Volume 29, Issue 3 (Iran South Med J 2026)
Iran South Med J 2026, 29(3): 123-139 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Vaez H, Shahrakimojahed L. Design of A Multi-epitope Vaccine Candidate against Q Fever based on the Outer Mem-brane Proteins OMP1 and LolB: An Immunoinformatic Study. Iran South Med J 2026; 29 (3) :123-139
URL: http://ismj.bpums.ac.ir/article-1-2590-en.html
URL: http://ismj.bpums.ac.ir/article-1-2590-en.html
1- Department of Microbiology, School of Medicine, Zabol University of Medical Sciences, Zabol, Iran
Pediatric Gastroenterology and Hepatology Research Center, Zabol University of Medical Sciences, Zabol, Iran ,h_vaez@zbmu.ac.ir
2- Veterinary organization, Sistan and Baluchistan, Zabol, Iran
Pediatric Gastroenterology and Hepatology Research Center, Zabol University of Medical Sciences, Zabol, Iran ,
2- Veterinary organization, Sistan and Baluchistan, Zabol, Iran
Abstract: (309 Views)
Background: Q fever—caused by Coxiella burnetii—is a zoonotic disease reported worldwide. It can cause severe complications in the host, manifesting with conditions such as liver, heart, and vascular failure, pneumonia, and long-term chronic fatigue. Given the significant impact of C. burnetii on public health and the limitations of previously designed vaccines, this study aimed to design a Q fever vaccine based on C. burnetii outer membrane proteins using bioinformatics methods.
Materials and Methods: Epitopes that stimulate B- and T-lymphocytes were identified using the ABCpred and IEDB servers. After evaluating various properties—such as non-toxicity (ToxinPred server), lack of allergenicity (AllerTOP server), and immunogenicity (VaxiJen server)—a recombinant vaccine was designed. The characteristics of the vaccine candidate were evaluated using different servers (ProtParam, Solpro, PSIPRED, Cluspro, and C-ImmSim).
Results: Following comprehensive evaluations, three B-lymphocyte-stimulating epitopes and 17 T-lymphocyte-stimulating epitopes were selected for the OMP1 and LolB proteins, respectively. In addition, 17 and 9 T-lymphocyte-stimulating epitopes were identified for OMP1 and LolB, respectively. Various properties of the designed vaccine candidate, including physicochemical properties, secondary structure, expression levels, non-toxicity, and ability to elicit a positive immune system, were predicted.
Conclusion: Based on the computational findings of this study, the designed vaccine may effectively stimulate the immune system and provide immunity against Q fever. Further in vitro and in vivo studies are necessary to ensure the effectiveness and safety of the designed vaccine.
Materials and Methods: Epitopes that stimulate B- and T-lymphocytes were identified using the ABCpred and IEDB servers. After evaluating various properties—such as non-toxicity (ToxinPred server), lack of allergenicity (AllerTOP server), and immunogenicity (VaxiJen server)—a recombinant vaccine was designed. The characteristics of the vaccine candidate were evaluated using different servers (ProtParam, Solpro, PSIPRED, Cluspro, and C-ImmSim).
Results: Following comprehensive evaluations, three B-lymphocyte-stimulating epitopes and 17 T-lymphocyte-stimulating epitopes were selected for the OMP1 and LolB proteins, respectively. In addition, 17 and 9 T-lymphocyte-stimulating epitopes were identified for OMP1 and LolB, respectively. Various properties of the designed vaccine candidate, including physicochemical properties, secondary structure, expression levels, non-toxicity, and ability to elicit a positive immune system, were predicted.
Conclusion: Based on the computational findings of this study, the designed vaccine may effectively stimulate the immune system and provide immunity against Q fever. Further in vitro and in vivo studies are necessary to ensure the effectiveness and safety of the designed vaccine.
Original: Original |
Subject:
Microbiology and Immunology
Received: 2026/05/17 | Accepted: 2026/07/28 | Published: 2026/08/23
Received: 2026/05/17 | Accepted: 2026/07/28 | Published: 2026/08/23
References
1. Mezouar S, Desnues B, Bechah Y, et al. Pathogenicity and Virulence of Coxiella burnetii: Focus on Q fever. Virulence 2025; 16(1): 2495842. [DOI]
2. Bauer BU, Knittler MR, Andrack J, et al. Interdisciplinary studies on Coxiella burnetii: From molecular to cellular, to host, to one health research. Int J Med Microbiol 2023; 313(6): 151590. [DOI]
3. Latifian M, Amiri FB, Mostafavi E, et al. Evidence of Coxiella burnetii infection among pregnant and aborted women: A systematic review and meta -analysis. New Microbes New Infect 2025; 67: 101619. [DOI]
4. Sasikala A, Prakash C, Valli Ramamoorthy M, et al. Coxiella burnetii as a model system for understanding host immune response against obligate intracellular, vacuolar pathogens. PLoS Pathog 2025; 21(5): e1013071. [DOI]
5. Ullah Q, Jamil T, Saqib M, et al. Q fever —a neglected zoonosis. Microorganisms 2022; 10(8): 1530. [DOI]
6. Gisbert P, Hurtado A, Guatteo R. Efficacy and safety of an inactivated phase I Coxiella burnetii vaccine to control Q fever in ruminants: a systematic review. Animals 2024 ;14(10): 1484. [DOI]
7. Basmenj ER, Pajhouh SR, Fallah AE, et al. Computational epitope -based vaccine design with bioinformatics approach; a review. Heliyon 2025; 11(1): e41714. [DOI]
8. Garc í a -Machorro J, Ram írez -Salinas GL, Martinez -Archundia M, et al. The advantage of using immunoinformatic tools on vaccine design and development for coronavirus. Vaccines 2022; 10(11): 1844. [DOI]
9. Kodori M., Amani J, Ahmadi A. Unveiling promising immunogenic targets in Coxiella burnetii through in silico analysis: paving the way for novel vaccine strategies. BMC Infect Dis 2023; 23(1): 902. [DOI]
10. Metters G, Hemsley C, Norville I, et al. Identification of essential genes in Coxiella burnetii. Microb Genom 2023; 9(2): mgen000944. [DOI]
11. Sanchez -Trincado JL, Gomez -Perosanz M, Reche PA. Fundamentals and methods for T‐and B‐cell epitope prediction. J immunol res 2017; 2017: 2680160. [DOI]
12. Vaez H, Vaez V. Comprehensive analysis of four major surface proteins for vaccine design against Klebsiella pneumoniae. Infect Epidemiol Microbiol 2025; 11(1): 1-12. [DOI]
13. Paul S, Sidney J, Sette A, et al. TepiTool: a pipeline for computational prediction of T cell epitope candidates. Curr protoc immunol 2016; 114: 1-18. [DOI]
14. Gupta S, Kapoor P, Chaudhary K, et al. In silico approach for predicting toxicity of peptides and proteins. PloS one 2013; 8(9): e73957. [DOI]
15. Nguyen MN, Krutz NL, Limviphuvadh V, et al. AllerCatPro 2.0: a web server for predicting protein allergenicity potential. Nucleic Acids Res 2022; 50(W1): W36 -W43. [DOI]
16. Rouzbahani AK, Kheirandish F, Hosseini SZ. Design of a multi -epitope -based peptide vaccine against the S and N proteins of SARS -COV -2 using immunoinformatics approach. Egy J Med Hum Genet 2022; 23(1): 16. [DOI]
17. Gasteiger E, Hoogland C, Gattiker A, et al. Protein Identification and Analysis Tools on the Expasy Server. In The Proteomics Protocols Handbook 2005. Totowa, NJ: Humana press; 571-607. [DOI]
18. Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic acids res 2007; 35: W407-410. [DOI]
19. Heo L, Park H, Seok C. GalaxyRefine: Protein structure refinement driven by side-chain repacking. Nucleic acids res 2013; 41: W384-388. [DOI]
20. Madeira F, Park YM, Lee J, et al. The EMBL -EBI search and sequence analysis tools APIs in 2019. Nucleic acids res 2019; 47: W636-W641. [DOI]
21. Grote A, Hiller K, Scheer M, et al. JCat: a novel tool to adapt codon usage of a target gene to its potential expression host. Nucleic acids res 2005; 33: W526-531. [DOI]
22. Desta IT, Kotelnikov S, Jones G, et al. The ClusPro AbEMap web server for the prediction of antibody epitopes. Nat protoc 2023; 18(6): 1814-1840. [DOI]
23. L ópez -Blanco JR, Aliaga JI, Quintana -Ort í ES, et al. iMODS: internal coordinates normal mode analysis server. Nucleic acids res 2014; 42: W271 -276. [DOI]
24. Castiglione F, Mantile F, De Berardinis P, et al. How the interval between prime and boost injection affects the immune response in a computational model of the immune system. Comput math meth med 2012; 2012(1): 842329. [DOI]
25. Tan T, Heller J, Firestone S, et al. A systematic review of global Q fever outbreaks. One Health 2023; 18: 100667. [DOI]
26. Ahmadinezhad M, Mounesan L, Doosti-Irani A, et al. The prevalence of Q fever in the Eastern Mediterranean region: a systematic review and meta-analysis. Epidemiol Health 2022; 44: e2022097. [DOI]
27. Sam G, Stenos J, Graves SR, et al. Q fever immunology: the quest for a safe and effective vaccine. NPJ Vaccines 2023; 8(1): 133. [DOI]
28. Fratzke AP, van Schaik EJ, Samuel JE. Immunogenicity and reactogenicity in Q fever vaccine development. Front Immunol 2022; 13:886810. [DOI]
29. Sellens E, Bosward KL, Willis S, et al. Frequency of adverse events following Q Fever immunisation in young adults. Vaccines 2018; 6(4): 83. [DOI]
30. Sellens E, Bosward KL, Norris JM, et al. Coxiella burnetii seroprevalence in unvaccinated veterinary workers in Australia: evidence to support Q Fever vaccination. Zoonoses Public Health 2020; 67(1): 79–88. [DOI]
31. Sam G, Plain K, Chen S, et al. Synthetic particulate subunit vaccines for the prevention of Q fever. Adv Health Mater 2024; 13(7): e2302351. [DOI]
32. Li Q, Niu D, Wen B, et al. Protective immunity against Q Fever induced with a recombinant P1 antigen fused with HspB of Coxiella burnetii. Ann N Y Acad Sci 2005; 1063: 130–142. [DOI]
33. Gerlach C, Škult éty Ľ, Henning K, et al. Coxiella burnetii immunogenic proteins as a basis for new Q Fever diagnostic and vaccine development. Acta Virol 2017; 61(3): 377–390. [DOI]
34. Sluder AE, Raju Paul S, Moise L, et al. Evaluation of a human T cell-targeted multi -epitope vaccine for Q fever in animal models of Coxiella burnetii immunity. Front immunol 2022; 13: 901372. [DOI]
35. Rashidian E, Gandabeh ZS, Forouharmehr A, et al. Immunoinformatics approach to engineer a potent polyepitope fusion protein vaccine against Coxiella burnetii. Int J Pep Res Ther 2020; 26(4): 2191-2201. [DOI]
36. Scholzen A, Richard G, Moise L, et al. Promiscuous Coxiella burnetii CD4 epitope clusters associated with human recall responses are candidates for a novel T-cell targeted multi-epitope Q Fever vaccine. Front Immunol 2019; 10: 207. [DOI]
37. Duvaud S, Gabella C, Lisacek F, et al. Expasy, the Swiss Bioinformatics Resource Portal, as designed by its users. Nucleic Acids Res 2021; 49(W1): W216–W227. [DOI]
38. Laskowski RA, MacArthur MW, Moss DS, et al. PROCHECK: a program to check the stereochemical quality of protein structures. Applied Crystallog 1993; 26(2): 283-291. [DOI]
Send email to the article author
| Rights and Permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
