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Title: Use of bioinformatics in improving detection of Newcastle disease virus

Author
item Kim, L
item Suarez, David
item Afonso, Claudio

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 9/25/2006
Publication Date: 11/28/2006
Citation: Kim, L.M., Suarez, D.L., Afonso, C.L. 2007. Use of bioinformatics in improving detection of Newcastle disease virus. In: Rogeria de Almeida, M., Pires Moraes, M., Patarroyo, J.H., Vidigal, P.M.P., Borem, A., editors. Biotecnologia e Saude Animal. Viscoza, Brazil: Federal University of Viscosa. Chapter 9. p. 227-249.

Interpretive Summary: Not required.

Technical Abstract: Newcastle disease (ND) is a major concern for poultry producers around the world and the rapid diagnosis of an outbreak is crucial to any control program. Prompt detection of the causative agent of ND, virulent forms of avian paramyxovirus serotype-1 (APMV-1) also known as virulent Newcastle disease virus (vNDV), is complicated by the diverse genetic variability found within this serotype. Bioinformatics offers an invaluable tool to not only understand the epidemiology and evolution of APMV-1, but also to develop and improve diagnostic tests. When the United States Department of Agriculture (USDA) validated a real-time reverse transcription-PCR (RRT-PCR) test (Fusion test) directed at the fusion-cleavage site of NDV, the goal was to differentiate virulent Newcastle disease virus strains from those of low virulence. However it was recognized from the beginning that the test might miss some isolates, since at least one virulent isolate (Dove/Italy/2736/2000; DoveIT) escaped detection. Bioinformatics tools such as comparative nucleotide alignment and phylogenic analysis were used to identify how this isolate differed from other detectable isolates, to identify other isolates that may fail detection, and to determine which mismatches allow the virus to escape detection. Phylogenetic analysis located the DoveIT isolate into a subgroup of pigeon-adapted viruses with a fusion-cleavage site motif of “RRKKRF.” In addition, these data identified unique mismatches between DoveIT and the Fusion test probe sequence likely responsible for the failure of the probe to bind. The effect of these specific mismatches was also characterized by testing clones with different permutations of the mismatches present in DoveIT. Here, a specific problem was targeted and addressed by identifying potential locations in the probe-site for improved detection. Similarly, a phylogenetically separated group of typically low virulence viruses (Class I APMV-1) are often missed by the USDA validated matrix-gene RRT-PCR test (Matrix test). Comparative nucleotide analysis of the 24 bp Matrix test probe-site identified significant genomic variability between Class I and II isolates that are likely responsible for the Matrix test missing these wildlife and live bird market isolates. Conserved regions suitable for test development were identified using bioinformatics tools, and a novel RRT-PCR test targeting the polymerase gene to identify Class I viruses is proposed. Preliminary results suggest improved detection of the Class I viruses with the polymerase-gene test over the Matrix test. Bioinformatics analysis is an essential component to the continued improvement and development of molecular diagnostics.