Communications medicine · 2026
Profiling of ocular surface microbiome and its ocular types in children and adolescents.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Ling Xiangtian, Zhang Yuzhou, Bui Christine H T, Chan Hei-Nga, Peng Yu, Zhang Xiu Juan, Yim Charlene C, Yau Jennifer Wing-Ki, Kam Ka Wai, Ip Patrick, Young Alvin L, Hon Kam Lun, Tham Clement C, Pang Chi Pui, Chen Li Jia, Yam Jason C
Аннотация
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.
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.