Case Series: Unbiased Deep Sequencing Analysis of Acute Infectious Conjunctivitis in an Ambulatory Eye Center in Berkeley, California

Abstract

SIGNIFICANCE Acute infectious conjunctivitis poses significant challenges to eye care providers. It can be highly transmissible, and because etiology is often presumed, correct treatment and management can be difficult. This study uses unbiased deep sequencing to identify causative pathogens of infectious conjunctivitis, potentially allowing for improved approaches to diagnosis and management. PURPOSES This study aimed to identify associated pathogens of acute infectious conjunctivitis in a single ambulatory eye care center. CASE REPORTS This study included patients who presented to the University of California Berkeley eye center with signs and symptoms suggestive of infectious conjunctivitis. From December 2021 to July 2021, samples were collected from seven subjects (ages ranging from 18 to 38). Deep sequencing identified associated pathogens in five of seven samples, including human adenovirus D, Haemophilus influenzae, Chlamydia trachomatis, and human coronavirus 229E. CONCLUSIONS Unbiased deep sequencing identified some unexpected pathogens in subjects with acute infectious conjunctivitis. Human adenovirus D was recovered from only one patient in this series. Although all samples were obtained during the COVID-19 pandemic, only one case of human coronavirus 229E and no SARS-CoV-2 were identified.