Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid

TLDR

Metagenomic next‑generation sequencing (mNGS) has proven effective in proof‑of‑concept studies for pan‑pathogen detection in patients with acute unknown illness, yet it remains largely confined to research settings. We developed and validated a clinical mNGS assay to diagnose infectious meningitis and encephalitis from cerebrospinal fluid in a licensed microbiology laboratory. The assay employs a customized SURPI+ bioinformatics pipeline, quality metrics, and defined thresholds with limits of detection between 0.2 and 313 genomic copies or colony‑forming units per milliliter. Diagnostic accuracy testing revealed 73 % sensitivity and 99 % specificity versus initial clinical results, 81 % positive and 99 % negative percent agreement after discrepancy analysis, and 92 % sensitivity and 96 % specificity in prospective pediatric CSF samples, confirming robust analytic performance for pan‑pathogen detection in clinical diagnosis of neurological infections.

Abstract

Metagenomic next-generation sequencing (mNGS) for pan-pathogen detection has been successfully tested in proof-of-concept case studies in patients with acute illness of unknown etiology but to date has been largely confined to research settings. Here, we developed and validated a clinical mNGS assay for diagnosis of infectious causes of meningitis and encephalitis from cerebrospinal fluid (CSF) in a licensed microbiology laboratory. A customized bioinformatics pipeline, SURPI+, was developed to rapidly analyze mNGS data, generate an automated summary of detected pathogens, and provide a graphical user interface for evaluating and interpreting results. We established quality metrics, threshold values, and limits of detection of 0.2–313 genomic copies or colony forming units per milliliter for each representative organism type. Gross hemolysis and excess host nucleic acid reduced assay sensitivity; however, spiked phages used as internal controls were reliable indicators of sensitivity loss. Diagnostic test accuracy was evaluated by blinded mNGS testing of 95 patient samples, revealing 73% sensitivity and 99% specificity compared to original clinical test results, and 81% positive percent agreement and 99% negative percent agreement after discrepancy analysis. Subsequent mNGS challenge testing of 20 positive CSF samples prospectively collected from a cohort of pediatric patients hospitalized with meningitis, encephalitis, and/or myelitis showed 92% sensitivity and 96% specificity relative to conventional microbiological testing of CSF in identifying the causative pathogen. These results demonstrate the analytic performance of a laboratory-validated mNGS assay for pan-pathogen detection, to be used clinically for diagnosis of neurological infections from CSF.