Hemagglutinin Quantitative ELISA-based Potency Assay for Trivalent Seasonal Influenza Vaccine Using Group-Specific Universal Monoclonal Antibodies

Wonil Chae, Paul Kim, Hanna Kim, Yu Cheol Cheong, Young Seok Kim, Sang Moo Kang, Baik L. Seong

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1 Citation (Scopus)

Abstract

The assurance of vaccine potency is important for the timely release and distribution of influenza vaccines. As an alternative to Single Radial Immunodiffusion (SRID), we report a new quantitative enzyme-linked immunosorbent assay (ELISA) for seasonal trivalent influenza vaccine (TIV). The consensus hemagglutinin (cHA) stalks for group 1 influenza A virus (IAV), group 2 IAV, and influenza B virus (IBV) were designed and produced in bacterial recombinant host in a soluble form, and monoclonal antibodies (mAbs) were generated. The group-specific ‘universal’ mAbs (uAbs) bound to various subtypes of HAs in the same group from recombinant hosts, embryonated eggs, and commercial vaccine lots. The calibration curves were generated to assess the sensitivity, specificity, accuracy, and linear dynamic range. The quantitative ELISA was validated for the potency assay of individual components of TIV- H1, H3, and IBV- with good correlation with the SRID method. This new assay could be extended to pandemic or pre-pandemic mock-up vaccines of H5 of group 1 and H7 virus of group 2, and novel HA stalk-based universal vaccines.

Original languageEnglish
Article number19675
JournalScientific reports
Volume9
Issue number1
DOIs
Publication statusPublished - 2019 Dec 1

Bibliographical note

Funding Information:
This study was supported by grants from the Ministry of Food and Drug Safety of the Republic of Korea (16172MFDS199 and 18172MFDS252) and National Research Foundation of Korea (NRF) funded by the Korea government (Ministry of Science and ICT) (NRF-2018M3A9H4079358). We thank Dr. Dong-wook Kim (Department of Statistics, Sungkyunkwan University, Seoul, South Korea) for statistical analyses of data.

Publisher Copyright:
© 2019, The Author(s).

All Science Journal Classification (ASJC) codes

  • General

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