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DOI 10.1016/j.jviromet.2015.01.007

Медицинская библиотека · Journal of virological methods · 2015

HA1-specific indirect ELISA for serological detection of canine influenza virus H3N2 infection in dogs.

Shim Doo Hee, Kim Jeong-Ki, Hong Minki, Na Woonsung, Park Yong-A, Park Seong Jun, Song Daesub, Lee Jae Myun, Kim Hye Kwon

Сравнительное исследованиеОценочное исследованиеСтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

An indirect ELISA using recombinant HA1 protein of canine influenza virus (CIV) as a coating antigen was developed and characterized for its application to serosurveillance in dogs. The CIV H3N2-specific indirect ELISA was developed using recombinant HA1 protein (baculovirus-expression system) as a coating antigen. A total of 65 CIV H3N2-positive or negative canine sera were tested by the indirect ELISA for receiver operating characteristic (ROC) analysis and results compared to those generated by the hemagglutination inhibition (HI) test. Canine sera collected 10 days following intranasal inoculation with canine H3N2, seasonal H3N2 (A/Brisbane/10/2007) or pandemic H1N1 influenza virus (A/California/04/2009) were used for the cross-reaction test. An adjusted optical density (OD) of 0.17 was determined to be the optimal cut-off value for seropositivity. The indirect ELISA showed 95.7% sensitivity and 94.7% specificity when compared to the HI test. A cross-reaction test was also performed using canine sera reactive with CIV H3N2, seasonal H3N2 (human) and pandemic H1N1 (human) influenza viruses. Based on the data generated in this study, the canine H3N2-associated ELISA using baculovirus expressed HA1 antigen will be useful for herd-based serological survey of the canine H3N2 virus infection in dogs.

Для цитирования: Shim Doo Hee, Kim Jeong-Ki, Hong Minki, Na Woonsung, Park Yong-A, Park Seong Jun, Song Daesub, Lee Jae Myun, Kim Hye Kwon. HA1-specific indirect ELISA for serological detection of canine influenza virus H3N2 infection in dogs.. Journal of virological methods. 2015. DOI: 10.1016/j.jviromet.2015.01.007.

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