Microbial Dysbiosis On The Ocular Surface: Investigating The Role Of The Microbiome In Limbal Stem Cell Deficiency
Published 2025 - 43rd Congress of the ESCRS
Reference: FP27.03 | Type: Free paper | DOI: 10.82333/5etd-hp95
Authors: Alice Grise-Dulac* 1 , Maria RIZK 1 , Oceanne Haelewyn 1 , Damien Gatinel 1
1Rothschild,Paris,France
Purpose
Ocular microbial dysbiosis has been linked to several ocular surface diseases, while a balanced microbiome is pivotal to maintaining ocular surface health. Dysfunctional interactions between microbial communities and host epithelial cells may impede the regenerative capacity of the limbal stem cell niche and impair corneal epithelial repair mechanisms in limbal stem cell deficiency (LSCD). In the current study, we evaluated ocular microbiomes in patients suffering from LSCD and healthy individuals.
Setting
Outpatient department and Cornea Clinic of Dr Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India
Methods
The microbiome composition of 54 individuals, obtained from swabbing the inferior conjunctival fornix, was analysed using Whole Genome Metagenome Sequencing on the Nanopore platform. Taxonomy analysis of the reads was performed against an indexed NT (NCBI non-redundant nucleotide) database followed by detailed bioinformatics analysis.
Results
34 patients with LSCD and 20 controls, age & sex matched, were included. Higher concentration of microbial DNA was isolated in LSCD than controls (119 vs 25 ng/ml; P<0.001). Reduced abundance of beneficial commensal bacteria (Propionibacterium, Cutibacterium) and overgrowth of pathogenic taxa (Pseudomonas, Pneumococcus, Corynebacterium) was noted. Distinct microbial species like Rothia mucilaginosa, Ralstonia solonacearum, Dracunculus medinensis were isolated for the first time from the ocular surface of patients with LSCD.
Conclusions
These findings indicate that these microorganisms may be promising biomarkers for discriminating LSCD from healthy individuals. Variations in microbial profiles could serve as predictive biomarkers for identifying patients at higher risk of disease progression or treatment resistance, guiding personalized therapeutic interventions and prognostic assessments.