Illuminating Uveitis: Metagenomic Deep Sequencing Identifies Common and Rare Pathogens

Abstract

BackgroundOcular infections remain a major cause of blindness and morbidity worldwide. While prognosis is dependent on the timing and accuracy of diagnosis, the etiology remains elusive in ~ 50% of presumed infectious uveitis cases.1,2 We aimed to determine if unbiased metagenomic deep sequencing (MDS) can accurately detect pathogens in intraocular fluid samples of patients with uveitis.\n\nMethodsThis is a proof-of-concept study, in which intraocular fluid samples were obtained from 5 subjects with known diagnoses, and one subject with bilateral chronic uveitis without a known etiology. Samples were subjected to MDS, and results were compared with conventional diagnostic tests. Pathogens were identified using a rapid computational pipeline to analyze the non-host sequences obtained from MDS.\n\nFindingsUnbiased MDS of intraocular fluid produced results concordant with known diagnoses in subjects with (n=4) and without (n=1) uveitis. Rubella virus (RV) was identified in one case of chronic bilateral idiopathic uveitis. The subjects strain was most closely related to a German RV strain isolated in 1992, one year before he developed a fever and rash while living in Germany.\n\nInterpretationMDS can identify fungi, parasites, and DNA and RNA viruses in minute volumes of intraocular fluid samples. The identification of chronic intraocular RV infection highlights the eyes role as a long-term pathogen reservoir, which has implications for virus eradication and emerging global epidemics.