Clinical & Translational Immunology · 2019 · 26 citations · 48 references
Life SciencesImmunologyInfectious DiseasesImmunology Of Infectious DiseasesMolecular VirologyVirologyAntiviral ImmunityArboviral DiseasesDiagnostic ImmunologyViral DiagnosticsViral InfectionsViral PathogenesisB-cell EpitopesCross-reactive AntigensCross-reactive ImmunityLinear EpitopesNeutralizing Antibody ResponsesViral Antigen DetectionViral Antigen RecognitionViral Disease Diagnosis
OBJECTIVES: Recent Zika virus (ZIKV) outbreaks challenged existing laboratory diagnostic standards, especially for serology-based methods. Because of the genetic and structural similarity of ZIKV with other flaviviruses, this results in cross-reactive antibodies, which confounds serological interpretations. METHODS: Plasma from Singapore ZIKV patients was screened longitudinally for antibody responses and neutralising capacities against ZIKV. Samples from healthy controls, ZIKV patients and DENV patients were further assessed using ZIKV and DENV peptides of precursor membrane (prM), envelope (E) or non-structural 1 (NS1) viral proteins in a peptide-based ELISA for epitope identification. Identified epitopes were re-validated and diagnostically evaluated using sera of patients with DENV, bacteria or unknown infections from Thailand. RESULTS: Long-lasting ZIKV-neutralising antibodies were elicited during ZIKV infection. Thirteen potential linear B-cell epitopes were identified, and of these, four common flavivirus, three ZIKV-specific and one DENV-specific differential epitopes had more than 50% sensitivity and specificity. Notably, ZIKV-specific peptide 26 on domain I/II of E protein (amino acid residues 271-288) presented 80% sensitivity and 85.7% specificity. Importantly, the differential epitopes also showed significance in differentiating non-flavivirus patient samples. CONCLUSION: Linear B-cell epitope candidates to differentiate between ZIKV and DENV infections were identified, providing the first step towards the design of a much-needed serology-based assay.
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