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A Novel Synthetic Receptor-Based Immunoassay for Influenza Vaccine Quantification

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Figshare2016-01-18 更新2026-04-29 收录
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https://figshare.com/articles/dataset/A_Novel_Synthetic_Receptor_Based_Immunoassay_for_Influenza_Vaccine_Quantification__/156547
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Vaccination is the most effective prophylactic method for preventing influenza. Quantification of influenza vaccine antigens is critically important before the vaccine is used for human immunization. Currently the vaccine antigen quantification relies on hemagglutinin content quantification, the key antigenic component, by single radial immunodiffusion (SRID) assay. Due to the inherent disadvantages associated with the traditional SRID; i.e. low sensitivity, low throughput and need for annual reagents, several approaches have been proposed and investigated as alternatives. Yet, most alternative methods cannot distinguish native hemagglutinin from denatured form, making them less relevant to antigenic analyses. Here, we developed a quantitative immunoassay based on the sialic acid binding property of influenza vaccine antigens. Specifically, we chemically synthesized human and avian influenza virus receptors analogues, N-acetylneuraminic acid-2,6-lactose and N-acetylneuraminic acid-2,3-lactose derivatives with an azidopropyl aglycon, using α-2,6- and α-2,3-sialyltransferases, respectively. The azido group of the two sialyllactose-derivatives was reduced and conjugated to mouse serum albumin through a squarate linkage. We showed that the synthetic α-2,6- and α-2,3-receptors selectively bound to human and avian-derived hemagglutinins, respectively, forming the basis of a new, and robust assay for hemagglutinin quantification. Hemagglutinin treated at high temperature or low pH was measured differentially to untreated samples suggesting native conformation is dependent for optimal binding. Importantly, this receptor-based immunoassay showed excellent specificity and reproducibility, high precision, less turnaround time and significantly higher sensitivity and throughput compared with SRID in analyzing multiple influenza vaccines.
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2016-01-18
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