Ocular microbiome changes in dry eye disease and meibomian gland dysfunction

Jerome Ozkan; Marwan E Majzoub; Minas Coroneo; Torsten Thomas; Mark Willcox

doi:10.1016/j.exer.2023.109615

Ocular microbiome changes in dry eye disease and meibomian gland dysfunction

Exp Eye Res. 2023 Oct:235:109615. doi: 10.1016/j.exer.2023.109615. Epub 2023 Aug 15.

Authors

Jerome Ozkan¹, Marwan E Majzoub², Minas Coroneo³, Torsten Thomas⁴, Mark Willcox⁵

Affiliations

¹ School of Optometry and Vision Science, University of New South Wales, Sydney, Australia; Centre for Marine Science and Innovation and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, Australia. Electronic address: j.ozkan@unsw.edu.au.
² Host-Microbiome Interactions Group, School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia.
³ Department of Ophthalmology, Faculty of Medicine, University of New South Wales, Sydney, Australia.
⁴ Centre for Marine Science and Innovation and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, Australia.
⁵ School of Optometry and Vision Science, University of New South Wales, Sydney, Australia.

PMID: 37586456
DOI: 10.1016/j.exer.2023.109615

Abstract

The most common and chronic ocular problem of aging is dry eye disease (DED) and the associated condition of meibomian gland dysfunction (MGD). The resident ocular surface bacteria may have a role in maintaining homeostasis and perturbation may contribute to disease development. The aim of this study was to compare the microbiomes of the conjunctiva and eyelid margin in humans with mild and moderate DED and controls using 16 S rRNA gene sequencing. The conjunctiva and lid margin of three cohorts (N = 60; MGD, MGD with lacrimal dysfunction [MGD + LD] and controls) were swabbed bilaterally three times over three months. Microbial communities were analysed by extracting DNA and sequencing the V3-V4 region of the 16 S ribosomal RNA gene using the Illumina MiSeq platform. Sequences were quality filtered, clustered into amplicon sequence variants (ASVs) using UNOISE algorithm and taxonomically classified using a Bayesian Last Common Ancestor (BCLA) algorithm against the GTDB 2207 database. The overall microbial communities of the MGD, MGD + LD and control groups were significantly different from each other (P = 0.001). The MGD and MGD + LD dry eye groups showed greater variability between individuals compared to the control (PERMDISP, P < 0.01). There was decreased richness and diversity in females compared to males for the conjunctiva (P < 0.04) and eyelid margin (P < 0.018). The conjunctiva in the MGD + LD group had more abundant Pseudomonas azotoformans, P. oleovorans and Caballeronia zhejiangensis compared to MGD and control (P < 0.05), while the MGD group had more abundant Corynebacterium macginleyi and C. kroppenstedtii compared to control (P < 0.05). The lid margin in MGD was more abundant in C. macginleyi, C. accolens, and C. simulans compared to the MGD + LD and control (P < 0.05). There were differences in the overall microbial community composition and certain taxa, including increased levels of lipophilic bacteria, on the conjunctiva and eyelid margin in mild to moderate DED/MGD compared to controls. DED/MGD was also associated with a reduced bacterial richness and diversity in females.

Keywords: 16S rRNA gene sequencing; Dry eye disease; Meibomian gland dysfunction; Microbiome; Ocular microbiology.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Bacteria / genetics
Bayes Theorem
Dry Eye Syndromes*
Eyelid Diseases*
Female
Humans
Male
Meibomian Gland Dysfunction*
Meibomian Glands
Microbiota*
Tears