Rapid virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing
| Autor: | Kevin K. Lahmers, Patti J. Miller, David L. Suarez, Tonya L. Taylor, James B. Stanton, Asif M. Rana, Salman Latif Butt, Claudio L. Afonso, Kiril M. Dimitrov, Jeremy D. Volkening, Dawn Williams-Coplin |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
animal structures Genotype Nanopore sequencing Newcastle Disease 030106 microbiology Newcastle disease virus Virulence MinION Genome Viral Newcastle disease Sensitivity and Specificity DNA sequencing Poultry lcsh:Infectious and parasitic diseases 03 medical and health sciences Nanopores Virology Animals DNA Barcoding Taxonomic lcsh:RC109-216 Phylogeny Poultry Diseases biology Research Outbreak Genetic Variation High-Throughput Nucleotide Sequencing Amplicon biology.organism_classification Data Accuracy Rapid sequencing 030104 developmental biology Infectious Diseases Minion NGS embryonic structures RNA Viral RNA |
| Zdroj: | Virology Journal, Vol 15, Iss 1, Pp 1-14 (2018) Virology Journal |
| DOI: | 10.1186/s12985-018-1077-5 |
| Popis: | 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 101 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. |
| Databáze: | OpenAIRE |
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