Designing of Multi-Epitope Vaccine against Trichomonas vaginalis Using Immuno-informatics

Author

Assistant Professor, Department of Cell and Molecular Biology & Microbiology, School of Biological Sciences and Technology, University of Isfahan, Isfahan, Iran

Abstract

Background: Trichomonas vaginalis is one of the most common sexually transmitted infections around the world. Given the importance of this infection in public health, extensive efforts have been made to develop vaccines. Previous research has been limited to the inactivated vaccine or using an adhesion protein as a vaccine candidate, and no effective vaccine for the disease has been suggested until now.  This study aimed to design a vaccine based on epitopes of parasite adhesion proteins to be used as an immunogenic protein using immune-informatics tools.
Methods: First, AP33, AP51 and AP65 protein sequences were retrieved. Epitopes of B and T lymphocytes were then predicted. Antigenicity, non-allergenicity and non-toxicity of epitopes were evaluated and vaccine structure was designed. Then the physical, chemical and structural properties of the vaccine were determined and finally, the ability of the vaccine to bind to TLRs was investigated.
Findings: A total of 9 lymphocytes B and T epitopes were selected and a vaccine construct was designed based on them. Immuno-informatics evaluations showed that the designed vaccine is safe, hydrophilic and stable at different temperatures and conditions, that can bind to TLRs and activate innate immunity.
Conclusion: Based on the results, the polypeptide construct can be a suitable candidate for Trichomoniasis vaccine.

Keywords


  1. Arbabi M, Delavari M, Fakhrieh-Kashan Z, Hooshyar H. Review of trichomonas vaginalis in Iran, based on epidemiological situation. J Reprod Infertil 2018; 19(2): 82-8.
  2. Rowley J, vander Hoorn S, Korenromp E, Low N, Unemo M, Abu-Raddad LJ, et al. Chlamydia, gonorrhoea, trichomoniasis and syphilis: global prevalence and incidence estimates, 2016. Bull World Health Organ 2019; 97(8): 548-62.
  3. Matini M, Rezaie S, Mohebali M, Maghsood A, Rabiee S, Fallah M, et al. Prevalence of Trichomonas vaginalis Infection in Hamadan City, Western Iran. Iran J Parasitol 2012; 7(2): 67-72.
  4. Singh BN, Lucas JJ, Fichorova RN. Trichomonas vaginalis: pathobiology and pathogenesis. In: Khan NA, editors. Emerging protozoan pathogens. London, UK: Taylor & Francis Group; 2007. p. 411-55.
  5. Sallam TAK, Meghahed LA, Ibrahim SM, Morsy TA. An overview on trichomonas vaginalis with reference to Egypt. J Egypt Soc Parasitol 2021; 51(2): 267-80.
  6. de Aquino MFK, Hinderfeld AS, Simoes-Barbosa A. Trichomonas vaginalis. Trends Parasitol 2020; 36(7): 646-7.
  7. Lin WC, Chang WT, Chang TY, Shin JW. The pathogenesis of human cervical epithelium cells induced by interacting with Trichomonas vaginalis. PLoS One 2015; 10(4): e0124087.
  8. Zhang Z, Li Y, Wang S, Hao L, Zhu Y, Li H, et al. The molecular characterization and immunity identification of trichomonas vaginalis adhesion protein 33 (AP33). Front Microbiol 2020; 11: 1433.
  9. Lin HC, Chu LJ, Huang PJ, Cheng WH, Zheng YH, Huang CY, et al. Proteomic signatures of metronidazole-resistant Trichomonas vaginalis reveal novel proteins associated with drug resistance. Parasit Vectors 2020; 13(1): 1-14.
  10. Liu T, Shi K, Li W. Deep learning methods improve linear B-cell epitope prediction. BioData Min 2020; 13: 1.
  11. Fleri W, Paul S, Dhanda SK, Mahajan S, Xu X, Peters B, et al. The immune epitope database and analysis resource in epitope discovery and synthetic vaccine design. Front Immunol 2017; 8: 278.
  12. Bibi S, Ullah I, Zhu B, Adnan M, Liaqat R, Kong WB, et al. In silico analysis of epitope-based vaccine candidate against tuberculosis using reverse vaccinology. Sci Rep 2021; 11(1): 1249.
  13. Calis JJ, Maybeno M, Greenbaum JA, Weiskopf D, De Silva AD, Sette A, et al. Properties of MHC class I presented peptides that enhance immunogenicity. PLoS Comput Biol 2013; 9(10): e1003266.
  14. Walker JM. The proteomics protocols handbook. New York, NY: Springer. 2005; p. 571-608.
  15. Pitti T, Chen CT, Lin HN, Choong WK, Hsu WL, Sung TY. N-GlyDE: a two-stage N-linked glycosylation site prediction incorporating gapped dipeptides and pattern-based encoding. Sci Rep 2019; 9(1): 15975.
  16. Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature 2021; 596(7873): 583-9.
  17. Heo L, Park H, Seok C. GalaxyRefine: Protein structure refinement driven by side-chain repacking. Nucleic Acids Res 2013; 41(Web Server issue): W384-8.
  18. Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr 1993; 26(2): 283-91.
  19. Sanches RC, Tiwari S, Ferreira LC, Oliveira FM, Lopes MD, Passos MJ, et al. Immunoinformatics design of multi-epitope peptide-based vaccine against Schistosoma mansoni using transmembrane proteins as a target. Front Immunol 2021; 12: 621706.
  20. Kissinger P. Trichomonas vaginalis: a review of epidemiologic, clinical and treatment issues. BMC Infect Dis 2015; 15: 307.
  21. Bouchemal K, Bories C, Loiseau PM. Strategies for prevention and treatment of Trichomonas vaginalis infections. Clin Microbiol Rev 2017; 30(3): 811-25.
  22. Mendoza-Oliveros T, Arana-Argáez V, Alvaréz-Sánchez LC, Lara-Riegos J, Alvaréz-Sánchez ME, Torres-Romero JC. Immune response of BALB/c mice toward putative calcium transporter recombinant protein of Trichomonas vaginalis. Korean J Parasitol 2019; 57(1): 33-8.
  23. Xie YT, Gao JM, Wu YP, Tang P, Hide G, Lai DH, et al. Recombinant α-actinin subunit antigens of Trichomonas vaginalis as potential vaccine candidates in protecting against trichomoniasis. Parasit Vectors 2017; 10(1): 83.
  24. Zhang Z, Song X, Zhang Z, Li H, Duan Y, Zhang H, et al. The molecular characterization and immune protection of adhesion protein 65 (AP65) of Trichomonas vaginalis. Microb Pathog 2021; 152: 104750.
  25. Dubey KK, Luke GA, Knox C, Kumar P, Pletschke BI, Singh PK, et al. Vaccine and antibody production in plants: developments and computational tools. Brief Funct Genomics 2018; 17(5): 295-307.
  26. García-Angulo VA, Kalita A, Kalita M, Lozano L, Torres AG. Comparative genomics and immunoinformatics approach for the identification of vaccine candidates for enterohemorrhagic Escherichia coli O157:H7. Infect Immun 2014; 82(5): 2016-26.
  27. Dong R, Chu Z, Yu F, Zha Y. Contriving multi-epitope subunit of vaccine for COVID-19: immunoinformatics approaches. Front Immunol 2020; 11: 1784.
  28. Meza B, Ascencio F, Sierra-Beltrán AP, Torres J, Angulo C. A novel design of a multi-antigenic, multistage and multi-epitope vaccine against Helicobacter pylori: an in silico approach. Infect Genet Evol 2017; 49: 309-17.
  29. Corradin G, Villard V, Kajava AV. Protein structure based strategies for antigen discovery and vaccine development against malaria and other pathogens. Endocr Metab Immune Disord Drug Targets 2007; 7(4): 259-65.
  30. Fitzgerald KA, Kagan JC. Toll-like receptors and the control of immunity. Cell 2020; 180(6): 1044-66.