Making Use of Immunoinformatics to Develop mRNA Vaccines against Influenza D Virus

Yunio Geclia^*
*Correspondence: Yunio Geclia, Department of Molecular Biology, Immunology and Bioinformatics, Adeleke University, Ede 232104, Osun State, Nigeria, Email:

Introduction

Influenza D Virus (IDV) is a relatively newly discovered member of the Orthomyxoviridae family, distinct from the more commonly known influenza A, B, and C viruses. Discovered in 2011, IDV primarily infects cattle and swine, though human cases have been reported. Its zoonotic potential raises concerns about future outbreaks and the need for effective vaccination strategies. Traditional vaccine development methods face challenges due to the virus's genetic diversity and rapid evolution. Immunoinformatics, a field combining immunology and bioinformatics, offers a promising approach to overcome these challenges by facilitating the design of mRNA vaccines tailored to combat IDV [1].

Description

Influenza D virus was first identified in swine in the United States and subsequently in cattle, indicating a broad host range. Unlike influenza A, B, and C viruses, IDV belongs to the genus Deltainfluenzavirus within the Orthomyxoviridae family. Its segmented RNA genome and unique surface glycoproteins contribute to its distinct antigenic profile, complicating vaccine development. Traditional vaccine development methods for influenza viruses rely on inactivated or attenuated viruses, recombinant proteins, or virus-like particles [2]. However, IDV's genetic diversity and reassortment capabilities complicate the effectiveness of these approaches. Moreover, the rapid evolution of IDV strains necessitates constant surveillance and updates to vaccine formulations, highlighting the need for a more adaptable approach. Immunoinformatics integrates computational tools with immunological principles to accelerate vaccine design. Epitope prediction identifying antigenic epitopes that stimulate immune responses. Molecular docking analyzing interactions between antigens and immune receptors to optimize vaccine efficacy. Sequence analysis comparing genetic sequences to identify conserved regions for vaccine targets. mRNA vaccines represent a revolutionary advancement in vaccine technology, offering advantages such as rapid development, scalability, and safety. They encode antigenic proteins, harnessing the body's cellular machinery to induce immune responses. Immunoinformatics enables the precise design of mRNA sequences to enhance antigen expression and immunogenicity [3].

mRNA vaccines represent a revolutionary advancement in vaccine technology, offering advantages such as rapid development, scalability, and safety. They encode antigenic proteins, harnessing the body's cellular machinery to induce immune responses. Immunoinformatics enables the precise design of mRNA sequences to enhance antigen expression and immunogenicity [4]. Researchers synthesized mRNA encoding IDV hemagglutinin-esterase protein and tested its immunogenicity in animal models. Immunoinformatics-guided modifications enhanced protein expression and induced robust antibody responses, demonstrating the vaccine's efficacy. Using epitope prediction tools, scientists designed a multi-epitope mRNA vaccine targeting multiple IDV proteins. In silico analysis predicted strong antigenicity and MHC binding affinity, prompting further preclinical studies to evaluate vaccine efficacy and safety. Regulatory approval for mRNA vaccines requires comprehensive safety and efficacy data, necessitating rigorous preclinical and clinical trials. IDV's antigenic diversity necessitates ongoing surveillance and periodic vaccine updates to maintain effectiveness. Optimizing mRNA vaccine delivery systems and storage conditions ensures stability and potency, particularly in resource-limited settings [5].

Conclusion

Immunoinformatics-driven mRNA vaccines offer a promising strategy to combat Influenza D virus by overcoming traditional vaccine development challenges. By leveraging computational tools to design precise antigenic targets and optimize mRNA sequences, researchers can accelerate vaccine development and enhance immune responses. Future efforts should focus on refining bioinformatics algorithms, conducting robust preclinical evaluations, and navigating regulatory pathways to translate these advancements into effective public health interventions against IDV. In conclusion, the convergence of immunoinformatics and mRNA vaccine technology represents a paradigm shift in infectious disease prevention, offering hope for controlling zoonotic threats like Influenza D virus and improving global health security.

Acknowledgement

None.

Conflict of Interest

None.

References

1. Gray, Gregory C., Emily R. Robie, Caleb J. Studstill and Charles L. Nunn. "Mitigating future respiratory virus pandemics: New threats and approaches to consider." Viruses 13 (2021): 637.

Google Scholar, Crossref, Indexed at

2. Horimoto, Taisuke, Takahiro Hiono, Hirohisa Mekata and Tomoha Odagiri, et al. "Nationwide distribution of bovine influenza D virus infection in Japan." PloS one 11 (2016): e0163828.

Google Scholar, Crossref, Indexed at

3. Leibler, Jessica H., Anfal Abdelgadir, James Seidel and Roberta F. White, et al. "Influenza D virus exposure among US cattle workers: A call for surveillance." Zoonoses and Public Health 70 (2023): 166-170.

Google Scholar, Crossref, Indexed at

4. Schlake, Thomas, Andreas Thess, Mariola Fotin-Mleczek and Karl-Josef Kallen. "Developing mRNA-vaccine technologies." RNA Biology 9 (2012): 1319-1330.

Google Scholar, Crossref, Indexed at

5. Vita, Randi, Swapnil Mahajan, James A. Overton and Sandeep Kumar Dhanda, et al. "The immune epitope database (IEDB): 2018 update." Nucleic Acids Res 47 (2019): D339-D343.

Google Scholar, Crossref