ABSTRACT
Purpose To compare the performance of unbiased high-throughput sequencing with pathogen directed PCR using DNA isolated from archived ocular fluid, approaches that are compatible with the current sample handling practice of ophthalmologists.
Design Retrospective molecular study of banked vitreous samples.
Methods We evaluated a metagenomic DNA sequencing-based approach (DNA-seq) using archived positive (n = 31) and negative (n=36) vitreous specimens as determined by reference pathogen-specific PCR assays (herpes simplex virus 1 and 2, cytomegalovirus, varicella-zoster virus, and Toxoplasma gondii). Pathogens were identified using a rapid computational pipeline to analyze the non-host sequences obtained from DNA-seq. Clinical samples were de-identified and laboratory personnel handling the samples and interpreting the data were masked.
Results Metagenomic DNA sequencing detected 87% of positive reference samples. In the presumed negative reference samples, DNA-seq detected an additional 6 different pathogens in 8 samples (22% of negative samples) that were either not detected or not targeted with pathogen-specific PCR assays. Infectious agents identified only with DNA-seq were Candida dubliniensis, Klebsiella pneumoniae, human herpesvirus 6 (HHV-6), and human T-cell leukemia virus type 1 (HTLV-1). Discordant samples were independently verified in CLIA-certified laboratories. CMV sequences were compared against the antiviral mutation database and 3 of the samples were found to have mutations conferring ganciclovir resistance.
Conclusions Metagenomic DNA sequencing was highly concordant with pathogen-directed PCRs. The unbiased nature of metagenomics DNA sequencing allowed an expanded scope of pathogen detection, including bacteria, fungal species, and viruses, resolving 22% of cases that had previously escaped detection by routine pathogen-specific PCRs. The detection of drug resistance mutations highlights the potential for unbiased sequencing to provide clinically actionable information beyond pathogen species detection.
