Multi Epitope Based Vaccine Design against Capnocytophaga canimorsus through Immunoinformatics Approaches

Abstract

Immunoinformatics has provided an important contribution to the acceleration of vaccine research. The in silico tools developed under immunoinformatics efficiently filter candidate vaccines and select the most appropriate ones for in vitro and in vivo studies. Multi epitope-based vaccine design against Capnocytophaga canimorsus infections through immunoinformatics approaches was proposed in the present investigation. Outer membrane protein (OMP) of C. canimorsus was used to develop peptide-based vaccines. IEDB tools are used in this research. The antigenic potential of C. canimorsus OMP was evaluated via VaxiJen v2.0 and the Overall Prediction for the Protective Antigen was found to be 0.6049. MHC-I and -II binding epitopes with maximum scores were found to be “QEIGKLKKY” for HLAB*44:03 and “FNAVQEIGK” for HLA-DRB5*01:01, respectively. ABCPrep analysis identified multiple epitopes. The maximum score of 0.91 was associated with the sequence “KNMRIGYVDMDFILEN”. Discontinuous epitopes were also detected in this research with the maximum score observed for the regions A:L247, A:E248, A:Q250 and A:K251. The population coverage for the global population was calculated to be 96.45% for a defined set of epitopes. In conclusion, since the adoption of dogs and cats as pets has increased after COVID-19, there is a clear risk for C. canimorsus infections. The proposed peptide-based vaccines in this report may mitigate this risk on a global level.

Keywords

• Antigenic potential
• Capnocytophaga canimorsus
• Immunoinformatics
• Health biotechnology
• vaccine

References

1. Ammerman SM (2017). The Evolution of Animals through Domestication and other Human Relationships: An Animal-Centered Approach (Doctoral dissertation, UCLA).
2. Andreatta M, Nielsen M (2016) Gapped sequence alignment using artificial neural networks: application to the MHC class I system. Bioinformatics 32: 511-517 doi.org/10.1093/bioinformatics/btv639
3. Antelmann H, Tjalsma H, Voigt B, Ohlmeier S, Bron S, van Dijl JM, Hecker M (2001) A proteomic view on genome-based signal peptide predictions. Genome Res 11: 1484-1502 doi.org/10.1101/gr.182801
4. Authority EFS (2024) The European Union One Health 2023 Zoonoses report. EFSA J 22: 9106 doi.org/10.2903/j.efsa.2024.9106
5. Bateman A, Martin MJ, Orchard S, Magrane M, Ahmad S, Alpi E, Bowler-Barnett EH, Britto R, Cukura A, Denny P, Dogan T (2023) UniProt: the universal protein knowledgebase in 2023. Nucleic Acids Res 51: 523-531 doi.org/10.1093/nar/gkac1052
6. Beauruelle C, Plouzeau C, Grillon A, Isnard C, Corvec S, Degand N, Jacquier H, Amara M, Mizrahi A, Diedrich T, Piau C, Farfour E, Bonzon L, Le Brun C, Walewski V, Bille E, Dortet L, Guillard T, Soismier N, Le Guen R, Morand P, de Ponfilly GP, Le Monnier A, Le Monnier A, Héry-Arnaud G (2022) Capnocytophaga zoonotic infections: a 10-year retrospective study (the French CANCAN study). Eur J Clin Microbiol Infect Dis 41: 581-588 doi.org/10.1007/s10096-022-04402-x
7. Bobo RA, Newton EJ (1976) A previously undescribed gram-negative bacillus causing septicemia and meningitis. Am J Clin Pathol 65: 564-569 doi.org/10.1093/ajcp/65.4.564
8. Buckland B, Sanyal G, Ranheim T, Pollard D, Searles JA, Behrens S, Pluschkell S, Josefsberg J, Roberts CJ (2024) Vaccine process technology—A decade of progress. Biotechnol Bioeng doi.org/10.1002/bit.28703

9. Bui HH, Sidney J, Dinh K, Southwood S, Newman MJ, Sette A (2006) Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinformatics 7: 1-5 doi.org/10.1186/1471-2105-7-153
10. Butler T (2015) Capnocytophaga canimorsus : an emerging cause of sepsis, meningitis, and post-splenectomy infection after dog bites. Eur J Clin Microbiol Infect Dis 34: 1271-1280 doi.org/10.1007/s10096-015-2360-7
11. Calado CR (2022) Antigenic and conserved peptides from diverse Helicobacter pylori antigens. Biotechnol Lett 44: 535-545 doi.org/10.1007/s10529-022-03238-x
12. Calis JJ, Maybeno M, Greenbaum JA, Weiskopf D, De Silva AD, Sette A, Keşmir C, Peters B (2013) Properties of MHC class I presented peptides that enhance immunogenicity. PLoS Comput Biol 9:1003266 doi.org/10.1371/journal.pcbi.1003266 Coudert E, Gehant S, De Castro E, Pozzato M, Baratin D, Neto T, Sigrist CJ, Redaschi N, Bridge A (2023) Annotation of biologically relevant ligands in UniProtKB using ChEBI Bioinformatics 39: 793 doi.org/10.1093/bioinformatics/btac793
13. Cusick MF, Libbey JE, Fujinami RS (2012) Molecular mimicry as a mechanism of autoimmune disease. Clin Rev Allergy Immunol 42: 102-111 doi.org/10.1007/s12016-011-8294-7
14. Damas MSF, Mazur FG, Freire CCDM, Cunha AFD, Pranchevicius MCDS (2022) A systematic immuno-informatic approach to design a multiepitope-based vaccine against emerging multiple drug resistant serratia marcescens. Front Immunol 13: 768569 doi.org/10.3389/fimmu.2022.768569
15. De Tiège A, Verpooten J, Braeckman J (2021) From animal signals to art: manipulative animal signaling and the evolutionary foundations of aesthetic behavior and art production. Q Rev Biol 96: 1-27 doi.org/10.1086/713210
16. Desvars-Larrive A, Vogl AE, Puspitarani GA, Yang L, Joachim A, Käsbohrer A (2024) A One Health framework for exploring zoonotic interactions demonstrated through a case study. Nat Commun15: 5650 doi.org/ 10.1038/s41467-024-49967-7
17. Dimitrov I, Zaharieva N, Doytchinova, I (2020) Bacterial immunogenicity prediction by machine learning methods. Vaccines 8: 709 doi.org/10.3390/vaccines8040709
18. Dogbey G, Dugah A, Abbiw RK, Agbolosu A, Asare-Dompreh K, Odoom T, Okine A, Amakye-Anim J, Otsyina HR, Enyetornye B (2024) Impact of COVID-19 on pets and pet owners: A survey conducted in selected veterinary clinics in Accra, Ghana. Heliyon 10 doi.org/ 10.1016/j.heliyon.2024.e37328
19. Esposito MM, Turku S, Lehrfield L, Shoman A (2023) The impact of human activities on zoonotic infection transmissions. Anim 13: 1646 doi.org/10.3390/ani13101646
20. Fiers MW, Kleter GA, Nijland H, Peijnenburg AA, Nap JP, Van Ham RC (2004) Allermatch™, a webtool for the prediction of potential allergenicity according to current FAO/WHO Codex alimentarius guidelines. BMC Bioinformatics 5: 1-6 doi.org/10.1186/1471-2105-5-133
21. Galibert F, Quignon P, Hitte C, André C (2011) Toward understanding dog evolutionary and domestication history. C R Biol 334: 190-196 doi.org/10.1016/j.crvi.2010.12.011
22. Galles A, Monlun E, Villeneuve L, Poirot-Mazères S (2020) Méningite à Capnocytophaga canimorsus. Med Mal Infect 50: 754-756 doi.org/10.1016/j.medmal.2020.09.001
23. Gebre MS, Brito LA, Tostanoski LH, Edwards DK, Carfi A, Barouch DH (2021) Novel approaches for vaccine development. Cell 184: 1589-1603 doi.org/10.1016/j.cell.2021.02.030
24. Gonzalez-Galarza FF, McCabe A, Santos, EJMD, Jones J, Takeshita L, Ortega-Rivera N D, Cid-Pavon G M D, Ramsbottom K, Ghattaoraya G, Alfirevic A, Middleton D, Jones A R (2020) Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools. Nucleic Acids Res 48: 783-788 doi.org/10.1093/nar/gkz1029
25. Hannon DM, Harkin E, Donnachie K, Sibartie S, Doyle M, Chan G (2020) A case of Capnocytophaga canimorsus meningitis and bacteraemia. Ir J Med Sci 189: 251-252 doi.org/10.1007/s11845-019-02045-0
26. Hedman HD, Krawczyk E, Helmy YA, Zhang L, Varga C (2021) Host diversity and potential transmission pathways of SARS-CoV-2 at the human-animal interface. Pathog 10: 180 doi.org/10.3390/pathogens10020180 Ho J, Hussain S, Sparagano O (2021) Did the COVID-19 pandemic spark a public interest in pet adoption?. Front Vet Sci 8: 647308 doi.org/10.3389/fvets.2021.647308
27. Jespersen MC, Peters B, Nielsen M, Marcatili P (2017) BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Res 45: 24-29 doi.org/10.1093/nar/gkx346
28. Jolivet-Gougeon A, Sixou JL, Tamanai-Shacoori Z, Bonnaure-Mallet M (2007) Antimicrobial treatment of Capnocytophaga infections. Int J Antimicrob Agent 29: 367-373 doi.org/10.1016/j.ijantimicag.2006.10.005
29. Jumper, J, Evans R, Pritzel A, Green, T, Figurnov M, Ronneberger, O, Tunyasuvunakool K, Bates R, Žídek A, Potapenko A, Bridgland A, Meyer C, Kohl SAA, Ballard AJ, Cowie A, Romera-Paredes B, Nikolov S, Jain R, Adler J, Black T, Pretersen S, Reiman D, Clancy E, Zielinski M, Steinegger M, Pacholska M, Berghammer T, Bodenstein S, Silver D, Vinyals O, Senior AW, Kavukcuoglu K, Kohli P, Hassabis D 2021 Highly accurate protein structure prediction with AlphaFold. Nature 596: 583-589
30. Ko AI, Goarant C, Picardeau M (2009) Leptospira: the dawn of the molecular genetics era for an emerging zoonotic pathogen. Nat Rev Microbiol 7: 736-747 doi.org/10.1038/nrmicro2208
31. Kolaskar AS, Tongaonkar PC (1990) A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett. 276: 172-174 doi.org/10.1016/0014-5793(90)80535-Q
32. Krishnan S, Joshi A, Akhtar N, Kaushik V (2021) Immunoinformatics designed T cell multi epitope dengue peptide vaccine derived from non structural proteome. Microb Pathog 150: 104728 doi.org/10.1016/j.micpath.2020.104728
33. Kushwaha V, Prabha A, Sharma V, Devi A, Ramniwas S, Sharma A, Sharma AK, Sheikh I, Panwar A, Kaur D (2024) Immunoinformatics: computational keys to immune system secrets. Bioinform Drug Discov 123 doi.org/10.1515/9783111568584-007
34. Lee K, McGregor S, Strowd L (2020) Noninflammatory Retiform Purpura: Answer. Am J Dermatopathol 42: 893-894 doi.org/10.1097/DAD.0000000000001552
35. Larsen MV, Lundegaard C, Lamberth K, Buus S, Lund O, Nielsen M (2007) Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction. BMC Bioinformatics 8: 1-12 doi.org/10.1186/1471-2105-8-424
36. Larsen JEP, Lund O, Nielsen M (2006) Improved method for predicting linear B-cell epitopes. Immunome Res 2: 1-7 doi.org/10.1186/1745-7580-2-2
37. Li D, Wu M (2021) Pattern recognition receptors in health and diseases. Signal Transduct Target Ther 6: 291 doi.org/10.1038/s41392-021-00687-0
38. Lion C, Escande F, Burdin JC (1996) Capnocytophaga canimorsus infections in human: review of the literature and cases report. Eur J Epidemiol 12: 521-533 doi.org/10.1007/BF00144007
39. Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M (2008) NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11. Nucleic Acids Res 36: 509-512 doi.org/10.1093/nar/gkn202
40. Mader N, Luehrs F, Langenbeck M, Herget-Rosenthal S (2020) Capnocytophaga canimorsus–a potent pathogen in immunocompetent humans–systematic review and retrospective observational study of case reports. Infect Dis 52: 65-74 doi.org/10.1080/23744235.2019.1687933
41. Masum MHU, Wajed S, Hossain MI, Moumi NR, Talukder A, Rahman MM (2024) An mRNA vaccine for pancreatic cancer designed by applying in silico immunoinformatics and reverse vaccinology approaches. PLoS One 19: 0305413 doi.org/10.1371/journal.pone.0305413
42. Meyer EC, Alt-Epping S, Moerer O, Büttner B (2021) Fatal septic shock due to Capnocytophaga canimorsus bacteremia masquerading as COVID-19 pneumonia-a case report. BMC Infect Dis 21: 1-6 doi.org/10.1186/s12879-021-06422-y
43. Nielsen M, Lundegaard C, Lund O, Keşmir C (2005) The role of the proteasome in generating cytotoxic T-cell epitopes: insights obtained from improved predictions of proteasomal cleavage. Immunogenet 57: 33-41 doi.org/10.1007/s00251-005-0781-7
44. Oltenacu EAB (2004) Domestication of animals. Encycl Anim Sci 294-296
45. O'Riordan, F Ronayne A, Jackson A (2021) Capnocytophaga canimorsus meningitis and bacteraemia without a dog bite in an immunocompetent individual. BMJ Case Rep 14: 242432 doi.org/10.1136/bcr-2021-242432
46. Ortega-Tirado D, Arvizu-Flores AA, Velazquez C, Garibay-Escobar A (2020) The role of immunoinformatics in the development of T-cell peptide-based vaccines against Mycobacterium tuberculosis. Expert Rev Vaccines 19: 831-841 doi.org/10.1080/14760584.2020.1825950
47. Owji H, Nezafat N, Negahdaripour M, Hajiebrahimi A, Ghasemi Y (2018) A comprehensive review of signal peptides: Structure, roles, and applications. Eur J Cell Biol 97: 422-441 doi.org/10.1016/j.ejcb.2018.06.003
48. Parisi X, Pihán G (2023) Purpura fulminans due to Capnocytophaga canimorsus. Br J Haematol 202 doi.org/10.1111/bjh.18837.
49. Pati R, Shevtsov M, Sonawane A (2018) Nanoparticle vaccines against infectious diseases. Front Immunol 9: 2224 doi.org/10.3389/fimmu.2018.02224
50. Pieracci EG, Williams CE, Wallace RM, Kalapura CR, Brown CM (2021) US dog importations during the COVID-19 pandemic: Do we have an erupting problem?. PLoS One, 16: 0254287 doi.org/10.1371/journal.pone.0254287
51. Ponomarenko J, Bui HH, Li W, Fusseder N, Bourne PE, Sette A, Peters B (2008) ElliPro: a new structure-based tool for the prediction of antibody epitopes. BMC Bioinformatics 9: 1-8. doi.org/10.1186/1471-2105-9-514
52. Popiel KY, Vinh DC (2013) ‘Bobo-Newton syndrome’: An unwanted gift from man’s best friend. Can J Infect Dis Med Microbiol 24: 209 doi.org/10.1155/2013/930158
53. Powell L, Lavender TM, Reinhard CL, Watson B (2022) Pet Owners’ Perceptions of COVID-19, zoonotic disease, and veterinary medicine: The impact of demographic characteristics. Vet Sci 9: 195 doi.org/10.3390/vetsci9050195
54. Rees EM, Minter A, Edmunds WJ, Lau CL, Kucharski AJ, Lowe R (2021) Transmission modelling of environmentally persistent zoonotic diseases: a systematic review. Lancet Planet Health 5: 466-478 doi.org/10.1016/S2542-5196(21)00137-6
55. Repac J, Mandić M, Lunić T, Božić B, Božić Nedeljković B (2021) Mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis—A systematic immunoinformatics analysis of T cell epitopes. PLoS One 16: 0253918 doi.org/10.1371/journal.pone.0253918
56. Saha S, Raghava GPS (2006) AlgPred: prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Res 34: 202-209 doi.org/10.1093/nar/gkl343
57. Saha S, Raghava GPS (2006) Prediction of continuous B‐cell epitopes in an antigen using recurrent neural network. Proteins:Struct Funct Bioinf 65: 40-48 doi.org/10.1002/prot.21078
58. Saklani S, Barsola, B, Pathania D, Sonu S, Kumari P, Singh P, Taha BA, Rustagi S, Thakur P, Narayan M, Chaudhary V (2024) Nanomaterials-integrated electrochemical biosensors as pioneering solutions for zoonotic disease diagnosis. J Electrochem Soc171: 087502 doi.org/10.1149/1945-7111/ad65bb
59. Sandoe JA (2004) Capnocytophaga canimorsus endocarditis. J Med Microbiol 53: 245-248 doi.org/10.1099/jmm.0.05274-0
60. Schleidt WM, Shalter MD (2003) Co-evolution of humans and canids. Evol Cogn 9: 57-72
61. Shamakhi A, Kordbacheh E (2021) Immunoinformatic design of an epitope-based immunogen candidate against Bacillus anthracis. Inform Med Unlocked 24: 100574 doi.org/10.1016/j.imu.2021.100574
62. Shin H, Mally M, Kuhn M, Paroz C, Cornelis GR (2007) Escape from immune surveillance by Capnocytophaga canimorsus. J Infect Dis 195: 375-386 doi.org/10.1086/510243
63. Silva DN, Chrobok M, Ahlén G, Blomberg P, Sällberg M, Pasetto A (2022) ATMP development and pre-GMP environment in academia: a safety net for early cell and gene therapy development and manufacturing. Immuno-Oncol Technol 16: 100099 doi.org/10.1016/j.iotech.2022.100099
64. Sunita, Sajid, A., Singh, Y. and Shukla, P., 2020. Computational tools for modern vaccine development. Hum. Vaccines Immunother. 16: 723-735 doi.org/10.1080/21645515.2019.1670035
65. Teufel F, Almagro Armenteros JJ, Johansen AR, Gíslason MH, Pihl SI, Tsirigos KD, Winther O, Brunak S, von Heijne G, Nielsen H (2022) SignalP 6.0 predicts all five types of signal peptides using protein language models. Nat Biotechnol 40: 1023-1025 doi.org/10.1038/s41587-021-01156-3
66. Umeda K, Suzuki M, Imaoka K (2024) Investigation of antimicrobial susceptibility and resistance gene prevalence in Capnocytophaga spp. isolated from dogs and cats and characterization of novel class A β-lactamase CST-1. Eur J Clin Microbiol Infect Dis 1-11 doi.org/10.1007/s10096-024-05025-0
67. Van Dam AP, Jansz A (2011) Capnocytophaga canimorsus infections in The Netherlands: a nationwide survey. Clin Microbiol Infect 17: 312-315 doi.org/10.1111/j.1469-0691.2010.03195.x
68. Van Samkar A, Brouwer MC, Schultsz C, van der Ende A, van de Beek D (2016) Capnocytophaga canimorsus meningitis: three cases and a review of the literature. Zoonoses Public Health 63: 442-448 doi.org/10.1111/zph.12248
69. Vigne JD, Guilaine J, Debue K, Haye L, Gérard P (2004) Early taming of the cat in Cyprus. Science 304: 259-259 doi.org/10.1126/science.1095335.
70. Vinusha V, Girish C (2024) Discovering vaccines: the trial tale. Naunyn-Schmiedeb. Arch Pharmacol 1-15 doi.org/10.1007/s00210-024-03368-1
71. Wang P, Sidney J, Dow C, Mothé B, Sette A, Peters B (2008) A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Computut Biol 4: 1000048 doi.org/10.1371/journal.pcbi.1000048
72. Wang P, Sidney J, Kim Y, Sette A, Lund O, Nielsen M, Peters B (2010) Peptide binding predictions for HLA DR, DP and DQ molecules. BMC Bioinformatics 11:1-12. doi.org/10.1186/1471-2105-11-568
73. Wang P (2021) Natural and synthetic saponins as vaccine adjuvants vaccines 2021: 9, 222 doi.org/10.3390/vaccines9030222
74. Warimwe GM, Francis MJ, Bowden TA, Thumbi SM, Charleston B (2021) Using cross-species vaccination approaches to counter emerging infectious diseases. Nat Rev Immunol 21: 815-822 doi.org/10.1038/s41577-021-00567-2
75. Yang MC, Ling J, Mosaed S (2021) Capnocytophaga canimorsus blebitis: case report and review of literature. BMC Ophthalmol 21:1-5 doi.org/10.1186/s12886-021-01823-8
76. Yurina V, Adianingsih OR (2022) Predicting epitopes for vaccine development using bioinformatics tools. Ther Adv Vaccines Immunother 10: 25151355221100218 doi.org/10.1177/25151355221100218
77. Zaharieva N, Dimitrov I, Flower DR, Doytchinova I (2019) VaxiJen dataset of bacterial immunogens: an update. Curr Comput-Aided Drug Des 15: 398-400. doi.org/10.2174/1573409915666190318121838
78. Zaharieva N, Dimitrov I, Flower D, Doytchinova I (2017) Immunogenicity prediction by VaxiJen: a ten year overview. J Proteom Bioinform 10: 10-4172 doi.org/10.4172/jpb.1000454
79. Zajkowska J, Król M, Falkowski D, Syed N, Kamieńska A (2016) Capnocytophaga canimorsus–an underestimated danger after dog or cat bite–review of literature. Prz Epidemiol 70: 289-295