Identifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed. OBJECTIVE To present a case series of patients with diagnostically challenging subacute or chronic meningitis using metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) supported by a statistical framework generated from mNGS of control samples from the environment and from patients who were noninfectious. DESIGN, SETTING, AND PARTICIPANTS In this case series, mNGS data obtained from the CSF of 94 patients with noninfectious neuroinflammatory disorders and from 24 water and reagent control samples were used to develop and implement a weighted scoring metric based on z scores at the species and genus levels for both nucleotide and protein alignments to prioritize and rank the mNGS results. Total RNA was extracted for mNGS from the CSF of 7 participants with subacute or chronic meningitis who were recruited between September 2013 and March 2017 as part of a multicenter study of mNGS pathogen discovery among patients with suspected neuroinflammatory conditions. The neurologic infections identified by mNGS in these 7 participants represented a diverse array of pathogens. The patients were referred from the University of California, San Francisco Medical Center (n = 2), Zuckerberg San Francisco General Hospital and Trauma Center (n = 2), Cleveland Clinic (n = 1), University of Washington (n = 1), and Kaiser Permanente (n = 1). A weighted z score was used to filter out environmental contaminants and facilitate efficient data triage and analysis. MAIN OUTCOMES AND MEASURES Pathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results. RESULTS The 7 participants ranged in age from 10 to 55 years, and 3 (43%) were female. A parasitic worm (Taenia solium, in 2 participants), a virus (HIV-1), and 4 fungi (Cryptococcus neoformans, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis) were identified among the 7 participants by using mNGS. Evaluating mNGS data with a weighted z score-based scoring algorithm reduced the reported microbial taxa by a mean of 87% (range, 41%-99%) when taxa with a combined score of 0 or less were removed, effectively separating bona fide pathogen sequences from spurious environmental sequences so that, in each case, the causative pathogen was found within the top 2 scoring microbes identified using the algorithm. CONCLUSIONS AND RELEVANCE Diverse microbial pathogens were identified by mNGS in the CSF of patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for 1 year, the first reported case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of C dubliniensis meningitis. Prioritizing metagenomic data with a scoring algorithm greatly clarified data interpretation and highlighted the problem of attributing biological significance to organisms present in contr...

SignificanceLower respiratory tract infections (LRTIs) are the leading cause of infectious disease-related deaths worldwide yet remain challenging to diagnose because of limitations in existing microbiologic tests. In critically ill patients, noninfectious respiratory syndromes that resemble LRTIs further complicate diagnosis and confound targeted treatment. To address this, we developed a metagenomic sequencing-based approach that simultaneously interrogates three core elements of acute airway infections: the pathogen, airway microbiome, and host response. We studied this approach in a prospective cohort of critically ill patients with acute respiratory failure and found that combining pathogen, microbiome, and host gene expression metrics achieved accurate LRTI diagnosis and identified etiologic pathogens in patients with clinically identified infections but otherwise negative testing.

SUMMARY A 37-year-old man with a history of seminoma presented with vertigo, ataxia, and diplopia. An autoantibody specific for kelch-like protein 11 (KLHL11) was identified with the use of programmable phage display. Immunoassays were used to identify KLHL11 IgG in 12 other men with similar neurologic features and testicular disease. Immunostaining of the patient’s IgG on mouse brain tissue showed sparse but distinctive points of staining in multiple brain regions, with enrichment in perivascular and perimeningeal tissues. The onset of the neurologic syndrome preceded the diagnosis of seminoma in 9 of the 13 patients. An age-adjusted estimate of the prevalence of autoimmune KLHL11 encephalitis in Olmsted County, Minnesota, was 2.79 cases per 100,000 men.

BackgroundOcular infections remain a major cause of blindness and morbidity worldwide. While prognosis is dependent on the timing and accuracy of diagnosis, the etiology remains elusive in ~50 % of presumed infectious uveitis cases. The objective of this study is to determine if unbiased metagenomic deep sequencing (MDS) can accurately detect pathogens in intraocular fluid samples of patients with uveitis.MethodsThis is a proof-of-concept study, in which intraocular fluid samples were obtained from five subjects with known diagnoses, and one subject with bilateral chronic uveitis without a known etiology. Samples were subjected to MDS, and results were compared with those from conventional diagnostic tests. Pathogens were identified using a rapid computational pipeline to analyze the non-host sequences obtained from MDS.ResultsUnbiased MDS of intraocular fluid produced results concordant with known diagnoses in subjects with (n = 4) and without (n = 1) uveitis. Samples positive for Cryptococcus neoformans, Toxoplasma gondii, and herpes simplex virus 1 as tested by a Clinical Laboratory Improvement Amendments-certified laboratory were correctly identified with MDS. Rubella virus was identified in one case of chronic bilateral idiopathic uveitis. The subject’s strain was most closely related to a German rubella virus strain isolated in 1992, one year before he developed a fever and rash while living in Germany. The pattern and the number of viral identified mutations present in the patient’s strain were consistent with long-term viral replication in the eye.ConclusionsMDS can identify fungi, parasites, and DNA and RNA viruses in minute volumes of intraocular fluid samples. The identification of chronic intraocular rubella virus infection highlights the eye’s role as a long-term pathogen reservoir, which has implications for virus eradication and emerging global epidemics.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-016-0344-6) contains supplementary material, which is available to authorized users.

Objective Immunodeficient patients are particularly vulnerable to neuroinvasive infections that can be challenging to diagnose. Metagenomic next-generation sequencing can identify unusual or novel microbes and is therefore well suited for investigating the etiology of chronic meningoencephalitis in immunodeficient patients. Methods We present the case of a 34 year-old man with X-linked agammaglobulinemia from Australia suffering from three years of meningoencephalitis that defied an etiologic diagnosis despite extensive conventional testing, including a brain biopsy. Metagenomic next-generation sequencing of his cerebrospinal fluid and brain biopsy tissue was performed to identify a causative pathogen. Results Sequences aligning to multiple Cache Valley virus genes were identified via metagenomic next-generation sequencing. Reverse transcription polymerase chain reaction and immunohistochemistry subsequently confirmed the presence of Cache Valley virus in the brain biopsy tissue. Interpretation Cache Valley virus, a mosquito-borne orthobunyavirus, has only been identified in three immunocompetent North American patients with acute neuroinvasive disease. The reported severity ranges from a self-limiting meningitis to a rapidly fatal meningoencephalitis with multi-organ failure. The virus has never been known to cause a chronic systemic or neurologic infection in humans. Cache Valley virus has also never previously been detected on the Australian continent. Indeed, our research subject traveled to North and South Carolina and Michigan in the weeks prior to the onset of his illness. This report demonstrates that metagenomic next-generation sequencing allows for unbiased pathogen identification, the early detection of emerging viruses as they spread to new locales, and the discovery of novel disease phenotypes.

Since 2012, the United States has experienced a biennial spike in pediatric acute flaccid myelitis (AFM). 1-6 Epidemiologic evidence suggests non-polio enteroviruses (EVs) are a potential etiology, yet EV RNA is rarely detected in cerebrospinal fluid (CSF). 2 We interrogated CSF from children with AFM (n=42) and pediatric other neurologic disease controls (n=58) for intrathecal anti-viral antibodies using a phage display library expressing 481,966 overlapping peptides derived from all known vertebrate and arboviruses (VirScan). We also performed metagenomic next-generation sequencing (mNGS) of AFM CSF RNA (n=20 cases), both unbiased and with targeted enrichment for EVs. Using VirScan, the only viral family significantly enriched by the CSF of AFM cases relative to controls was Picornaviridae, with the most enriched Picornaviridae peptides belonging to the genus Enterovirus (n=29/42 cases versus 4/58 controls). EV VP1 ELISA confirmed this finding (n=22/26 cases versus 7/50 controls). mNGS did not detect additional EV RNA. Despite rare detection of EV RNA, pan-viral serology identified frequently high levels of CSF EV-specific antibodies in AFM compared to controls, providing further evidence for a causal role of non-polio EVs in AFM.

Solid organ transplant patients are vulnerable to suffering neurologic complications from a wide array of viral infections and can be sentinels in the population who are first to get serious complications from emerging infections like the recent waves of arboviruses, including West Nile virus, Chikungunya virus, Zika virus, and Dengue virus. The diverse and rapidly changing landscape of possible causes of viral encephalitis poses great challenges for traditional candidate‐based infectious disease diagnostics that already fail to identify a causative pathogen in approximately 50% of encephalitis cases. We present the case of a 14‐year‐old girl on immunosuppression for a renal transplant who presented with acute meningoencephalitis. Traditional diagnostics failed to identify an etiology. RNA extracted from her cerebrospinal fluid was subjected to unbiased metagenomic deep sequencing, enhanced with the use of a Cas9‐based technique for host depletion. This analysis identified West Nile virus (WNV). Convalescent serum serologies subsequently confirmed WNV seroconversion. These results support a clear clinical role for metagenomic deep sequencing in the setting of suspected viral encephalitis, especially in the context of the high‐risk transplant patient population.

Globally, there are an estimated 10.6 million cases of meningitis and 288,000 deaths every year, with the vast majority occurring in low- and middle-income countries. In addition, many survivors suffer from long-term neurological sequelae. Most laboratories assay only for common bacterial etiologies using culture and directed PCR, and the majority of meningitis cases lack microbiological diagnoses, impeding institution of evidence-based treatment and prevention strategies. We report here the results of a validation and application study of using unbiased metagenomic sequencing to determine etiologies of idiopathic (of unknown cause) cases. This included CSF from patients with known neurologic infections, with idiopathic meningitis, and without infection admitted in the largest children’s hospital of Bangladesh and environmental samples. Using mNGS and machine learning, we identified and confirmed an etiology (viral or bacterial) in 40% of idiopathic cases. We detected three instances of Chikungunya virus (CHIKV) that were >99% identical to each other and to a strain previously recognized to cause systemic illness only in 2017. CHIKV qPCR of all remaining stored 472 CSF samples from children who presented with idiopathic meningitis in 2017 at the same hospital uncovered an unrecognized CHIKV meningitis outbreak. CSF mNGS can complement conventional diagnostic methods to identify etiologies of meningitis, and the improved patient- and population-level data can inform better policy decisions.