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      Meningococcal Deduced Vaccine Antigen Reactivity (MenDeVAR) Index: a Rapid and Accessible Tool That Exploits Genomic Data in Public Health and Clinical Microbiology Applications

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          Abstract

          As microbial genomics makes increasingly important contributions to clinical and public health microbiology, the interpretation of whole-genome sequence data by nonspecialists becomes essential. In the absence of capsule-based vaccines, two protein-based vaccines have been used for the prevention of invasive serogroup B meningococcal disease (IMD) since their licensure in 2013 and 2014. These vaccines have different components and different levels of coverage of meningococcal variants. Hence, decisions regarding which vaccine to use in managing serogroup B IMD outbreaks require information about the index case isolate, including (i) the presence of particular vaccine antigen variants, (ii) the expression of vaccine antigens, and (iii) the likely susceptibility of its antigen variants to antibody-dependent bactericidal killing.

          ABSTRACT

          As microbial genomics makes increasingly important contributions to clinical and public health microbiology, the interpretation of whole-genome sequence data by nonspecialists becomes essential. In the absence of capsule-based vaccines, two protein-based vaccines have been used for the prevention of invasive serogroup B meningococcal disease (IMD) since their licensure in 2013 and 2014. These vaccines have different components and different levels of coverage of meningococcal variants. Hence, decisions regarding which vaccine to use in managing serogroup B IMD outbreaks require information about the index case isolate, including (i) the presence of particular vaccine antigen variants, (ii) the expression of vaccine antigens, and (iii) the likely susceptibility of its antigen variants to antibody-dependent bactericidal killing. To obtain this information requires a multitude of laboratory assays, impractical in real-time clinical settings, where the information is most urgently needed. To facilitate assessment for public health and clinical purposes, we synthesized genomic and experimental data from published sources to develop and implement the Meningococcal Deduced Vaccine Antigen Reactivity (MenDeVAR) Index, which is publicly available on PubMLST ( https://pubmlst.org). Using whole-genome sequences or individual gene sequences obtained from IMD isolates or clinical specimens, the MenDeVAR Index provides rapid evidence-based information on the presence and possible immunological cross-reactivity of different meningococcal vaccine antigen variants. The MenDeVAR Index enables practitioners who are not genomics specialists to assess the likely reactivity of vaccines for individual cases, outbreak management, or the assessment of public health vaccine programs. The MenDeVAR Index has been developed in consultation with, but independently of, both the 4CMenB (Bexsero; GSK) and rLP2086 (Trumenba; Pfizer, Inc.) vaccine manufacturers.

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          Most cited references66

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          Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications

          The PubMLST.org website hosts a collection of open-access, curated databases that integrate population sequence data with provenance and phenotype information for over 100 different microbial species and genera.  Although the PubMLST website was conceived as part of the development of the first multi-locus sequence typing (MLST) scheme in 1998 the software it uses, the Bacterial Isolate Genome Sequence database (BIGSdb, published in 2010), enables PubMLST to include all levels of sequence data, from single gene sequences up to and including complete, finished genomes.  Here we describe developments in the BIGSdb software made from publication to June 2018 and show how the platform realises microbial population genomics for a wide range of applications.  The system is based on the gene-by-gene analysis of microbial genomes, with each deposited sequence annotated and curated to identify the genes present and systematically catalogue their variation.  Originally intended as a means of characterising isolates with typing schemes, the synthesis of sequences and records of genetic variation with provenance and phenotype data permits highly scalable (whole genome sequence data for tens of thousands of isolates) means of addressing a wide range of functional questions, including: the prediction of antimicrobial resistance; likely cross-reactivity with vaccine antigens; and the functional activities of different variants that lead to key phenotypes.  There are no limitations to the number of sequences, genetic loci, allelic variants or schemes (combinations of loci) that can be included, enabling each database to represent an expanding catalogue of the genetic variation of the population in question.  In addition to providing web-accessible analyses and links to third-party analysis and visualisation tools, the BIGSdb software includes a RESTful application programming interface (API) that enables access to all the underlying data for third-party applications and data analysis pipelines.
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            DNA sequencing with chain-terminating inhibitors

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              MLST revisited: the gene-by-gene approach to bacterial genomics.

              Multilocus sequence typing (MLST) was proposed in 1998 as a portable sequence-based method for identifying clonal relationships among bacteria. Today, in the whole-genome era of microbiology, the need for systematic, standardized descriptions of bacterial genotypic variation remains a priority. Here, to meet this need, we draw on the successes of MLST and 16S rRNA gene sequencing to propose a hierarchical gene-by-gene approach that reflects functional and evolutionary relationships and catalogues bacteria 'from domain to strain'. Our gene-based typing approach using online platforms such as the Bacterial Isolate Genome Sequence Database (BIGSdb) allows the scalable organization and analysis of whole-genome sequence data.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                J Clin Microbiol
                J Clin Microbiol
                jcm
                jcm
                JCM
                Journal of Clinical Microbiology
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                0095-1137
                1098-660X
                14 October 2020
                17 December 2020
                January 2021
                : 59
                : 1
                : e02161-20
                Affiliations
                [a ]Department of Zoology, University of Oxford, Oxford, United Kingdom
                [b ]Paediatric Infectious Diseases Unit, St. George's University Hospitals NHS Foundation Trust, London, United Kingdom
                [c ]Glasgow Dental School, University of Glasgow, Glasgow, United Kingdom
                [d ]Scottish Microbiology Reference Laboratory, NHS Greater Glasgow & Clyde, Glasgow, United Kingdom
                [e ]Public Health Scotland, Glasgow, United Kingdom
                University of Iowa College of Medicine
                Author notes
                Address correspondence to Martin C. J. Maiden, martin.maiden@ 123456zoo.ox.ac.uk .

                Citation Rodrigues CMC, Jolley KA, Smith A, Cameron JC, Feavers IM, Maiden MCJ. 2021. Meningococcal Deduced Vaccine Antigen Reactivity (MenDeVAR) Index: a rapid and accessible tool that exploits genomic data in public health and clinical microbiology applications. J Clin Microbiol 59:e02161-20. https://doi.org/10.1128/JCM.02161-20.

                Author information
                https://orcid.org/0000-0003-0942-3707
                https://orcid.org/0000-0002-0751-0287
                https://orcid.org/0000-0001-6321-5138
                Article
                02161-20
                10.1128/JCM.02161-20
                7771438
                33055180
                c402042e-bc79-42eb-b4b3-467f82678465
                Copyright © 2020 Rodrigues et al.

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

                History
                : 18 August 2020
                : 29 September 2020
                : 9 October 2020
                Page count
                supplementary-material: 1, Figures: 2, Tables: 3, Equations: 0, References: 66, Pages: 13, Words: 8713
                Funding
                Funded by: Wellcome Trust;
                Award ID: 218205/Z/19/Z
                Award Recipient : Martin C. J. Maiden Award Recipient :
                Funded by: Thrasher Research Fund (TRF), https://doi.org/10.13039/100005627;
                Award ID: Integrating Genomic Epidemiology Into Public Health Microbiology for Meningococcal Disease
                Award Recipient : Charlene M. C. Rodrigues
                Categories
                Bacteriology
                Custom metadata
                January 2021

                Microbiology & Virology
                meningococcal disease,neisseria meningitidis,vaccines,meningococcal deduced vaccine antigen reactivity (mendevar),meningococcal antigen typing system (mats),meningococcal antigen surface expression (measure) assay,serum bactericidal activity assay,outbreaks,whole-genome sequencing,public health

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