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      Enhanced Virus Detection and Metagenomic Sequencing in Patients with Meningitis and Encephalitis

      research-article
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      mBio
      American Society for Microbiology
      encephalitis, metagenomic sequencing, next-generation sequencing (NGS), meningitis, virus, hybrid capture, methylated DNA depletion

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          ABSTRACT

          Meningitis and encephalitis are leading causes of central nervous system (CNS) disease and often result in severe neurological compromise or death. Traditional diagnostic workflows largely rely on pathogen-specific tests, sometimes over days to weeks, whereas metagenomic next-generation sequencing (mNGS) profiles all nucleic acid in a sample. In this single-center, prospective study, 68 hospitalized patients with known ( n = 44) or suspected ( n = 24) CNS infections underwent mNGS from RNA and DNA to identify potential pathogens and also targeted sequencing of viruses using hybrid capture. Using a computational metagenomic classification pipeline based on KrakenUniq and BLAST, we detected pathogen nucleic acid in cerebrospinal fluid (CSF) from 22 subjects, 3 of whom had no clinical diagnosis by routine workup. Among subjects diagnosed with infection by serology and/or peripheral samples, we demonstrated the utility of mNGS to detect pathogen nucleic acid in CSF, importantly for the Ixodes scapularis tick-borne pathogens Powassan virus, Borrelia burgdorferi, and Anaplasma phagocytophilum. We also evaluated two methods to enhance the detection of viral nucleic acid, hybrid capture and methylated DNA depletion. Hybrid capture nearly universally increased viral read recovery. Although results for methylated DNA depletion were mixed, it allowed the detection of varicella-zoster virus DNA in two samples that were negative by standard mNGS. Overall, mNGS is a promising approach that can test for multiple pathogens simultaneously, with efficacy similar to that of pathogen-specific tests, and can uncover geographically relevant infectious CNS disease, such as tick-borne infections in New England. With further laboratory and computational enhancements, mNGS may become a mainstay of workup for encephalitis and meningitis.

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          Most cited references57

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            Basic local alignment search tool.

            A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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              Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

              Summary Background Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding Bill & Melinda Gates Foundation.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                mBio
                mBio
                mbio
                mBio
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2150-7511
                31 August 2021
                Jul-Aug 2021
                31 August 2021
                : 12
                : 4
                : e01143-21
                Affiliations
                [a ] Broad Institutegrid.66859.34, of MIT and Harvard, Cambridge, Massachusetts, USA
                [b ] Division of Infectious Diseases, Massachusetts General Hospitalgrid.32224.35, , Boston, Massachusetts, USA
                [c ] Emory University School of Medicinegrid.471395.d, , Atlanta, Georgia, USA
                [d ] Department of Neurology, Massachusetts General Hospitalgrid.32224.35, , Boston, Massachusetts, USA
                [e ] Harvard Medical School, Boston, Massachusetts, USA
                [f ] Harvard-MIT Program of Health Sciences and Technology, Cambridge, Massachusetts, USA
                [g ] Department of Pathology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
                [h ] Department of Pediatrics, Harvard Medical School, Children’s Hospital, Boston, Massachusetts, USA
                [i ] Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
                [j ] Division of Infectious Diseases, Brigham and Women’s Hospital, Boston, Massachusetts, USA
                [k ] Department of Pathology, Massachusetts General Hospitalgrid.32224.35, , Boston, Massachusetts, USA
                [l ] University of Iowa, Department of Neurology, Iowa City, Iowa, USA
                [m ] Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA
                [n ] Department of Immunology and Infectious Disease, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
                [o ] Howard Hughes Medical Institute, Chevy Chase, Maryland, USA
                Virginia Polytechnic Institute and State University
                Author notes
                [*]

                Present address: Kaelyn C. Cummins, Baylor College of Medicine, Houston, Texas, USA; Jesse M. Thon, Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Cormac M. Kinsella, Amsterdam UMC, Amsterdam, The Netherlands.

                Anne Piantadosi, Shibani S. Mukerji, and Simon Ye all contributed equally to this work. Author order was determined by mutual agreement among first authors.

                Tracey A. Cho and Pardis Sabeti contributed equally.

                Author information
                https://orcid.org/0000-0002-5942-1534
                https://orcid.org/0000-0002-1221-5725
                Article
                mBio01143-21
                10.1128/mBio.01143-21
                8406231
                34465023
                d0cbc717-b553-44c2-b742-f735a7225013
                Copyright © 2021 Piantadosi et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 4 May 2021
                : 2 July 2021
                Page count
                supplementary-material: 10, Figures: 4, Tables: 1, Equations: 0, References: 56, Pages: 13, Words: 9804
                Funding
                Funded by: HHS | NIH | National Institute of Mental Health (NIMH), FundRef https://doi.org/10.13039/100000025;
                Award ID: K23MH115812
                Award Recipient :
                Funded by: HHS | NIH | National Institute of Allergy and Infectious Diseases (NIAID), FundRef https://doi.org/10.13039/100000060;
                Award ID: 5P30AI060354-16
                Award Recipient :
                Funded by: Harvard Medical School (HMS), FundRef https://doi.org/10.13039/100006691;
                Award ID: Harvard University Eleanor and Miles Shore Fellowship Program
                Award Recipient : Award Recipient :
                Funded by: HHS | NIH | National Institute of Allergy and Infectious Diseases (NIAID), FundRef https://doi.org/10.13039/100000060;
                Award ID: K08AI139348
                Award Recipient :
                Funded by: HHS | NIH | National Center for Advancing Translational Sciences (NCATS), FundRef https://doi.org/10.13039/100006108;
                Award ID: KL2TR002542
                Award Recipient :
                Categories
                Research Article
                virology, Virology
                Custom metadata
                July/August 2021

                Life sciences
                encephalitis,metagenomic sequencing,next-generation sequencing (ngs),meningitis,virus,hybrid capture,methylated dna depletion

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