A Metagenomics – Based Diagnostic Approach for Central Nervous System Infections in Hospital Acute Care Setting

The etiology of central nervous system (CNS) infections such as meningitis and encephalitis remains unknown in a large proportion of cases partly because the diversity of pathogens that may cause CNS infections greatly outnumber available test methods. Here we present a metagenomic next generation sequencing (mNGS) based approach for broad-range detection of pathogens associated with CNS infections, which is suitable for application in the acute care hospital setting. Using an Illumina MiSeq benchtop sequencer and the IDseq pipeline for identifying pathogens in metagenomic sequence data, we show that the analytical sensitivity of mNGS to detect pathogens is comparable to that of PCR in simulated cerebrospinal fluid (CSF) specimens. We then applied this method for pathogen detection in 74 CSF specimens from patients with suspected CNS infections that were previously tested by culture and/or PCR. Diagnostic accuracy, sensitivity and specificity of mNGS approach with reference to conventional methods were all 95%. Furthermore, confirmatory testing on specimens that gave discrepant results were mostly in favor of the mNGS assay. The clinical application of mNGS holds promise to benefit patients with CNS infections of unknown etiology.