The authors were interested in the use of metagenomic sequencing (mS) for the diagnosis of infectious causes of meningitis and encephalitis from cerebrospinal fluid (CSF). They created a customised bioinformatics pipeline, SURPI+, to analyse mS data, generate an automated summary of detected pathogens and provide a graphical user interface for evaluating and interpreting results. The authors also determined quality metrics, threshold values, and identified limits of detection of 0.2-313 genomic copies or colony forming units/mL for each organism. They found that gross haemolysis and excessive host nucleic acid reduced the sensitivity of the assay and the use of spiked phages could indicate when this had occurred. The authors assessed diagnostic test accuracy by blinded mS testing of 95 patient samples, which found that sensitivity was 73% and specificity 99%, compared with original clinical test results, and had 81% positive agreement and 99% negative agreement following discrepancy analysis. Further mS challenge testing of 20 positive CSF samples prospectively collected from a cohort of paediatric patients that had been hospitalised with meningitis, encephalitis and/or myelitis, demonstrated 92% sensitivity and 96% specificity relative to conventional microbiology. Therefore there is potential for a laboratory-validated mS assay for pan-pathogen detection from neurological infections in CSF.
Read more here