Development of a broad-spectrum nasal live attenuated influenza vaccine based on mosaic antigen design against influenza B viruses

<b>ABSTRACT</b>Influenza B virus (IBV) causes significant seasonal disease burden, and frequent antigenic drift limits the effectiveness of conventional vaccines. To address this, we designed mosaic haemagglutinin (HA) and neuraminidase (NA) antigens to maximize T-cell epitope coverage and incorporated them into a nasal live attenuated influenza vaccine (LAIV) platform. Using B/Victoria lineage sequences (2009-2021), mosaic HA/NA candidates were generated via an iterative genetic algorithm. BALB/c mice were randomized into PBS, conventional inactivated influenza vaccine (IIV), conventional LAIV, and mosaic-LAIV (MoBV) groups, and immunized intranasally on days 0 and 14. Immune responses were evaluated by haemagglutination inhibition (HAI), microneutralization (MN), neuraminidase inhibition (NAI), mucosal IgA by ELISA, and T-cell profiling by flow cytometry. Protective efficacy was assessed by challenge with multiple IBV strains. MoBV-induced higher cross-reactive antibody responses (HAI, MN, NAI) and markedly increased mucosal IgA, which persisted for 100 days, alongside enhanced T-cell responses. Upon challenge, MoBV improved survival to 25-100% compared with controls. These results demonstrate that MoBV elicits broad systemic and mucosal immunity, providing robust cross-lineage protection against diverse IBV strains and supporting the development of a universal influenza B vaccine.

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Publication Details

Journal
Emerging Microbes & Infections
Published
2025-10-16
DOI
https://doi.org/10.1080/22221751.2025.2576141
Citations
1
Primary Topic
Influenza Virus Research Studies
Type
article
Field-Weighted Citation Impact
1.35
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Development of a broad-spectrum nasal live attenuated influenza vaccine based on mosaic antigen design against influenza B viruses

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article

Development of a broad-spectrum nasal live attenuated influenza vaccine based on mosaic antigen design against influenza B viruses

Wenfei Zhu, Yuhang Shi, Qi Chen, Lin Zhu, Tian Bai, Xuejie Liu, Yuhang Zhang, Hongwei Chen, Xue Han, Chen Chen, Ximeng Ma, Zhuolin Yang, Rui Ma, Jian Lü, Lifang Yuan, Tianyi Zhao, Yuelong Shu, Wantong Pang
article en
1 citations

Abstract

<b>ABSTRACT</b>Influenza B virus (IBV) causes significant seasonal disease burden, and frequent antigenic drift limits the effectiveness of conventional vaccines. To address this, we designed mosaic haemagglutinin (HA) and neuraminidase (NA) antigens to maximize T-cell epitope coverage and incorporated them into a nasal live attenuated influenza vaccine (LAIV) platform. Using B/Victoria lineage sequences (2009-2021), mosaic HA/NA candidates were generated via an iterative genetic algorithm. BALB/c mice were randomized into PBS, conventional inactivated influenza vaccine (IIV), conventional LAIV, and mosaic-LAIV (MoBV) groups, and immunized intranasally on days 0 and 14. Immune responses were evaluated by haemagglutination inhibition (HAI), microneutralization (MN), neuraminidase inhibition (NAI), mucosal IgA by ELISA, and T-cell profiling by flow cytometry. Protective efficacy was assessed by challenge with multiple IBV strains. MoBV-induced higher cross-reactive antibody responses (HAI, MN, NAI) and markedly increased mucosal IgA, which persisted for 100 days, alongside enhanced T-cell responses. Upon challenge, MoBV improved survival to 25-100% compared with controls. These results demonstrate that MoBV elicits broad systemic and mucosal immunity, providing robust cross-lineage protection against diverse IBV strains and supporting the development of a universal influenza B vaccine.

Emerging Microbes & InfectionsVol. 14(1)
Chinese Center For Disease Control and Prevention (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), National Institute for Viral Disease Control and Prevention (CN), Shenzhen University Health Science Center (CN), National Institute for Communicable Disease Control and Prevention (CN)
Openalex Percentile: Top 15%
Influenza Virus Research Studies
1.35
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