Rapid and sensitive virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing
Salman Latif ButtiD, Tonya L. Taylor, Jeremy D. VolkeningiD, Kiril M. DimitroviD, Dawn Williams-CopliniD, Kevin K. LahmersiD, Patti J. Miller, Asif M. Rana, David L. SuareziD, Claudio L. AfonsoiD, James B. StantoniD
Abstract
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. A highly sensitive amplicon sequencing (AmpSeq) workflow for virulence and genotype prediction of NDV samples using a third-generation, real-time DNA sequencing platform is described using both egg-propagated virus and clinical samples. 1D MinION sequencing of barcoded NDV amplicons was performed on 33 egg-grown isolates, (23 unique lineages, including 15 different NDV genotypes), and from 15 clinical swab samples from field outbreaks. Assembly-based data analysis was performed in a customized, Galaxy-based AmpSeq workflow. For all egg-grown samples, NDV was detected and virulence and genotype were predicted. For clinical samples, NDV was detected in ten of eleven NDV samples. Six of the clinical samples contained two mixed genotypes, of which the MinION method detected both genotypes in four of those samples. Additionally, testing a dilution series of one NDV sample resulted in detection of NDV with a 50% egg infectious dose (EID50) as low as 101 EID50/ml. This was accomplished in as little as 7 minutes of sequencing time, with a 98.37% sequence identity compared to the expected consensus. The high sensitivity, fast sequencing capabilities, accuracy of the consensus sequences, and the low cost of multiplexing allowed for identification of NDV of different genotypes circulating worldwide. This general method will likely be applicable to other infections agents.
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