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Rapid virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing

BACKGROUND: Newcastle disease (ND) outbreaks are global challenges to the poultry industry. Effective management requires rapid identification and virulence prediction of the circulating Newcastle disease viruses (NDV), the causative agent of ND. However, these diagnostics are hindered by the geneti...

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Autores principales: Butt, Salman L., Taylor, Tonya L., Volkening, Jeremy D., Dimitrov, Kiril M., Williams-Coplin, Dawn, Lahmers, Kevin K., Miller, Patti J., Rana, Asif M., Suarez, David L., Afonso, Claudio L., Stanton, James B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6251111/
https://www.ncbi.nlm.nih.gov/pubmed/30466441
http://dx.doi.org/10.1186/s12985-018-1077-5
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author Butt, Salman L.
Taylor, Tonya L.
Volkening, Jeremy D.
Dimitrov, Kiril M.
Williams-Coplin, Dawn
Lahmers, Kevin K.
Miller, Patti J.
Rana, Asif M.
Suarez, David L.
Afonso, Claudio L.
Stanton, James B.
author_facet Butt, Salman L.
Taylor, Tonya L.
Volkening, Jeremy D.
Dimitrov, Kiril M.
Williams-Coplin, Dawn
Lahmers, Kevin K.
Miller, Patti J.
Rana, Asif M.
Suarez, David L.
Afonso, Claudio L.
Stanton, James B.
author_sort Butt, Salman L.
collection PubMed
description BACKGROUND: Newcastle disease (ND) outbreaks are global challenges to the poultry industry. Effective management requires rapid identification and virulence prediction of the circulating Newcastle disease viruses (NDV), the causative agent of ND. However, these diagnostics are hindered by the genetic diversity and rapid evolution of NDVs. METHODS: An amplicon sequencing (AmpSeq) workflow for virulence and genotype prediction of NDV samples using a third-generation, real-time DNA sequencing platform is described here. 1D MinION sequencing of barcoded NDV amplicons was performed using 33 egg-grown isolates, (15 NDV genotypes), and 15 clinical swab samples collected from field outbreaks. Assembly-based data analysis was performed in a customized, Galaxy-based AmpSeq workflow. MinION-based results were compared to previously published sequences and to sequences obtained using a previously published Illumina MiSeq workflow. RESULTS: For all egg-grown isolates, NDV was detected and virulence and genotype were accurately predicted. For clinical samples, NDV was detected in ten of eleven NDV samples. Six of the clinical samples contained two mixed genotypes as determined by MiSeq, of which the MinION method detected both genotypes in four samples. Additionally, testing a dilution series of one NDV isolate resulted in NDV detection in a dilution as low as 10(1) 50% egg infectious dose per milliliter. This was accomplished in as little as 7 min of sequencing time, with a 98.37% sequence identity compared to the expected consensus obtained by MiSeq. CONCLUSION: The depth of sequencing, fast sequencing capabilities, accuracy of the consensus sequences, and the low cost of multiplexing allowed for effective virulence prediction and genotype identification of NDVs currently circulating worldwide. The sensitivity of this protocol was preliminary tested using only one genotype. After more extensive evaluation of the sensitivity and specificity, this protocol will likely be applicable to the detection and characterization of NDV. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12985-018-1077-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-62511112018-11-26 Rapid virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing Butt, Salman L. Taylor, Tonya L. Volkening, Jeremy D. Dimitrov, Kiril M. Williams-Coplin, Dawn Lahmers, Kevin K. Miller, Patti J. Rana, Asif M. Suarez, David L. Afonso, Claudio L. Stanton, James B. Virol J Research BACKGROUND: Newcastle disease (ND) outbreaks are global challenges to the poultry industry. Effective management requires rapid identification and virulence prediction of the circulating Newcastle disease viruses (NDV), the causative agent of ND. However, these diagnostics are hindered by the genetic diversity and rapid evolution of NDVs. METHODS: An amplicon sequencing (AmpSeq) workflow for virulence and genotype prediction of NDV samples using a third-generation, real-time DNA sequencing platform is described here. 1D MinION sequencing of barcoded NDV amplicons was performed using 33 egg-grown isolates, (15 NDV genotypes), and 15 clinical swab samples collected from field outbreaks. Assembly-based data analysis was performed in a customized, Galaxy-based AmpSeq workflow. MinION-based results were compared to previously published sequences and to sequences obtained using a previously published Illumina MiSeq workflow. RESULTS: For all egg-grown isolates, NDV was detected and virulence and genotype were accurately predicted. For clinical samples, NDV was detected in ten of eleven NDV samples. Six of the clinical samples contained two mixed genotypes as determined by MiSeq, of which the MinION method detected both genotypes in four samples. Additionally, testing a dilution series of one NDV isolate resulted in NDV detection in a dilution as low as 10(1) 50% egg infectious dose per milliliter. This was accomplished in as little as 7 min of sequencing time, with a 98.37% sequence identity compared to the expected consensus obtained by MiSeq. CONCLUSION: The depth of sequencing, fast sequencing capabilities, accuracy of the consensus sequences, and the low cost of multiplexing allowed for effective virulence prediction and genotype identification of NDVs currently circulating worldwide. The sensitivity of this protocol was preliminary tested using only one genotype. After more extensive evaluation of the sensitivity and specificity, this protocol will likely be applicable to the detection and characterization of NDV. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12985-018-1077-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-11-22 /pmc/articles/PMC6251111/ /pubmed/30466441 http://dx.doi.org/10.1186/s12985-018-1077-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Butt, Salman L.
Taylor, Tonya L.
Volkening, Jeremy D.
Dimitrov, Kiril M.
Williams-Coplin, Dawn
Lahmers, Kevin K.
Miller, Patti J.
Rana, Asif M.
Suarez, David L.
Afonso, Claudio L.
Stanton, James B.
Rapid virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing
title Rapid virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing
title_full Rapid virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing
title_fullStr Rapid virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing
title_full_unstemmed Rapid virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing
title_short Rapid virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing
title_sort rapid virulence prediction and identification of newcastle disease virus genotypes using third-generation sequencing
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6251111/
https://www.ncbi.nlm.nih.gov/pubmed/30466441
http://dx.doi.org/10.1186/s12985-018-1077-5
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