ZIKV-Specific NS1 Epitopes as Serological Markers of Acute Zika Virus Infection

寨卡病毒 病毒学 血清学 表位 病毒 免疫学 生物 医学 抗体
作者
Yiu‐Wing Kam,Juliana Almeida Leite,Siti Naqiah Amrun,Fok‐Moon Lum,Wearn‐Xin Yee,Farhana Abu Bakar,Kai Er Eng,David Chien Lye,Yee‐Sin Leo,Chia-Yin Chong,André Ricardo Ribas Freitas,Guilherme Paier Milanez,José Luiz Proença‐Módena,Laurent Rénia,Fábio Trindade Maranhão Costa,Lisa F. P. Ng,Zika-Unicamp Network,Eliana Amaral,Renato Passini,Helaine Maria Besteti Pires Mayer-Milanez
出处
期刊:The Journal of Infectious Diseases [Oxford University Press]
卷期号:220 (2): 203-212 被引量:23
标识
DOI:10.1093/infdis/jiz092
摘要

BACKGROUND: Zika virus (ZIKV) infections have reemerged as a global health issue due to serious clinical complications. Development of specific serological assays to detect and differentiate ZIKV from other cocirculating flaviviruses for accurate diagnosis remains a challenge. METHODS: We investigated antibody responses in 51 acute ZIKV-infected adult patients from Campinas, Brazil, including 7 pregnant women who later delivered during the study. Using enzyme-linked immunosorbent assays, levels of antibody response were measured and specific epitopes identified. RESULTS: Several antibody-binding hot spots were identified in ZIKV immunogenic antigens, including membrane, envelope (E) and nonstructural protein 1 (NS1). Interestingly, specific epitopes (2 from E and 2 from NS1) strongly recognized by ZIKV-infected patients' antibodies were identified and were not cross-recognized by dengue virus (DENV)-infected patients' antibodies. Corresponding DENV peptides were not strongly recognized by ZIKV-infected patients' antibodies. Notably, ZIKV-infected pregnant women had specific epitope recognition for ZIKV NS1 (amino acid residues 17-34), which could be a potential serological marker for early ZIKV detection. CONCLUSIONS: This study identified 6 linear ZIKV-specific epitopes for early detection of ZIKV infections. We observed differential epitope recognition between ZIKV-infected and DENV-infected patients. This information will be useful for developing diagnostic methods that differentiate between closely related flaviviruses.
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