ABSTRACT
Effective vaccines are an important public health tool which may be needed to combat the emerging, highly pathogenic H5N1 avian influenza viruses currently circulating in cattle and poultry in the United States. While nucleic acid-based vaccines such as mRNA-lipid nanoparticles (LNPs) have several potential advantages during a viral epidemic compared to traditional seasonal influenza vaccines, their utility and efficacy against H5N1 viruses remain incompletely defined. Here, we developed novel DNA- and mRNA-LNP-based vaccines encoding both hemagglutinin (HA) and neuraminidase (NA) proteins from the human-isolated highly pathogenic avian influenza H5N1 strain, A/Texas/37/2024, in a single open reading frame. This dual-antigen expression approach elicited strong protective immune responses targeting both the HA and NA proteins and provided complete protection against lethal viral challenges in a murine model. The pre-clinical data described in this work suggest that these multi-valent, adaptable, and scalable vaccine approaches may represent practical and rapid solutions to mediate robust protection from emerging zoonotic influenza virus threats.
IMPORTANCE
Vaccines capable of protecting from infection with the H5N1 influenza viruses actively circulating in dairy cattle could be deployed to protect livestock and potentially also be used to protect human health. Here, we describe the development of protective DNA and mRNA-lipid nanoparticle vaccines targeting hemagglutinin and neuraminidase proteins from the highly pathogenic avian influenza (HPAI) H5N1 A/Texas/37/2024 virus and show that they are both protective against severe morbidity and mortality in a mouse model. Thus, the vaccines described in this work represent effective approaches to limit the current circulation of H5N1 viruses in animals and may represent practical solutions for human vaccination in the event of sustained human transmission of HPAI H5N1 viruses.
Source: Journal of Virology, https://journals.asm.org/doi/full/10.1128/jvi.00795-25?af=R
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