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      In‐field detection and characterization of B/Victoria lineage deletion variant viruses causing early influenza activity and an outbreak in Louisiana, 2019

      brief-report

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          Abstract

          Background

          In 2019, the Louisiana Department of Health reported an early influenza B/Victoria (B/VIC) virus outbreak.

          Method

          As it was an atypically large outbreak, we deployed to Louisiana to investigate it using genomics and a triplex real‐time RT‐PCR assay to detect three antigenically distinct B/VIC lineage variant viruses.

          Results

          The investigation indicated that B/VIC V1A.3 subclade, containing a three amino acid deletion in the hemagglutinin and known to be antigenically distinct to the B/Colorado/06/2017 vaccine virus, was the most prevalent circulating virus within the specimens evaluated (86/88 in real‐time RT‐PCR).

          Conclusion

          This work underscores the value of portable platforms for rapid, onsite pathogen characterization.

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          Most cited references9

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          The neighbor-joining method: a new method for reconstructing phylogenetic trees.

          N Saitou, M Nei (1987)
          A new method called the neighbor-joining method is proposed for reconstructing phylogenetic trees from evolutionary distance data. The principle of this method is to find pairs of operational taxonomic units (OTUs [= neighbors]) that minimize the total branch length at each stage of clustering of OTUs starting with a starlike tree. The branch lengths as well as the topology of a parsimonious tree can quickly be obtained by using this method. Using computer simulation, we studied the efficiency of this method in obtaining the correct unrooted tree in comparison with that of five other tree-making methods: the unweighted pair group method of analysis, Farris's method, Sattath and Tversky's method, Li's method, and Tateno et al.'s modified Farris method. The new, neighbor-joining method and Sattath and Tversky's method are shown to be generally better than the other methods.
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            Changes in Influenza and Other Respiratory Virus Activity During the COVID-19 Pandemic — United States, 2020–2021

            Sonja Olsen, Amber Winn, Alicia Budd … (2021)
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              Viral deep sequencing needs an adaptive approach: IRMA, the iterative refinement meta-assembler

              Samuel Shepard, Sarah Meno, Justin Bahl … (2016)
              Background Deep sequencing makes it possible to observe low-frequency viral variants and sub-populations with greater accuracy and sensitivity than ever before. Existing platforms can be used to multiplex a large number of samples; however, analysis of the resulting data is complex and involves separating barcoded samples and various read manipulation processes ending in final assembly. Many assembly tools were designed with larger genomes and higher fidelity polymerases in mind and do not perform well with reads derived from highly variable viral genomes. Reference-based assemblers may leave gaps in viral assemblies while de novo assemblers may struggle to assemble unique genomes. Results The IRMA (iterative refinement meta-assembler) pipeline solves the problem of viral variation by the iterative optimization of read gathering and assembly. As with all reference-based assembly, reads are included in assembly when they match consensus template sets; however, IRMA provides for on-the-fly reference editing, correction, and optional elongation without the need for additional reference selection. This increases both read depth and breadth. IRMA also focuses on quality control, error correction, indel reporting, variant calling and variant phasing. In fact, IRMA’s ability to detect and phase minor variants is one of its most distinguishing features. We have built modules for influenza and ebolavirus. We demonstrate usage and provide calibration data from mixture experiments. Methods for variant calling, phasing, and error estimation/correction have been redesigned to meet the needs of viral genomic sequencing. Conclusion IRMA provides a robust next-generation sequencing assembly solution that is adapted to the needs and characteristics of viral genomes. The software solves issues related to the genetic diversity of viruses while providing customized variant calling, phasing, and quality control. IRMA is freely available for non-commercial use on Linux and Mac OS X and has been parallelized for high-throughput computing. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3030-6) contains supplementary material, which is available to authorized users.
              Article 0 comments Cited 95 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                John R. Barnes: fzq9@cdc.gov
                Journal
                Journal ID (nlm-ta): Influenza Other Respir Viruses
                Journal ID (iso-abbrev): Influenza Other Respir Viruses
                Journal ID (doi): 10.1111/(ISSN)1750-2659
                Journal ID (publisher-id): IRV
                Title: Influenza and Other Respiratory Viruses
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Print): 1750-2640
                ISSN (Electronic): 1750-2659
                Publication date (Electronic): 05 January 2024
                Publication date Collection: January 2024
                Volume: 18
                Issue: 1 ( doiID: 10.1111/irv.v18.1 )
                Electronic Location Identifier: e13246
                Affiliations
                [ 1 ] Virology, Surveillance and Diagnosis Branch, Influenza Division Centers for Disease Control and Prevention Atlanta Georgia USA
                [ 2 ] Louisiana Department of Health Office of Public Health Laboratory Baton Rouge Louisiana USA
                [ 3 ] Louisiana Department of Health Office of Public Health, Infectious Disease Epidemiology New Orleans Louisiana USA
                Author notes
                [*] [* ] Correspondence

                John R. Barnes, Virology, Surveillance and Diagnosis Branch, Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

                Email: fzq9@ 123456cdc.gov

                Author information
                https://orcid.org/0000-0003-0859-9604
                Article
                Publisher ID: IRV13246
                DOI: 10.1111/irv.13246
                PMC ID: 10767671
                SO-VID: 66dd099a-eea0-41f0-a77f-1fe0be7efe7a
                Copyright © © 2024 The Authors. Influenza and Other Respiratory Viruses published by John Wiley & Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                Date revision received : 06 December 2023
                Date received : 13 October 2023
                Date accepted : 10 December 2023
                Page count
                Figures: 1, Tables: 1, Pages: 5, Words: 2695
                Categories
                Subject: Short Communication
                Subject: Short Communications
                Custom metadata
                source-schema-version-number 2.0
                cover-date January 2024
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.6 mode:remove_FC converted:05.01.2024

                ScienceOpen disciplines: Infectious disease & Microbiology
                Keywords: amino acid deletion,b/victoria lineage,in‐field detection,influenza outbreak
                Data availability:
                ScienceOpen disciplines: Infectious disease & Microbiology
                Keywords: amino acid deletion, b/victoria lineage, in‐field detection, influenza outbreak

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