Abstract Background The ocular surface microbiome is increasingly recognized for its role in eye health, but the complexity of its composition complicates personalized characterization. This study aims to define the ocular surface microbiome profile and identify distinct microbial community clusters, or Ocular Types, in a population of children and adolescents. Methods In this population-based, cross-sectional study, conjunctival swabs from children and adolescents were processed with 16S ribosomal RNA gene amplicon sequencing. Microbial clusters were determined using a partitioning around medoids clustering approach, validated through internal cross-comparison and external datasets. Functional profiles of the clusters were predicted from the sequencing data. Results Here we show that in 1246 samples from 1006 individuals aged 3 to 18 years, the predominant bacterial phyla are Proteobacteria (34.1%), Firmicutes (37.4%), and Actinobacteria (25.2%), with Staphylococcus , Corynebacterium , and Streptococcus as core microbiota. Five distinct Ocular Types are identified, characterized by the dominance of Staphylococcus , Corynebacterium , Streptococcus , uncultured Neisseriaceae , or Escherichia-Shigella . These Ocular Types demonstrate associations with host factors including age, ethnicity and ocular parameter, but not with sex. Functional prediction reveals considerable overlap in the metabolic pathways among the Ocular Types. Conclusions This study characterizes five distinct ocular surface microbiome types in pediatric population and establishes their association with host factors. These findings provide a structured framework for investigating microbial community dynamics and their potential implications for ocular health.
Ling et al. (Mon,) studied this question.