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      Metagenomics for neurological infections — expanding our imagination

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          Abstract

          Over the past two decades, the diagnosis rate for patients with encephalitis has remained poor despite advances in pathogen-specific testing such as PCR and antigen assays. Metagenomic next-generation sequencing (mNGS) of RNA and DNA extracted from cerebrospinal fluid and brain tissue now offers another strategy for diagnosing neurological infections. Given that mNGS simultaneously assays for a wide range of infectious agents in an unbiased manner, it can identify pathogens that were not part of a neurologist’s initial differential diagnosis either because of the rarity of the infection, because the microorganism has not been previously associated with a clinical phenotype or because it is a newly discovered organism. This Review discusses the technical advantages and pitfalls of cerebrospinal fluid mNGS in the context of patients with neuroinflammatory syndromes, including encephalitis, meningitis and myelitis. We also speculate on how mNGS testing potentially fits into current diagnostic testing algorithms given data on mNGS test performance, cost and turnaround time. Finally, the Review highlights future directions for mNGS technology and other hypothesis-free testing methodologies that are in development.

          Abstract

          This Review discusses the advantages and pitfalls of metagenomic next-generation sequencing (mNGS) in patients with encephalitis, meningitis and myelitis. The authors outline data on mNGS test performance, cost and turnaround time and highlight future directions for mNGS technology.

          Key points

          • Meningoencephalitis remains a challenging diagnosis owing to the multitude of possible infectious and autoimmune causes.

          • Meningoencephalitis is associated with a high rate of morbidity and mortality and requires prompt diagnosis and treatment.

          • Metagenomic next-generation sequencing (mNGS) is now a clinically validated test for neuroinfectious diseases that can aid clinicians with a timely diagnosis.

          • mNGS can improve the detection of pathogens that were missed by clinicians or on standard direct testing.

          • mNGS does not perform well when indirect tests are required to make the diagnosis (for example, serology), when infections are compartmentalized and for certain low abundance pathogens.

          • The clinical context of the case is required when interpreting the results of mNGS.

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          Most cited references63

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          CRISPR-Cas12–based detection of SARS-CoV-2

          An outbreak of betacoronavirus SARS-CoV-2 began in Wuhan, China in December 2019. COVID-19, the disease associated with infection, rapidly spread to produce a global pandemic. We report development of a rapid (<40 min), easy-to-implement and accurate CRISPR-Cas12-based lateral flow assay for detection of SARS-CoV-2 from respiratory swab RNA extracts. We validated our method using contrived reference samples and clinical samples from US patients, including 36 patients with COVID-19 infection and 42 patients with other viral respiratory infections. Our CRISPR-based DETECTR assay provides a visual and faster alternative to the US CDC SARS-CoV-2 real-time RT-PCR assay, with 95% positive predictive agreement and 100% negative predictive agreement.. SARS-CoV-2 in patient samples is detected in under an hour using a CRISPR-based lateral flow assay.
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            Is Open Access

            Massively multiplexed nucleic acid detection with Cas13

            The great majority of globally circulating pathogens go undetected, undermining patient care and hindering outbreak preparedness and response. To enable routine surveillance and comprehensive diagnostic applications, there is a need for detection technologies that can scale to test many samples 1–3 while simultaneously testing for many pathogens 4–6 . Here, we develop Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN), a platform for scalable, multiplexed pathogen detection. In the CARMEN platform, nanolitre droplets containing CRISPR-based nucleic acid detection reagents 7 self-organize in a microwell array 8 to pair with droplets of amplified samples, testing each sample against each CRISPR RNA (crRNA) in replicate. The combination of CARMEN and Cas13 detection (CARMEN–Cas13) enables robust testing of more than 4,500 crRNA–target pairs on a single array. Using CARMEN–Cas13, we developed a multiplexed assay that simultaneously differentiates all 169 human-associated viruses with at least 10 published genome sequences and rapidly incorporated an additional crRNA to detect the causative agent of the 2020 COVID-19 pandemic. CARMEN–Cas13 further enables comprehensive subtyping of influenza A strains and multiplexed identification of dozens of HIV drug-resistance mutations. The intrinsic multiplexing and throughput capabilities of CARMEN make it practical to scale, as miniaturization decreases reagent cost per test by more than 300-fold. Scalable, highly multiplexed CRISPR-based nucleic acid detection shifts diagnostic and surveillance efforts from targeted testing of high-priority samples to comprehensive testing of large sample sets, greatly benefiting patients and public health 9–11 .
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              Is Open Access

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

              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.
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                Author and article information

                Contributors
                michael.wilson@ucsf.edu
                Journal
                Nat Rev Neurol
                Nat Rev Neurol
                Nature Reviews. Neurology
                Nature Publishing Group UK (London )
                1759-4758
                1759-4766
                13 July 2020
                : 1-10
                Affiliations
                [1 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Weill Institute for Neurosciences, , University of California, ; San Francisco, CA USA
                [2 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Department of Neurology, , University of California, ; San Francisco, CA USA
                Author information
                http://orcid.org/0000-0002-8705-5084
                Article
                374
                10.1038/s41582-020-0374-y
                7356134
                32661342
                14cc903a-d5f1-42b3-abce-7a7f25f4d6c5
                © Springer Nature Limited 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 4 June 2020
                Categories
                Review Article

                central nervous system infections,genetics research,diagnostic markers

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