Abstract
PURPOSE: The human ocular surface microbiome (OSM) plays a vital role in ocular health, infection prevention, and immune modulation. However, use of sequencing technology for researching the OSM is challenged by low sample biomass, high sample variability, and methodological inconsistencies. This review systematically evaluates existing literature on OSM research, identifying methodological challenges and proposing standardization strategies to enhance data quality, comparability, and clinical relevance. METHODS: A comprehensive analysis of peer-reviewed studies was conducted to assess methodologies used in sequencing-based OSM research, with focus on considerations in scope: sample size, selection, choice of eye, time frame, recruitment and enrollment criteria; sample collection and handling: sampling environment, topical anesthesia, sample collection tools and ocular region; sample preservation: temperature and use of buffers; and sample analysis: DNA extraction, quantification, and sequencing approach. Advantages and limitations of different approaches were identified, and best practices for standardization were explored. RESULTS: This review identified substantial variations in sample collection and processing methodologies, many of which are known to impact OSM composition. However, the influence of certain approaches remains unclear. Additionally, large reporting gaps were observed, as many studies failed to describe critical methodological elements, including specific sample handling procedures and sequencing parameters. CONCLUSIONS: While sequencing technologies offer valuable insights, our findings highlight the need for further investigation of different methodological approaches to determine best practices and establish standardized methodological protocols, as well as the need for standardized reporting protocols in OSM research. These standards are essential for enhancing data reliability and translating findings into clinical applications.