HKU Data Repository
Browse

File(s) under embargo

Supporting data for "Development of Intranasal SARS-CoV-2 Vaccines Based on the Influenza Virus-Vector"

dataset
posted on 2023-08-25, 03:45 authored by Shaofeng DengShaofeng Deng

Immunization has been crucial in mitigating the burden of COVID-19 since the introduction of SARS-CoV-2 vaccines in late 2020. However, the emergence of viral variants has impacted the efficacy of current vaccines, as these variants exhibit significant immune evasion.

Here, novel intranasally administered influenza virus-vectored SARS-CoV-2 vaccine candidates were developed and evaluated in animal models. Levels of neutralizing antibodies in the serum of mice and hamsters were measured by ELISA and a pseudovirus neutralization assay. Additionally, T cell responses were detected by flow. The virus titer in the lung and NT of challenged animals was measured by the TCID50 assay. All of this quantitative data is merged into an Excel table, and all quantitative data figures can be opened with Prism.The data show that these vaccines induced significant protection against both SARS-CoV-2 and influenza virus infection in animal models.

The histopathological analysis of the lung tissues of the challenged animals was performed. All image data (manually produced images), including histopathology of experimental animals, gel/membrane pictures, and immunostaining (IF, IHC) images, is merged into a pdf file.

In conclusion, SARS-CoV-2 vaccines using the DelNS1 influenza virus vector vaccine platform were developed and evaluated. These data indicate that the influenza-based viral vector platform has the potential to be utilized for the development of bivalent vaccines against both influenza and COVID-19 or other respiratory virus infections, including future emerging viruses.

History

Usage metrics

    Research Postgraduates

    Categories

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC