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DOI 10.1093/infdis/jiy606

Медицинская библиотека · The Journal of infectious diseases · 2019

Highly Sensitive and Specific Zika Virus Serological Assays Using a Magnetic Modulation Biosensing System.

Michelson Yehudit, Lustig Yaniv, Avivi Shira, Schwartz Eli, Danielli Amos

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

BACKGROUND

Zika virus has created global alarm because it has been associated with catastrophic fetal abnormalities, including microcephaly, spontaneous abortion, and intrauterine growth restriction. Current serological assays that detect antiviral antibodies suffer from low sensitivity and high cross-reactivity among different flaviviruses.

METHODS

In this study, utilizing a novel magnetic modulation biosensing (MMB) system and the Zika nonstructural 1 protein, we show highly sensitive and specific Zika serological assays. We blindly tested 60 reverse-transcription polymerase chain reaction Zika-positive samples and healthy patients' serum samples, as well as 44 serum samples from enzyme-linked immunosorbent assay (ELISA) West Nile- and dengue-positive patients. The Zika-positive samples were collected from Israeli travelers returning from Zika-endemic areas.

RESULTS

The MMB Zika assays have 88%-97% sensitivity, much higher than the current state-of-the-art EUROIMMUN ELISA assays (38%-74%). In addition, the specificity is 100%, and the cross-reactivity with West Nile and dengue viruses is minimal (0%-4%). Furthermore, the MMB assays detected Zika IgM antibodies as early as 5 days and as late as 180 days postsymptoms onset, significantly extending the number of days that the antibodies are detectable.

CONCLUSIONS

The sensitivity, specificity, and simplicity of the MMB assays may significantly improve Zika diagnosis and provide accurate results for public health agencies.

Для цитирования: Michelson Yehudit, Lustig Yaniv, Avivi Shira, Schwartz Eli, Danielli Amos. Highly Sensitive and Specific Zika Virus Serological Assays Using a Magnetic Modulation Biosensing System.. The Journal of infectious diseases. 2019. DOI: 10.1093/infdis/jiy606.

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