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Bioinformatics analysis and immunogenicity assessment of the novel multi-stage DNA vaccine W541 against Mycobacterium tuberculosis
Open accessPreprint — published as 10.1002/iid3.70074 · Paper page
Abstract
Background: Vaccination is one of the effective measures to prevent latent tuberculosis infection (LTBI) from developing into active tuberculosis (TB). Applying bioinformatics methods to pre-evaluate the biological characteristics and immunogenicity of vaccines can improve the efficiency of vaccine development. Objectives: To evaluate the immunogenicity of tuberculosis vaccine W541 and explore the application of bioinformatics technology in tuberculosis vaccine research. Methods: This study concatenated the immunodominant sequences of Ag85A, Ag85B, Rv3407, and Rv1733c to construct the W541 DNA vaccine. Then, bioinformatics methods were used to analyze the physicochemical properties, antigenicity, allergenicity, toxicity, and population coverage of the vaccine, identify its epitopes, and perform molecular docking with MHC alleles and Toll-like receptor 4 (TLR4) of the host. Finally, the immunogenicity of the vaccine was evaluated through animal experiments. Results: the W541 vaccine protein is a soluble cytoplasmic protein with a half-life of 1.1 hours in vivo and an instability index of 45.37. It has good antigenicity and wide population coverage without allergenicity and toxicity. It contains 138 HTL epitopes, 73 CTL epitopes, 8 linear and 14 discontinuous epitopes of B cells, and a strong affinity for TLR4. Immune simulations showed it could effectively stimulate innate and adaptive immune responses. Animal experiments have confirmed that the W541 DNA vaccine could effectively activate the Th1- and Th17-type immune responses, producing high levels of IFN-γ and IL-17A, but could not significantly increase antibody levels. Conclusion: the W541 DNA vaccine can induce strong cellular immune responses. However, further optimization of the vaccine design is needed to make the expressed protein more stable in vivo. Bioinformatics analysis could reveal vaccines’ physicochemical and immunological information, which is critical for guiding vaccine design and development.
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Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
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Metadata
- Authors
- Yang, Y., Liang, Y., Xue, Y., Wang, X., Wang, L., Wang, J., Zhang, J., & Wu, X.
- Affiliations
- Chinese PLA General Hospital (CN)
- Corresponding author
- Liang, Yan
- Wu, Xueqiong
- Venue
- Immunity Inflammation and Disease
- Publisher
- Wiley
- Published
- 2024-04-25
- Volume
- 12
- Issue
- 11
- Pages
- e70074-e70074
- ISSN
- 2050-4527 (ISSN-L)
- PMC
- PMC11590035
- OpenAlex
- W4404717200
- Cited by
- 3
- References
- 1
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1
- FWCI
- 0.41
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Immunity Inflammation and Disease (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- General Hospital of People’s Liberation Army
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Health Sciences › Medicine › Infectious Diseases › Tuberculosis Research and Epidemiology
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Keywords
- tuberculosis vaccine, DNA vaccine, Mycobacterium tuberculosis, Ag85A, Ag85B, immunogenicity, epitope prediction, B-cell epitopes, CTL epitopes, TLR4, MHC binding, Th1/Th17 response, latent tuberculosis infection, vaccine design
- MeSH terms
- Immunogenicity, Vaccine, Animals, Antigens, Bacterial, Female, Humans, Mycobacterium tuberculosis, Tuberculosis, Epitopes, T-Lymphocyte, Epitopes, B-Lymphocyte, Computational Biology, Vaccines, DNA, Tuberculosis Vaccines, Mice, Molecular Docking Simulation
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