Design and immunogenicity of a recombinant Saccharomyces boulardii secreting the P2-VP8 subunit rotavirus vaccine

1. Burke, R. M. et al. Impact of rotavirus vaccination on rotavirus hospitalizations in Taiwanese children. Vaccine 39(49), 7135–7139 (2021).

   Google Scholar 

2. Crawford, S. E. et al. Rotavirus infection. Nat. Rev. Dis. Primers. 3(1), 1–16 (2017).

   Google Scholar 

3. Marelli, B. et al. Oral immunization with live Lactococcus lactis expressing rotavirus VP8* subunit induces specific immune response in mice. J. Virol. Methods 175(1), 28–37 (2011).

   Google Scholar 

4. Wen, X. et al. Tandem truncated rotavirus VP8* subunit protein with T cell epitope as non-replicating parenteral vaccine is highly immunogenic. Hum. Vaccin. Immunother. 11(10), 2483–2489 (2015).

   Google Scholar 

5. Xue, M. et al. Immunogenicity and protective efficacy of rotavirus VP8* fused to cholera toxin B subunit in a mouse model. Hum. Vaccin. Immunother. 12(11), 2959–2968 (2016).

   Google Scholar 

6. Sadiq, A. & Bostan, N. Comparative analysis of G1P [8] rotaviruses identified prior to vaccine implementation in Pakistan with Rotarix™ and RotaTeq™ vaccine strains. Front. Immunol. 11, 562282 (2020).

   Google Scholar 

7. Parashar, U.D., E.A.S. Nelson, and G. Kang, Diagnosis, management, and prevention of rotavirus gastroenteritis in children. Bmj, 2013. 347.

8. Davies, M. N. & Flower, D. R. Harnessing bioinformatics to discover new vaccines. Drug Discov. Today 12(9–10), 389–395 (2007).

   Google Scholar 

9. Burke, R. M. et al. Current and new rotavirus vaccines. Curr. Opin. Infect. Dis. 32(5), 435 (2019).

   Google Scholar 

10. Perrie, Y. et al. Vaccine adjuvant systems: Enhancing the efficacy of sub-unit protein antigens. Int. J. Pharm. 364(2), 272–280 (2008).

    Google Scholar 

11. Lakatos, K. et al. Formulation and preclinical studies with a trivalent rotavirus P2-VP8 subunit vaccine. Hum. Vaccin. Immunother. 16(8), 1957–1968 (2020).

    Google Scholar 

12. Wen, X. et al. Inclusion of a universal tetanus toxoid CD4+ T cell epitope P2 significantly enhanced the immunogenicity of recombinant rotavirus ΔVP8* subunit parenteral vaccines. Vaccine 32(35), 4420–4427 (2014).

    Google Scholar 

13. Albekairi, T. H. et al. Design of a multi-epitope vaccine against tropheryma whipplei using immunoinformatics and molecular dynamics simulation techniques. Vaccines 10(5), 691 (2022).

    Google Scholar 

14. Samad, A. et al. Designing a multi-epitope vaccine against SARS-CoV-2: An immunoinformatics approach. J. Biomol. Struct. Dyn. 40(1), 14–30 (2022).

    Google Scholar 

15. Sharma, A.D., et al., T cell epitope based vaccine design while targeting outer capsid proteins of rotavirus strains infecting neonates: An immunoinformatics approach. J. Biomol. Struct. Dyn., 2023: p. 1–19.

16. Li, M. et al. Design of a multi-epitope vaccine candidate against Brucella melitensis. Sci. Rep. 12(1), 1–18 (2022).

    Google Scholar 

17. Farhani, I., et al., Designing a Multi-epitope Vaccine against the SARS-CoV-2 Variant Based on an Immunoinformatics Approach. Current Computer-aided Drug Design, 2023.

18. Akhgar, S., et al., Immunization of BALB/c mice against Shigella sonnei using a multiepitope protein vaccine through intranasal and subcutaneous administration. Iranian J. Allergy, Asthma Immunol., 2024.

19. Vita, R. et al. The immune epitope database (IEDB): 2018 update. Nucleic Acids Res. 47(D1), D339–D343 (2019).

    Google Scholar 

20. Andreatta, M. & Nielsen, M. Gapped sequence alignment using artificial neural networks: Application to the MHC class I system. Bioinformatics 32(4), 511–517 (2016).

    Google Scholar 

21. Reynisson, B. et al. NetMHCpan-4.1 and NetMHCIIpan-4.0: Improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data. Nucleic Acids Res. 48(W1), W449–W454 (2020).

    Google Scholar 

22. Mehta, N.K., et al., In silico tool for Predicting, Designing and Scanning IL-2 inducing peptides. bioRxiv, 2021: p. 2021.06. 20.449146.

23. Bui, H.-H. et al. Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinf. 7(1), 1–5 (2006).

    Google Scholar 

24. Jespersen, M. C. et al. BepiPred-2.0: Improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Res. 45(W1), W24–W29 (2017).

    Google Scholar 

25. Singh, H., Ansari, H. R. & Raghava, G. P. Improved method for linear B-cell epitope prediction using antigen’s primary sequence. PLoS ONE 8(5), e62216 (2013).

    Google Scholar 

26. Magnan, C. N. et al. High-throughput prediction of protein antigenicity using protein microarray data. Bioinformatics 26(23), 2936–2943 (2010).

    Google Scholar 

27. Doytchinova, I. A. & Flower, D. R. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinf. 8(1), 4 (2007).

    Google Scholar 

28. Nguyen, M.N., et al., AllerCatPro 2.0: A web server for predicting protein allergenicity potential. Nucleic Acids Research, 2022.

29. Sharma, N. et al. ToxinPred2: An improved method for predicting toxicity of proteins. Brief. Bioinf. 23(5), bbac174 (2022).

    Google Scholar 

30. Hebditch, M. et al. Protein–Sol: A web tool for predicting protein solubility from sequence. Bioinformatics 33(19), 3098–3100 (2017).

    Google Scholar 

31. Gasteiger, E., et al., Protein identification and analysis tools on the ExPASy server. The proteomics protocols handbook, 2005: p. 571–607.

32. Guruprasad, K., Reddy, B. B. & Pandit, M. W. Correlation between stability of a protein and its dipeptide composition: A novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Eng. Des. Sel. 4(2), 155–161 (1990).

    Google Scholar 

33. Ikai, A. Thermostability and aliphatic index of globular proteins. J. Biochem. 88(6), 1895–1898 (1980).

    Google Scholar 

34. Kalita, P. et al. Development of multi-epitope driven subunit vaccine against Fasciola gigantica using immunoinformatics approach. Int. J. Biol. Macromol. 138, 224–233 (2019).

    Google Scholar 

35. Zhao, S. et al. Secrets behind protein sequences: Unveiling the potential reasons for varying allergenicity caused by caseins from cows, goats, camels, and mares based on bioinformatics analyses. Int. J. Mol. Sci. 24(3), 2481 (2023).

    Google Scholar 

36. Buchan, D. W. & Jones, D. T. The PSIPRED protein analysis workbench: 20 years on. Nucleic Acids Res. 47(W1), W402–W407 (2019).

    Google Scholar 

37. Roy, A., Kucukural, A. & Zhang, Y. I-TASSER: A unified platform for automated protein structure and function prediction. Nat. Protoc. 5(4), 725–738 (2010).

    Google Scholar 

38. Laskowski, R., M. MacArthur, and J. Thornton, PROCHECK: validation of protein-structure coordinates. 2006.

39. Ko, J. et al. GalaxyWEB server for protein structure prediction and refinement. Nucleic Acids Res. 40(W1), W294–W297 (2012).

    Google Scholar 

40. Shuvo, M. H., Gulfam, M. & Bhattacharya, D. DeepRefiner: High-accuracy protein structure refinement by deep network calibration. Nucleic Acids Res. 49(W1), W147–W152 (2021).

    Google Scholar 

41. Wiederstein, M. & Sippl, M. J. ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 35(suppl_2), W407–W410 (2007).

    Google Scholar 

42. Ponomarenko, J. et al. ElliPro: A new structure-based tool for the prediction of antibody epitopes. BMC Bioinf. 9(1), 1–8 (2008).

    Google Scholar 

43. Yan, Y. et al. The HDOCK server for integrated protein–protein docking. Nat. Protoc. 15(5), 1829–1852 (2020).

    Google Scholar 

44. Laskowski, R. A. et al. PDBsum: Structural summaries of PDB entries. Protein Sci. 27(1), 129–134 (2018).

    Google Scholar 

45. Phillips, J. C. et al. Scalable molecular dynamics with NAMD. J. Comput. Chem. 26(16), 1781–1802 (2005).

    Google Scholar 

46. Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14(1), 33–38 (1996).

    Google Scholar 

47. Rapin, N., Lund, O. & Castiglione, F. Immune system simulation online. Bioinformatics 27(14), 2013–2014 (2011).

    Google Scholar 

48. Hofacker, I. L. Vienna RNA secondary structure server. Nucleic Acids Res. 31(13), 3429–3431 (2003).

    Google Scholar 

49. Suckow, M.A., K.A. Stevens, and R.P. Wilson, The laboratory rabbit, guinea pig, hamster, and other rodents. 2011: Academic Press.

50. Leenaars, M. & Hendriksen, C. F. Critical steps in the production of polyclonal and monoclonal antibodies: Evaluation and recommendations. ILAR J. 46(3), 269–279 (2005).

    Google Scholar 

51. Saluja, T. et al. A multicenter prospective hospital-based surveillance to estimate the burden of rotavirus gastroenteritis in children less than five years of age in India. Vaccine 32, A13–A19 (2014).

    Google Scholar 

52. Groome, M. J. et al. Safety and immunogenicity of a parenteral trivalent P2-VP8 subunit rotavirus vaccine: A multisite, randomised, double-blind, placebo-controlled trial. Lancet. Infect. Dis 20(7), 851–863 (2020).

    Google Scholar 

53. Monavari, S. H. R. et al. Epidemiology of rotavirus in the Iranian children: A systematic review and meta-analysis. J. Global Infect. Dis. 9(2), 66–72 (2017).

    Google Scholar 

54. Wang, N. et al. Subunit vaccines against emerging pathogenic human coronaviruses. Front. Microbiol. 11, 298 (2020).

    Google Scholar 

55. Pambudi, N. A. et al. Vaccine cold chain management and cold storage technology to address the challenges of vaccination programs. Energy Rep. 8, 955–972 (2022).

    Google Scholar 

56. Orr, M. T. et al. Elimination of the cold-chain dependence of a nanoemulsion adjuvanted vaccine against tuberculosis by lyophilization. J. Control. Release 177, 20–26 (2014).

    Google Scholar 

57. Kaur, A. et al. Toll-like receptor (TLR) agonists as a driving force behind next-generation vaccine adjuvants and cancer therapeutics. Curr. Opin. Chem. Biol. 70, 102172 (2022).

    Google Scholar 

58. Kumar, A. et al. “ Universal” T helper cell determinants enhance immunogenicity of a Plasmodium falciparum merozoite surface antigen peptide. J. Immunol. 148(5), 1499–1505 (1992).

    Google Scholar 

59. Hamley, I. W. Peptides for vaccine development. ACS Appl. Bio Mater. 5(3), 905–944 (2022).

    Google Scholar 

60. Xia, M. et al. Immune response and protective efficacy of the S particle presented rotavirus VP8* vaccine in mice. Vaccine 37(30), 4103–4110 (2019).

    Google Scholar 

61. Xu, J. et al. Expression of Toll-like receptors and their association with cytokine responses in peripheral blood mononuclear cells of children with acute rotavirus diarrhoea. Clin. Exp. Immunol. 144(3), 376–381 (2006).

    Google Scholar 

62. Zhou, W.-Y. et al. Therapeutic efficacy of a multi-epitope vaccine against Helicobacter pylori infection in BALB/c mice model. Vaccine 27(36), 5013–5019 (2009).

    Google Scholar 

63. Vartak, A. & Sucheck, S. J. Recent advances in subunit vaccine carriers. Vaccines 4(2), 12 (2016).

    Google Scholar 

64. Bagherpour, G. et al. Oral administration of recombinant Saccharomyces boulardii expressing ovalbumin-CPE fusion protein induces antibody response in mice. Front. Microbiol. 9, 723 (2018).

    Google Scholar 

65. Pontrelli, S. et al. Escherichia coli as a host for metabolic engineering. Metab. Eng. 50, 16–46 (2018).

    Google Scholar 

66. McFarland, L. V. Systematic review and meta-analysis of Saccharomyces boulardii in adult patients. World J. Gastroenterol: WJG 16(18), 2202 (2010).

    Google Scholar 

67. Hudson, L. E. et al. Functional heterologous protein expression by genetically engineered probiotic yeast Saccharomyces boulardii. PLoS ONE 9(11), e112660 (2014).

    Google Scholar 

68. Rosano, G. L. & Ceccarelli, E. A. Recombinant protein expression in Escherichia coli: Advances and challenges. Front. Microbiol. 5, 172 (2014).

    Google Scholar 

69. Carlini, D. B. Context-dependent codon bias and messenger RNA longevity in the yeast transcriptome. Mol. Biol. Evol. 22(6), 1403–1411 (2005).

    Google Scholar 

70. Yamchi, A. et al. Evaluation of the impact of polypeptide-p on diabetic rats upon its cloning, expression, and secretion in Saccharomyces boulardii. Arch. Microbiol. 206(1), 37 (2024).

    Google Scholar 

71. Chen, Y. et al. Truncated rotavirus VP4 proteins induce stronger protective immunity compared to P2-VP8 in animal models. Antiviral Res. 238, 106156 (2025).

    Google Scholar 

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