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DOI 10.1016/j.jviromet.2017.11.005

Медицинская библиотека · Journal of virological methods · 2017

Development and application of a triplex real-time PCR assay for the simultaneous detection of avian influenza virus subtype H5, H7 and H9.

Liu Junli, Yao Lu, Zhai Feifei, Chen Yuqing, Lei Jing, Bi Zhenwei, Hu Jianhua, Xiao Qian, Song Suquan, Yan Liping, Zhou Jiyong

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Avian influenza virus (AIV), especially subtypes H5, H7 and H9, has contributed to enormous economic losses and poses a potential pandemic threat to global human public health. Early screening of suspected cases is key to controlling the spread of AIVs. In this study, an accurate, rapid, and triplex real-time polymerase chain reaction (PCR) assay was developed for the simultaneous detection of AIV subtypes H5, H7 and H9. The sensitivity of the real-time PCR was at least 100 times higher than that of the conventional PCR, with a detection limit of 50 copies and an EID50 of 1 (50% egg infections dose) for the H5, H7, and H9 subtypes. The lack of cross-reaction with other avian respiratory viruses suggested that the real-time PCR assay was highly specific. The reproducibility of the assay was confirmed using plasmids containing targets genes. Furthermore, 362 clinical field samples were evaluated. Subtypes H5, H7 and H9 were detected in 102 (28.18%) samples by real-time PCR and in 35 (9.67%) samples by conventional virus isolation. These results indicate that the triplex real-time PCR assay has good sensitivity, specificity and reproducibility and that it might be useful for laboratory surveillance and rapid diagnosis of the H5, H7 and H9 subtypes of influenza A viruses.

Для цитирования: Liu Junli, Yao Lu, Zhai Feifei, Chen Yuqing, Lei Jing, Bi Zhenwei, Hu Jianhua, Xiao Qian, Song Suquan, Yan Liping, Zhou Jiyong. Development and application of a triplex real-time PCR assay for the simultaneous detection of avian influenza virus subtype H5, H7 and H9.. Journal of virological methods. 2017. DOI: 10.1016/j.jviromet.2017.11.005.

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