Multi-cohort analysis identifying core ocular surface microbiome and bacterial alterations in eye diseases.

Abstract

Purpose: Inconsistency exists among reported studies on the composition of human ocular surface microbiome (OSM). The roles of OSM in ocular diseases remain uncertain. In this study, we aimed to determine the composition of OSM and to evaluate its potential roles and functions from multiple cohorts.

Methods: Raw 16 s sequencing data were obtainable from publicly available repositories, sourced from 17 published studies. Employing a standardized method, we processed the data and conducted a cross-cohort analysis. Through bioinformatics pipelines QIIME2 and PICRUSt2, we processed a total of 1875 ocular surface samples. Core microbiome analyses, genera comparisons, and MetaCyc pathway analyses were performed within each cohort independently. The results were then combined to identify shared patterns across different datasets.

Results: The core OSM comprised seven genera: Corynebacterium, Staphylococcus, Acinetobacter, Streptococcus, Pseudomonas, Cutibacterium and Bacillus. Corynebacterium and Staphylococcus are the most abundant genera on ocular surface. Most ocular diseases showed OSM alterations and eight genera demonstrated a non-specific, shared response among two or more ocular diseases. Moreover, changes in various metabolic pathways were predicted following OSM alteration, indicating potential roles of OSM in biological processes.

Conclusion: We refined the core OSM candidates combining multiple cohorts. The common pattern shared by different cohorts is worth further investigation. Changes in metabolic pathways based on bioinformatic analysis indicated a role of OSM on ocular diseases. Our results help extend the knowledge and encourage further investigations on the associations between OSM and ocular diseases.