Effect of clinical parameters on the ocular surface microbiome in children and adults

Cavuoto, Kara M.; Méndez, Roberto; Miller, Darlene; Banerjee, Santanu

doi:10.2147/opth.s166547

Cited by 44 publications

(55 citation statements)

References 23 publications

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“…However, prior work has shown no significant differences in the OSM between gender, prior surgery, or use of topical medication. 42 Third, patients presenting for eye care may not be reflective of the general population. Finally, the cross-sectional nature of the study does not allow for following the evolution of an individual microbiome over time.…”

Section: Discussionmentioning

confidence: 99%

Composition and Comparison of the Ocular Surface Microbiome in Infants and Older Children

Cavuoto

Banerjee

Miller

et al. 2018

Trans. Vis. Sci. Tech.

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PurposeUnlike other microbiomes of the body, the composition of the ocular surface microbiome (OSM) in children has yet to be thoroughly explored. Our goal was to evaluate the OSM in young infants and compare its composition to older children using both culture dependent and independent methodologies to assess for differences with age.MethodsProspective, observational, cross-sectional study of children <18 years of age at a university-based institution. The mucosal surfaces of both eyes, nose and throat were swabbed with a forensic-quality swab. Half of the swab was plated for culture and the other half underwent 16S sequencing. Culture results and microbiome diversity were analyzed.ResultsFifty patients (mean age 37 months, range 1–168 months) were enrolled. Forty-seven eyes of 30 patients had positive cultures; four eyes grew >1 species. Culture positive patients were older (43 vs. 29 months, P = 0.19). Additionally, older children had greater diversity than children under 6 months of age by 16S sequencing (P = 0.05). Staphylococcus species were predominant by culture (35/52 isolates) and by 16S sequencing. The OSM was fairly similar to the nose microbiome, whereas the throat microbiome differed significantly and had a higher abundance of Streptococcaceae (P = 0.001).ConclusionsThe OSM is predominantly composed of Staphylococcus species in children, as demonstrated by both culture dependent and culture independent methods. Older children were more likely to have growth on culture and have more a complex bacterial milieu with 16S sequencing.Translational Relevance16S sequencing provides more robust information regarding the composition of the microbiomes than culture dependent methods.

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Section: Discussionmentioning

confidence: 99%

Composition and Comparison of the Ocular Surface Microbiome in Infants and Older Children

Cavuoto

Banerjee

Miller

et al. 2018

Trans. Vis. Sci. Tech.

Self Cite

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“…are the most representative [ 28 , 29 , 30 , 31 ]. Zhou and Cavuoto described that the conjunctival microbiota of subjects under the age of 10 showed a richness (absolute number of taxa present) and a Shannon diversity index (relative number and abundance of each taxon) significantly higher compared to that of older subjects [ 32 ]. In contrast, Wen et al, analyzed the composition of the ocular microbiota in subjects within an age group between 28 and 84 years, founding a greater diversity of Shannon index values in the older subjects than in the young ones.…”

Section: Effects Of Age Sex Ethnicity and Geographic Location Omentioning

confidence: 99%

Current Evidence on the Ocular Surface Microbiota and Related Diseases

et al. 2020

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The ocular surface microbiota refers to the resident non-pathogenic microorganisms that colonize conjunctiva and cornea. Several studies have shown that ocular surface epithelial cells can respond selectively to specific components of ocular pathogenic bacteria by producing pro-inflammatory cytokines and, in contrast, they do not respond to non-pathogenic bacteria, thus supporting the colonization by a real microbiota. However, the analysis of the ocular microbiome composition is essential for understanding the pathophysiology of various ophthalmic diseases. In this scenario, the first studies, which used microbiological culture techniques, reported a less diverse profile of the ocular microbiota compared with that recently discovered using new molecular-based methods. Indeed, until a few years ago, the microbiota of the ocular surface appeared to be dominated by Gram-positive and a few Gram-negative bacteria, as well as some fungal strains. In contrast, genomics has nowadays detected a remarkable diversity in the ocular surface microorganisms. Furthermore, recent studies suggest that the microbiota of other areas of the body, such as the gut and oral microbiota, are involved in the pathophysiology of several ophthalmic diseases. The aim of the present study is to highlight the current evidence on the ocular surface microbiota to better understand it and to investigate its potential role in the development of ophthalmic diseases.

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“…Possible factors shaping microbiome included gender, age, use of medications, and disease comorbidity. 7,[34][35][36] Little studies were conducted to explore these factors on conjunctival microbiome particularly in the pediatric populations. After adjusting for these factors, the result did not change dramatically ( Figure S7).…”

Section: Ta B L E 2 Analysis Of Beta Diversitymentioning

confidence: 99%

Characterization of ocular and nasopharyngeal microbiome in allergic rhinoconjunctivitis

Yau

Hou

Tsui

et al. 2019

Pediatric Allergy Immunology

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Background Allergic rhinoconjunctivitis (ARC) is a prevalent allergic condition in the pediatric population. Microbial dysbiosis has increasingly been recognized to influence on host immunity and allergic diseases. However, the microbial profile of ARC has not been characterized. This cross‐sectional study aims to evaluate the changes in nasal and ocular surface microbiome of children with ARC. Methods Ocular and nasopharyngeal swabs were collected from controls and pediatric ARC cases for 16S rRNA amplicon sequencing. The bacterial community profile was analyzed. The correlation of the microbial diversity with the ARC‐related clinical scores was studied. Results A total of 23 patients with ARC and 17 healthy controls were recruited;30 were ocular samples (15 controls vs 15 ARC), while 40 were nasal samples (17controls vs 23 ARC) The alpha diversity of nasopharyngeal microbiome was significantly higher in ARC patients than healthy controls (P < 0.01), but not for ocular microbiome. The clinical scores in all subjects were negatively correlated with the Shannon diversity for ocular (P = 0.014) and positively correlated with nasopharyngeal (P = 0.010) microbiome. While the ocular microbiome remained significantly distinct from nasopharyngeal microbiome in terms of both alpha and beta diversity in both healthy subjects and ARC patients, significant differences of relative abundance of certain phyla (Bacteroidetes, Cyanobacteria, and Deinococcus‐Thermus) and genera (Dolosigranulum and Moraxella) between nasal and ocular surfaces were only detected in healthy controls, but not in the ARC subjects, suggesting the microbial composition at both body sites becoming more similar at disease state. Conclusion This study reported (a) a higher alpha diversity in ocular than nasopharyngeal microbiome in both ARC patients and controls, and (b) nasopharyngeal microbiome became more diverse in ARC patients than in controls. Our results suggested an interaction of the microbiome between ocular and nasal compartments in patients with ARC.

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Effect of clinical parameters on the ocular surface microbiome in children and adults

Cited by 44 publications

References 23 publications

Composition and Comparison of the Ocular Surface Microbiome in Infants and Older Children

Composition and Comparison of the Ocular Surface Microbiome in Infants and Older Children

Current Evidence on the Ocular Surface Microbiota and Related Diseases

Characterization of ocular and nasopharyngeal microbiome in allergic rhinoconjunctivitis

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