Background: In patients with central nervous system (CNS) infections identification of the causative pathogen is important for treatment. Metagenomic next-generation sequencing techniques are increasingly being applied to identify causes of CNS infections, as they can detect any pathogen nucleic acid sequences present. Viromic techniques that enrich samples for virus particles prior to sequencing may simultaneously enrich ribosomes from bacterial pathogens, which are similar in size to small viruses.
Methods: We studied the performance of a viromic library preparation technique (VIDISCA) combined with low-depth IonTorrent sequencing (median ~ 25,000 reads per sample) for detection of ribosomal RNA from common pathogens, analyzing 89 cerebrospinal fluid samples from patients with culture proven bacterial meningitis.
Results: Sensitivity and specificity to Streptococcus pneumoniae (n = 24) before and after optimizing threshold parameters were 79% and 52%, then 88% and 90%. Corresponding values for Neisseria meningitidis (n = 22) were 73% and 93%, then 67% and 100%, Listeria monocytogenes (n = 24) 21% and 100%, then 27% and 100%, and Haemophilus influenzae (n = 18) 56% and 100%, then 71% and 100%. A higher total sequencing depth, no antibiotic treatment prior to lumbar puncture, increased disease severity, and higher c-reactive protein levels were associated with pathogen detection.
Conclusion: We provide proof of principle that a viromic approach can be used to correctly identify bacterial ribosomal RNA in patients with bacterial meningitis. Further work should focus on increasing assay sensitivity, especially for problematic species (e.g. L. monocytogenes), as well as profiling additional pathogens. The technique is most suited to research settings and examination of idiopathic cases, rather than an acute clinical setting.
Keywords: Bacterial meningitis; Cerebrospinal fluid; Metagenomics; Pathogen detection; Viromics.
© 2022. The Author(s).