BACKGROUND: Avian paramyxoviruses (APMVs), also termed avian avulaviruses, are of a vast diversity and great significance in poultry. Detection of all known APMVs is challenging, and distribution of APMVs have not been well investigated. METHODS: A set of reverse transcription polymerase chain reaction (RT-PCR) assays for detection of all known APMVs were established using degenerate primers targeting the viral polymerase L gene. The assays were preliminarily evaluated using in-vitro transcribed double-stranded RNA controls and 24 known viruses, and then they were employed to detect 4,346 avian samples collected from 11 provinces. RESULTS: The assays could detect 20-200 copies of the double-stranded RNA controls, and detected correctly the 24 known viruses. Of the 4,346 avian samples detected using the assays, 72 samples were found positive. Of the 72 positives, 70 were confirmed through sequencing, indicating the assays were specific for APMVs. The 4,346 samples were also detected using a reported RT-PCR assay, and the results showed this RT-PCR assay was less sensitive than the assays reported here. Of the 70 confirmed positives, 40 were class I Newcastle disease virus (NDV or APMV-1) and 27 were class II NDV from poultry including chickens, ducks, geese, and pigeons, and three were APMV-2 from parrots. The surveillance identified APMV-2 in parrots for the first time, and revealed that prevalence of NDVs in live poultry markets was higher than that in poultry farms. The surveillance also suggested that class I NDVs in chickens could be as prevalent as in ducks, and class II NDVs in ducks could be more prevalent than in chickens, and class II NDVs could be more prevalent than class I NDVs in ducks. Altogether, we developed a set of specific and sensitive RT-PCR assays for detection of all known APMVs, and conducted a large-scale surveillance using the assays which shed novel insights into APMV epidemiology.
BACKGROUND: Avian paramyxoviruses (APMVs), also termed avian avulaviruses, are of a vast diversity and great significance in poultry. Detection of all known APMVs is challenging, and distribution of APMVs have not been well investigated. METHODS: A set of reverse transcription polymerase chain reaction (RT-PCR) assays for detection of all known APMVs were established using degenerate primers targeting the viral polymerase L gene. The assays were preliminarily evaluated using in-vitro transcribed double-stranded RNA controls and 24 known viruses, and then they were employed to detect 4,346 avian samples collected from 11 provinces. RESULTS: The assays could detect 20-200 copies of the double-stranded RNA controls, and detected correctly the 24 known viruses. Of the 4,346 avian samples detected using the assays, 72 samples were found positive. Of the 72 positives, 70 were confirmed through sequencing, indicating the assays were specific for APMVs. The 4,346 samples were also detected using a reported RT-PCR assay, and the results showed this RT-PCR assay was less sensitive than the assays reported here. Of the 70 confirmed positives, 40 were class I Newcastle disease virus (NDV or APMV-1) and 27 were class II NDV from poultry including chickens, ducks, geese, and pigeons, and three were APMV-2 from parrots. The surveillance identified APMV-2 in parrots for the first time, and revealed that prevalence of NDVs in live poultry markets was higher than that in poultry farms. The surveillance also suggested that class I NDVs in chickens could be as prevalent as in ducks, and class II NDVs in ducks could be more prevalent than in chickens, and class II NDVs could be more prevalent than class I NDVs in ducks. Altogether, we developed a set of specific and sensitive RT-PCR assays for detection of all known APMVs, and conducted a large-scale surveillance using the assays which shed novel insights into APMV epidemiology.
Authors: Suxiang Tong; Shur-Wern Wang Chern; Yan Li; Mark A Pallansch; Larry J Anderson Journal: J Clin Microbiol Date: 2008-06-25 Impact factor: 5.948
Authors: Andrew M Ramey; Andrew B Reeves; Haruko Ogawa; Hon S Ip; Kunitoshi Imai; Vuong Nghia Bui; Emi Yamaguchi; Nikita Y Silko; Claudio L Afonso Journal: Arch Virol Date: 2013-06-27 Impact factor: 2.574
Authors: Luciano Matsumiya Thomazelli; Jansen de Araújo; Thomas Fabrizio; David Walker; Dilmara Reischak; Tatiana Ometto; Carla Meneguin Barbosa; Maria Virginia Petry; Richard J Webby; Edison Luiz Durigon Journal: PLoS One Date: 2017-05-09 Impact factor: 3.240
Authors: Kiril M Dimitrov; Celia Abolnik; Claudio L Afonso; Emmanuel Albina; Justin Bahl; Mikael Berg; Francois-Xavier Briand; Ian H Brown; Kang-Seuk Choi; Ilya Chvala; Diego G Diel; Peter A Durr; Helena L Ferreira; Alice Fusaro; Patricia Gil; Gabriela V Goujgoulova; Christian Grund; Joseph T Hicks; Tony M Joannis; Mia Kim Torchetti; Sergey Kolosov; Bénédicte Lambrecht; Nicola S Lewis; Haijin Liu; Hualei Liu; Sam McCullough; Patti J Miller; Isabella Monne; Claude P Muller; Muhammad Munir; Dilmara Reischak; Mahmoud Sabra; Siba K Samal; Renata Servan de Almeida; Ismaila Shittu; Chantal J Snoeck; David L Suarez; Steven Van Borm; Zhiliang Wang; Frank Y K Wong Journal: Infect Genet Evol Date: 2019-06-11 Impact factor: 3.342