BACKGROUND Metagenomic next-generation sequencing (NGS) of cerebrospinal fluid (CSF) has the potential to identify a broad range of pathogens in a single test. METHODS In a 1-year, multicenter, prospective study, we investigated the usefulness of metagenomic NGS of CSF for the diagnosis of infectious meningitis and encephalitis in hospitalized patients. All positive tests for pathogens on metagenomic NGS were confirmed by orthogonal laboratory testing. Physician feedback was elicited by teleconferences with a clinical microbial sequencing board and by surveys. Clinical effect was evaluated by retrospective chart review. RESULTS We enrolled 204 pediatric and adult patients at eight hospitals. Patients were severely ill: 48.5% had been admitted to the intensive care unit, and the 30-day mortality among all study patients was 11.3%. A total of 58 infections of the nervous system were diagnosed in 57 patients (27.9%). Among these 58 infections, metagenomic NGS identified 13 (22%) that were not identified by clinical testing at the source hospital. Among the remaining 45 infections (78%), metagenomic NGS made concurrent diagnoses in 19. Of the 26 infections not identified by metagenomic NGS, 11 were diagnosed by serologic testing only, 7 were diagnosed from tissue samples other than CSF, and 8 were negative on metagenomic NGS owing to low titers of pathogens in CSF. A total of 8 of 13 diagnoses made solely by metagenomic NGS had a likely clinical effect, with 7 of 13 guiding treatment. CONCLUSIONS Routine microbiologic testing is often insufficient to detect all neuroinvasive pathogens. In this study, metagenomic NGS of CSF obtained from patients with meningitis or encephalitis improved diagnosis of neurologic infections and provided actionable information in some cases. (Funded by the National Institutes of Health and others; PDAID ClinicalTrials.gov number, .)

SUMMARY A 14-year-old boy with severe combined immunodeficiency presented three times to a medical facility over a period of 4 months with fever and headache that progressed to hydrocephalus and status epilepticus necessitating a medically induced coma. Diagnostic workup including brain biopsy was unrevealing. Unbiased next-generation sequencing of the cerebrospinal fluid identified 475 of 3,063,784 sequence reads (0.016%) corresponding to leptospira infection. Clinical assays for leptospirosis were negative. Targeted antimicrobial agents were administered, and the patient was discharged home 32 days later with a status close to his premorbid condition. Polymerase-chain-reaction (PCR) and serologic testing at the Centers for Disease Control and Prevention (CDC) subsequently confirmed evidence of Leptospira santarosai infection.

SUMMARY Background Enterovirus D68 (EV-D68) is implicated in a widespread 2014 outbreak of severe respiratory illness across the United States, and has also been sporadically reported in patients with acute flaccid myelitis (AFM). The association between EV-D68 infection and AFM remains unclear. Methods Here we report metagenomic and molecular epidemiological analyses of 25 AFM cases in California and Colorado from 2012−2014. Findings EV-D68 was detected in respiratory secretions from 7 of 11 (64%) patients comprising two temporally and geographically linked AFM clusters at the height of the 2014 outbreak, and from 12 of 25 (48%) investigated AFM cases overall. Phylogenetic analysis revealed that all AFM-associated EV-D68 sequences grouped into a single novel clade B1 strain that originally emerged in 2010. Out of six observed coding polymorphisms in the clade B1 EV-D68 polyprotein, 5 of 6 polymorphisms were shared between neuropathogenic poliovirus and/or EV-D70. One child with AFM and a sibling with only upper respiratory illness were both infected by identical EV-D68 strains, suggesting a potential role for host-specific factors in differential responses to EV-D68 infection. Notably, EV-D68 viremia was identified in a child experiencing acute neurologic progression of his paralytic illness. Deep metagenomic sequencing of CSF from 14 AFM cases failed to reveal evidence of an alternative infectious etiology to EV-D68. Interpretation Taken together, these findings strengthen the putative association between EV-D68 and AFM, as well as the contention that AFM is a rare yet severe clinical manifestation of EV-D68 infection in susceptible hosts.

Unbiased next-generation sequencing (NGS) approaches enable comprehensive pathogen detection in the clinical microbiology laboratory and have numerous applications for public health surveillance, outbreak investigation, and the diagnosis of infectious diseases. However, practical deployment of the technology is hindered by the bioinformatics challenge of analyzing results accurately and in a clinically relevant timeframe. Here we describe SURPI (''sequence-based ultrarapid pathogen identification''), a computational pipeline for pathogen identification from complex metagenomic NGS data generated from clinical samples, and demonstrate use of the pipeline in the analysis of 237 clinical samples comprising more than 1.1 billion sequences. Deployable on both cloud-based and standalone servers, SURPI leverages two state-of-the-art aligners for accelerated analyses, SNAP and RAPSearch, which are as accurate as existing bioinformatics tools but orders of magnitude faster in performance. In fast mode, SURPI detects viruses and bacteria by scanning data sets of 7-500 million reads in 11 min to 5 h, while in comprehensive mode, all known microorganisms are identified, followed by de novo assembly and protein homology searches for divergent viruses in 50 min to 16 h. SURPI has also directly contributed to real-time microbial diagnosis in acutely ill patients, underscoring its potential key role in the development of unbiased NGS-based clinical assays in infectious diseases that demand rapid turnaround times.