17,43,44 The microbial community structure differed significantly between sites, with the skin having the most abundant quantity of bacteria and the conjunctiva having the lowest. There were no differences found in the bacterial community between the limbus and fornix. The genus Pseudomonas was distributed differently, however, with a high relative abundance on the conjunctiva (80%) and eyelid tissue (65%), less so on the skin (6%) and the ocular surface (2%).17,18


Two publications using 16S rRNA sequencing compared the ocular surface swabs of contact lens (CL) wearers versus non-wearers. These publications found some variability in abundance, yet no significant difference in alpha diversity. Another publication (n = 20) reported an ocular surface microbiome in lens wearers that was more similar to that of non–CL wearers’ skin under the eye. Furthermore, lens wearers had a higher interindividual variability of their ocular microbiota than non–lens wearers,45 and Proteobacteria dominated microbiome in CL wearers. Hypotheses that help explain this finding have included that the CL may transfer skin bacteria to the eye, that the lens selects for more skin-like bacterial microbiome composition, or that the lens alters the ocular surface barrier and therefore permits bacteria migration.45,29

Retuerto et al analyzed the CL belonging to 42 healthy wearers, correlating the effect of multipurpose solutions versus peroxide disinfection systems on bacterial DNA. Eighty percent of the lenses were negative for bacterial DNA. The lack of bacterial DNA was significantly more common (P = 0.004) when a peroxide disinfection system was used. Furthermore, increased diversity and abundance were found when a multipurpose solution was used, with Corynebacterium, Haemophilus, and Streptococcus being more abundant in lenses maintained with multipurpose solution.18,46

An additional study found that gram-positive bacteria were differentially distributed in those who wear CLs, with a higher load exhibited on the lower lid margins when compared with the load on the upper bulbar conjunctiva.5,47 Additionally, in one prospective longitudinal study that had a sample of 330 new extended-wear CL wearers, contact lens–H. influenzae was more frequently isolated from patients who developed contact lens–associated red eye and symptomatic infiltrates compared with those with no ocular surface changes.48 Cumulatively, the data from these studies suggest that the ocular surface microbiome is altered with CL wear; this alteration could be a risk factor for the development of an infection.5


One study, using the culture-dependent method, evaluated the effect that using glaucoma eye drops had on conjunctival bacterial flora against a control group that did not use the drops. The most frequent bacteria that were reported in both of the groups were coagulase-negative staphylococci. There was no difference reported between patients who used eye drops containing a dose of benzalkonium chloride of 0.01% or higher versus those containing a dose <0.01%.49 Similar culture rates were reported in patients that suffered from dry eye syndrome and were actively using eye drops compared with those that did not.20 They found that the eye drop group had a lower culture-positive rate of bacteria in the conjunctival sac; this is likely due to the fact that the bacteria were being physically washed out by the eye drops.20,49



Analyzed data from culture-dependent studies have conflicting results regarding the influence of diabetes on ocular flora. For instance, 1 Japanese study found no significant difference in the bacterial detection rate among individuals with variable diabetes statuses, hemoglobin A1c levels, diabetic retinopathy, or glycosuria.50 Similarly, a study in Turkey, explicitly designed to explore the differences in bacteria cultured from diabetic and nondiabetic patients, reported that there was no difference in culture rates between the 2 groups. However, this study did find a statistically significant (P = 0.018) higher rate of gram-negative organisms that were cultured from diabetic patients.51 Furthermore, a study based in Bangladesh found 64% and 38% culture-positive rates for diabetic (n = 50) and nondiabetic (n = 250) patients respectively, also reporting higher rates of S. aureus isolation in diabetic patients.52

Ham et al found through 16S rRNA sequencing that the microbial community of diabetic patients was more diverse than that of healthy volunteers. Specifically, Proteobacteria, Firmicutes, Actinobacteria, Cyanobacteria, and Bacteroidetes were found to be the dominant taxa present on the ocular surface; furthermore, there was a significant difference in the relative abundance of the bacterial phyla between the diabetic patients and control subjects. More specifically, Proteobacteria were more abundant in the diabetic group, whereas Firmicutes were more abundant in the control group. Analysis of bacterial taxa at the genus level illustrated that the core microbiome of diabetic patients was comprised of Acinetobacter, Burkholderia, Sphingomonas, and Ralstonia, whereas that of the controls was comprised of Bradyrhizobiaceae, Staphylococcus, Corynebacterium, Pseudomonas, Novosphingobium, Neisseriaceae, and Acinetobacter.53

Another study with 16S rRNA sequencing showed more diversity in the ocular surface microbiota of people with type 2 diabetes mellitus than in a control group. Bioinformatic analysis showed that there was a lower abundance of Proteobacteria and a higher abundance of Bacteroidetes; furthermore, there was a significantly increased abundance of Acinetobacter and Pseudomonas in the group with type 2 diabetes mellitus.54


A 2015 study found changes in the composition of ocular surface flora with a significantly higher incidence of Staphylococcus in subjects with chronic alcoholism when compared with the general population.55

Dry Eye and Meibomian Gland Dysfunction

One study found an increase in the relative abundance of Staphylococcus, Streptophyta, Corynebacterium, and Enhydrobacter, alongside a decrease of Propionibacterium in patients that had blepharitis (this was compared to healthy controls without blepharitis).56 Specifically, blepharitis was defined by clinical findings on slit-lamp examinations, which included lid margin or tarsal conjunctival erythema, telangiectasia, bulbar conjunctival hyperemia, thickening or irregularity of the eyelid margins, or meibomian gland orifice inclusions. These findings, however, differ from Watters et al, who focused their research on individuals with meibomian gland dysfunction (MGD) (defined as the presence of terminal duct obstruction, lid margin thickening, bulbar hyperemia, telangiectasia, and/or altered meibomian gland secretions, graded on a composite 3-point severity scale). In the latter study, individuals without MGD had the highest abundance of Staphylococcus, whereas cases that exhibited moderate-severe MGD had the lowest abundance. Furthermore, the authors of this research demonstrated that individuals with severe MGD had a higher frequency of P. acnes that was recovered from the ocular surface.57

It has been found that dry eye has additionally been associated with ocular surface microbiome alterations. For instance, 1 report related higher frequencies of S. aureus, coagulase-negative Staphylococcus, and Corynebacterium, in individuals with dry eye (defined by symptomatology, tear break-up time <10 seconds, and combined fluorescein and lissamine green staining ≥3) than in control groups.58 Furthermore, in another study, individuals who exhibited dry eye were found to have a higher relative abundance of the potential pathogens, Rhodococcus and Klebsiella oxytoca, compared with control groups. Additionally, the individuals with dry eye showcased an upward trend of increased bacterial counts and decreased goblet cell numbers.5,59

Sjögren Syndrome

One study collected microbiome samples from the inferior conjunctiva of 8 healthy volunteer controls that included 6 rosacea patients and 15 Sjögren syndrome (SS) patients. Subsequently, these patients were analyzed through 16S rRNA sequencing. A core microbiome consisting predominantly of Firmicutes, Actinobacteria, Proteobacteria, and Bacteroidetes phyla was found from all 3 groups without significant differences in overall composition, richness, or structure of ocular surface microbiome between the 3 groups.10

This same study induced a mouse model of SS by subjecting mice to 10 days of desiccating stress and antibiotics. As part of the study, they also characterized the microbiota fecal by evaluating the effects of intestinal dysbiosis on the dry eye phenotype. In this mouse model, worse dry eye phenotype was associated with decreased Clostridium in stool and a relative increase in Enterobacter, Escherichia/Shigella, and Pseudomonas in stool, in comparison with the controls. The dry eye phenotype was also associated with greater relative abundances of Pseudobutyrivibrio, Escherichia/Shigella, Blautia, and Streptococcus, and a lower relative abundance of Bacteroides, Parabacteroides, Faecalibacterium, and Prevotella than in the controls. The severity of ocular and systemic SS was found to be inversely correlated with microbial diversity. This correlation suggests that SS is marked by a dysbiotic intestinal microbiome that is driven by the low relative abundance of commensal bacteria and a high relative abundance of potentially pathogenic genera. In turn, the dysbiotic intestinal microbiome is associated with intensified cases of ocular mucosal disease.10,60


One report comparing the conjunctival microbiome of 220 residents of The Gambia, some with healthy eyes and some with trachoma, found 610 genera belonging to 22 phyla by 16S rRNA gene sequencing. Corynebacterium, Streptococcus, Propionibacterium, Staphylococcus, Bacillus, and Ralstonia were exhibited by at least 80% of all participants with normal conjunctiva. However, Pseudomonas was present at <1% of the relative abundance. A decreased diversity and an increased abundance of Corynebacterium and Streptococcus were seen in participants with conjunctival scarring in comparison to the controls.40

Stevens-Johnson Syndrome

In a nonrandomized study that included a total of 41 eyes of 22 patients with Stevens-Johnson syndrome (SJS), the frequency of testing positive for conjunctiva culture was higher than that which has been historically reported in healthy patients. Specifically, coagulase-negative staphylococci and Corynebacterium were the prominent species that were represented in the positive tests. Half of the patients (54%) tested positive for multiple bacterial species in their flora. Furthermore, it was shown that cultures grew pathogenic bacteria such as Enterobacter, Serratia nonliquefaciens, Escherichia coli, Morganella morganii, Proteus mirabilis, and Haemophilus.61

In another study of the ocular microbiome in SJS, it was shown that the frequency of a positive culture was significantly higher in cases than in the control groups without SJS (59% vs 12.9%). Here, coagulase-negative Staphylococcus was the most common organism found in both individuals with SJS and the control groups. It is important to note, however, that cultures from individuals with SJS also grew Enterobacter, Streptococcus viridians, and Micrococcus, which were not found in the controls.62

A recent study included 20 chronic SJS patients and 20 healthy subjects for microbiome analysis by conventional cultures and next-generation sequencing methods. Positive-cultured specimens were found in 60% of the SJS group and 10% of the healthy volunteers. Corynebacterium and Streptococcus were the more frequent bacteria. In the control group, S. epidermitis was the most frequent. 16S rRNA sequencing has found that the greater diversity of microbial species, the higher proportion of pathogenic microbes, including Pseudomonas, Staphylococcus, Streptococcus, and Acinetobacter, are to be found in the SJS group.24

Chronic Limbal Stem Cell Deficiency

One study with 13 patients found a positive conjunctival swab culture in all of them. These patients exhibited both chronic limbal stem cell deficiency due to SJS and ocular chemical injury, and were undergoing cultivated oral mucosal epithelial transplantation. The most common organism isolated was S. epidermidis, followed by S. aureus and P. aeruginosa.63

Chronic Ocular Graft-Versus-Host Disease

One study evaluated the conjunctival microbe, using conventional culture-based methods, of 32 eyes of 20 ocular graft-versus-host disease (GVHD) patients and 28 eyes of 20 non-GVHD cases, and found more complex diversity of the ocular surface microbes in the GVHD group. Staphylococcus, alpha-haemo Streptococcus, Corynebacterium species, P. acnes, aerobic gram-positive cocci, H. influenzae, and aerobic gram-positive rod were all observed in the GVHD patients, whereas few species were detected in the other group.64

Allergic Conjunctivitis

One study in allergic rhinoconjunctivitis patients related a negative correlation between ocular surface microbiome diversity and allergy severity. Allergic conjunctivitis patients showed a lower alpha diversity with increasing disease severity, challenging the results of the nasopharyngeal microbiome. Interestingly, the bacterial community of the nasal mucosa became more similar to that of the conjunctiva in the allergic patients.65

Behçet Disease

In a study with Behçet disease with culture had significantly higher rates of colonization with S. aureus, Moraxella, and Streptococcus in Behçet disease patients.66


At first, when culture-dependent methods were the only ones available, the bacteria of our normal ocular microbiome were classified only by the genus level. The genera would be described according to their physiochemical characteristics and by how microbes respired in the microbiological process. In essence, the only identifiable bacteria were coagulase-negative staphylococci, Propionibacterium, Corynebacterium, S. aureus, and Streptococcus, with some variations.17,18,20

Since the advent of 16S rRNA sequencing, including amplicon and metagenomic sequencing, it has now been possible to discover previously undescribed bacteria, more complex communities, and culture-resistant bacteria. With the new 16S rRNA sequencing technique, the core bacteria (40% of the total ocular surface) of the surface microbiome in healthy humans have been better defined at the phylum level. The core bacteria, including Actinobacteria (Corynebacterium and Propionibacterium), represent precisely 53% of the ocular surface microbiome, followed by Proteobacteria (Pseudomonas and Acinetobacter) accounting for 39%, and Firmicutes (Staphylococcus and Streptococcus) for 8%.18

Summarizing the results of this review, normal microbiomes differ by sex, geographic distribution, microhabitat on the eye, eye drop use, and CL use, as discussed in detail previously. The microbiome has been studied in selected systemic diseases, including diabetes and alcoholism. Logically, the eye surface microbiome has also been studied in various eye diseases that have included dry eye and MGD, allergic conjunctivitis, SJS, SS, trachoma, chronic limbal stem cell deficiency, chronic ocular GVHD, and Behçet disease.

In years past, bacteria were primarily studied in relationship to pathologies and with a focus on diagnostics and therapy. However, the research community has steadily been increasing its appreciation of the normal microbiome as we begin to understand the importance of immune-modulating functions and relationships between microbes, the eye, and other organs.


1. Aagaard K, Petrosino J, Keitel W, et al. The Human Microbiome Project strategy for comprehensive sampling of the human microbiome and why it matters. FASEB J 2013; 27:1012–1022.
2. Zegans ME, Van Gelder RN. Considerations in understanding the ocular surface microbiome. Am J Ophthalmol 2014; 158:420–422.
3. Human Microbiome Project Consortium. Structure, function, and diversity of the healthy human microbiome. Nature 2012; 486:207–214.
4. Human Microbiome Project Consortium. A framework for human microbiome research. Nature 2012; 486:215–221.
5. Cavuoto KM, Banerjee S, Galor A. Relationship between the microbiome and ocular health. Ocul Surf 2019; 17:384–392.
6. Doan T, Akileswaran L, Andersen D, et al. Paucibacterial microbiome and resident DNA virome of the healthy conjunctiva. Invest Ophthalmol Vis Sci 2016; 57:5116–5126.
7. Kernbauer E, Ding Y, Cadwell K. An enteric virus can replace the beneficial function of commensal bacteria. Nature 2014; 516:94–98.
8. Sartor RB, Wu GD. Roles for intestinal bacteria, viruses, and fungi in pathogenesis of inflammatory bowel diseases and therapeutic approaches. Gastroenterology 2017; 152:327–339. doi:10.1053/j.gastro.2016.10.012.
9. Cavuoto KM, Galor A, Banerjee S. Anatomic characterization of the ocular surface microbiome in children. Microorganisms 2019; 7:259Published August 14, 2019. doi:10.3390/microorganisms7080259.
10. de Paiva CS, Jones DB, Stern ME, et al. Altered mucosal microbiome diversity and disease severity in Sjögren syndrome. Sci Rep 2016; 6:23561Published April 18, 2016. doi:10.1038/srep23561.
11. Ejtahed HS, Tabatabaei-Malazy O, Soroush AR, et al. Worldwide trends in scientific publications on association of gut microbiota with obesity. Iran J Basic Med Sci 2019; 22:65–71.
12. Kugadas A, Wright Q, Geddes-McAlister J, et al. Role of microbiota in strengthening ocular mucosal barrier function through secretory IgA. Invest Ophthalmol Vis Sci 2017; 58:4593–4600.
13. Ueta M, Kinoshita S. Innate immunity of the ocular surface. Brain Res Bull 2010; 81:219–228.
14. Murray PR, Rosenthal KS, Kobayashi GS, Pfaller M. Microbiologia Médica. 4th ed.Rio de Janeiro: Guanabara Koogan; 2004.
15. Amann RI, Ludwig W, Schleifer KH. Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol Rev 1995; 59:143–169.
16. Hugenholtz P, Goebel BM, Pace NR. Impact of culture-independent studies on the emerging phylogenetic view of bacterial diversity. J Bacteriol 1998; 180:4765–4774.
17. Ozkan J, Willcox MD. The ocular microbiome: molecular characterisation of a unique and low microbial environment. Curr Eye Res 2019; 44:685–694.
18. Delbeke H, Younas S, Casteels I, et al. Current knowledge on the human eye microbiome: a systematic review of available amplicon and metagenomic sequencing data. Acta Ophthalmol 2020; doi:10.1111/aos.14508.
19. Keilty RA. The bacterial flora of the normal conjunctiva with comparative nasal culture study. Am J Ophthalmol 1930; 13:876–879.
20. Grzybowski A, Brona P, Kim SJ. Microbial flora and resistance in ophthalmology: a review. Graefes Arch Clin Exp Ophthalmol 2017; 255:851–862.
21. Hofling-Lima AL, Farah ME, Montenegro L, et al. Changes in conjunctival and lid flora after topical use of lomefloxacin and tobramycin in cataract and refractive surgery. Arq Bras Oftalmol 2002; 65:21–29.
22. Dong Q, Brulc JM, Iovieno A, et al. Diversity of bacteria at healthy human conjunctiva. Invest Ophthalmol Vis Sci 2011; 52:5408–5413.
23. Moeller CT, Branco BC, Yu MC, et al. Evaluation of normal ocular bacterial flora with two different culture media. Can J Ophthalmol 2005; 40:448–453.
24. Kittipibul T, Puangsricharern V, Chatsuwan T. Comparison of the ocular microbiome between chronic Stevens-Johnson syndrome patients and healthy subjects. Sci Rep 2020; 10:4353Published March 9, 2020. doi:10.1038/s41598-020-60794-w.
25. Thiel HJ, Schumacher U. Uber die Standortflora der menschlichen Bindehaut: Untersuchungen von 135 Personen unterschiedlichen Alters [Normal flora of the human conjunctiva: examination of 135 persons of various ages]. Klin Monbl Augenheilkd 1994; 205:348–357.
26. Willcox MD. Characterization of the normal microbiota of the ocular surface. Exp Eye Res 2013; 117:99–105.
27. Kugadas A, Gadjeva M. Impact of microbiome on ocular health. Ocul Surf 2016; 14:342–349.
28. Lu LJ, Liu J. Human microbiota and ophthalmic disease. Yale J Biol Med 2016; 89:325–330.
29. Boost M, Cho P, Wang Z. Disturbing the balance: effect of contact lens use on the ocular proteome and microbiome. Clin Exp Optom 2017; 100:459–472.
30. Borroni D, Romano V, Kaye SB, et al. Metagenomics in ophthalmology: current findings and future prospectives. BMJ Open Ophthalmol 2019; 4:e000248Published June 4, 2019. doi:10.1136/bmjophth-2018-000248.
31. St Leger AJ, Caspi RR. Visions of eye commensals: the known and the unknown about how the microbiome affects eye disease. Bioessays 2018; 40:e1800046doi:10.1002/bies.201800046.
32. Wen X, Miao L, Deng Y, et al. The influence of age and sex on ocular surface microbiota in healthy adults. Invest Ophthalmol Vis Sci 2017; 58:6030–6037.
33. Baim AD, Movahedan A, Farooq AV, et al. The microbiome and ophthalmic disease. Exp Biol Med (Maywood) 2019; 244:419–429.
34. Gallon P, Parekh M, Ferrari S, et al. Metagenomics in ophthalmology: hypothesis or real prospective? Biotechnol Rep (Amst) 2019; 23:e00355Published June 26, 2019. doi:10.1016/j.btre.2019.e00355.
35. Watane A, Cavuoto KM, Banerjee S, et al. The microbiome and ocular surface disease. Curr Ophthalmol Rep 2019; 7:196–203.
36. Cavuoto KM, Stradiotto AC, Galor A. Role of the ocular surface microbiome in allergic disease. Curr Opin Allergy Clin Immunol 2019; 19:482–487.
37. Lee PW, Jun AK, Cho BC. A study of microbial flora of conjunctival sac in newborns. Korean J Ophthalmol 1989; 3:38–41.
38. Eder M, Fariña N, Sanabria RR, et al. Normal ocular flora in newborns delivered in two hospital centers in Argentina and Paraguay. Graefes Arch Clin Exp Ophthalmol 2005; 243:1098–1107.
39. Ozkan J, Nielsen S, Diez-Vives C, et al. Temporal stability and composition of the ocular surface microbiome. Sci Rep 2017; 7:9880Published August 29, 2017. doi:10.1038/s41598-017-10494-9.
40. Zhou Y, Holland MJ, Makalo P, et al. The conjunctival microbiome in health and trachomatous disease: a case control study. Genome Med 2014; 6:99Published November 15, 2014. doi:10.1186/s13073-014-0099-x.
41. Versura P, Giannaccare G, Campos EC. Sex-steroid imbalance in females and dry eye. Curr Eye Res 2015; 40:162–175.
42. Cavuoto KM, Banerjee S, Miller D, et al. Composition and comparison of the ocular surface microbiome in infants and older children. Transl Vis Sci Technol 2018; 7:16Published November 30, 2018. doi:10.1167/tvst.7.6.16.
43. Ozkan J, Willcox M, Wemheuer B, et al. Biogeography of the human ocular microbiota. Ocul Surf 2019; 17:111–118.
44. Ozkan J, Coroneo M, Willcox M, et al. Identification and visualization of a distinct microbiome in ocular surface conjunctival tissue. Invest Ophthalmol Vis Sci 2018; 59:4268–4276.
45. Shin H, Price K, Albert L, et al. Changes in the eye microbiota associated with contact lens wearing. mBio 2016; 7:e00198Published March 22, 2016. doi:10.1128/mBio.00198-16.
46. Retuerto MA, Szczotka-Flynn L, Mukherjee PK, et al. Diversity of ocular surface bacterial microbiome adherent to worn contact lenses and bacterial communities associated with care solution use. Eye Contact Lens 2019; 45:331–339.
47. Sankaridurg PR, Markoulli M, de la Jara PL, et al. Lid and conjunctival micro biota during contact lens wear in children. Optom Vis Sci 2009; 86:312–317.
48. Sankaridurg PR, Willcox MD, Sharma S, et al. Haemophilus influenzae adherent to contact lenses associated with production of acute ocular inflammation. J Clin Microbiol 1996; 34:2426–2431.
49. Honda R, Toshida H, Suto C, et al. Effect of long-term treatment with eyedrops for glaucoma on conjunctival bacterial flora. Infect Drug Resist 2011; 4:191–196.
50. Suto C, Morinaga M, Yagi T, et al. Conjunctival sac bacterial flora isolated prior to cataract surgery. Infect Drug Resist 2012; 5:37–41.
51. Adam M, Balci M, Bayhan HA, et al. Conjunctival flora in diabetic and nondiabetic individuals. Turk J Ophthalmol 2015; 45:193–196.
52. Nahar N, Anwar S, Miah MRA. Conjunctival bacterial flora in diabetic patients. Ibrahim Med Coll J 2014; 7:5–8.
53. Ham B, Hwang HB, Jung SH, et al. Distribution and diversity of ocular microbial communities in diabetic patients compared with healthy subjects. Curr Eye Res 2018; 43:314–324.
54. Li S, Yi G, Peng H, et al. How ocular surface microbiota debuts in type 2 diabetes mellitus. Front Cell Infect Microbiol 2019; 9:202Published June 17, 2019. doi:10.3389/fcimb.2019.00202.
55. Gunduz G, Gunduz A, Polat N, et al. The effect of chronic alcoholism on the conjunctival flora. Curr Eye Res 2016; 41:734–739.
56. Lee SH, Oh DH, Jung JY, et al. Comparative ocular microbial communities in humans with and without blepharitis. Invest Ophthalmol Vis Sci 2012; 53:5585–5593.
57. Watters GA, Turnbull PR, Swift S, et al. Ocular surface microbiome in meibomian gland dysfunction. Clin Exp Ophthalmol 2017; 45:105–111.
58. Albietz JM, Lenton LM. Effect of antibacterial honey on the ocular flora in tear deficiency and meibomian gland disease. Cornea 2006; 25:1012–1019.
59. Graham JE, Moore JE, Jiru X, et al. Ocular pathogen or commensal: a PCR-based study of surface bacterial flora in normal and dry eyes. Invest Ophthalmol Vis Sci 2007; 48:5616–5623.
60. Zaheer M, Wang C, Bian F, et al. Protective role of commensal bacteria in Sjögren syndrome. J Autoimmun 2018; 93:45–56.
61. Frizon L, Araújo MC, Andrade L, et al. Evaluation of conjunctival bacterial flora in patients with Stevens-Johnson syndrome. Clinics (Sao Paulo) 2014; 69:168–172.
62. Venugopal R, Satpathy G, Sangwan S, et al. Conjunctival microbial flora in ocular Stevens-Johnson syndrome sequelae patients at a tertiary eye care center. Cornea 2016; 35:1117–1121.
63. Gunasekaran S, Dhiman R, Vanathi M, et al. Ocular surface microbial flora in patients with chronic limbal stem cell deficiency undergoing cultivated oral mucosal epithelial transplantation. Middle East Afr J Ophthalmol 2019; 26:23–26.
64. Shimizu E, Ogawa Y, Saijo Y, et al. Commensal microflora in human conjunctiva; characteristics of microflora in the patients with chronic ocular graft-versus-host disease. Ocul Surf 2019; 17:265–271.
65. Yau JW, Hou J, Tsui SKW, et al. Characterization of ocular and nasopharyngeal microbiome in allergic rhinoconjunctivitis. Pediatr Allergy Immunol 2019; 30:624–631.
66. Gündüz A, Gündüz A, Cumurcu T, Seyrek A. Conjunctival flora in Behçet patients. Can J Ophthalmol 2008; 43:476–479.

16S rRNA gene; disease; health; human; microbiology; microbiome; ocular surface

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