Design of an Epitope Candidate Vaccine Against Iha Protein in Escherichia Coli: an in Silico Approach An Epitope Candidate Vaccine Against Escherichia Coli
Journal of "Regeneration, Reconstruction & Restoration" (Triple R),
Vol. 5 (2020),
24 March 2020
Introduction: Iron-regulated outer membrane virulence protein (IrgA) involved in the initial step of iron uptake by binding ferric- iron chelation siderophore that allows the bacterium to extract iron from the environment. IrgA homologue adhesion (Iha) revealed as a novel adherence conferring molecule. In this study, homology modeling, fold recognition and Ab-initio approaches along with their combination were invoked to determine the tertiary structure of Iha.
Material and Methods: Specific bioinformatics methods were used to forecast their immunological, biochemical and functional properties.
Results: The results showed that IrgA constitutes beta barrel structures. The immunological, biochemical and functional analyzes led us to pick a region of every antigen with the highest immunogenic properties. Comparison of antigenicity scores for selected regions and the whole proteins showed that the antigenicity of the selected regions is considerably higher than the whole antigen.
Conclusion: Our strategy for prediction of the 3D structure and epitopes could be deemed as an amenable approach for efficient vaccine design. These approaches used could provide the basis for future functional studies to design and development of a suitable vaccine. In this regard, a region includes residues 200-340, covering a part of barrel, was chosen as vaccine candidate against Iha protein in Escherichia Coli.
- Iron receptor
How to Cite
P.M. Griffin, R.V. Tauxe, The epidemiology of infections caused by Escherichia coli O157: H7, other enterohemorrhagic E. coli, and the associated hemolytic uremic syndrome, Epidemiologic reviews 13(1) (1991) 60-98.
C.S. Edén, U. Jodal, L. Hanson, U. Lindberg, A.S. Åkerlund, Variable adherence to normal human urinary-tract epithelial cells of Escherichia coli strains associated with various forms of urinary-tract infection, The Lancet 308(7984) (1976) 490-492.
A.G. Torres, X. Zhou, J.B. Kaper, Adherence of diarrheagenic Escherichia coli strains to epithelial cells, Infection and immunity 73(1) (2005) 18-29.
R.A. Rashid, P.I. Tarr, S.L. Moseley, Expression of the Escherichia coli IrgA homolog adhesin is regulated by the ferric uptake regulation protein, Microbial pathogenesis 41(6) (2006) 207-217.
P.I. Tarr, S.S. Bilge, J.C. Vary, S. Jelacic, R.L. Habeeb, T.R. Ward, M.R. Baylor, T.E. Besser, Iha: a novel Escherichia coli O157: H7 adherence-conferring molecule encoded on a recently acquired chromosomal island of conserved structure, Infection and immunity 68(3) (2000) 1400-1407.
S. Kanamaru, H. Kurazono, S. Ishitoya, A. Terai, T. Habuchi, M. Nakano, O. Ogawa, S. Yamamoto, Distribution and genetic association of putative uropathogenic virulence factors iroN, iha, kpsMT, ompT and usp in Escherichia coli isolated from urinary tract infections in Japan, The Journal of urology 170(6) (2003) 2490-2493.
R.J. Bauer, L. Zhang, B. Foxman, A. Siitonen, M.E. Jantunen, H. Saxen, C.F. Marrs, Molecular epidemiology of 3 putative virulence genes for Escherichia coli urinary tract infection–usp, iha, and iroNE. coli, Journal of Infectious Diseases 185(10) (2002) 1521-1524.
J.R. Johnson, A.C. Murray, M.A. Kuskowski, S. Schubert, M.-F. Prere, B. Picard, R. Colodner, R. Raz, T.-G.I.f.A.R.A. Investigators, Distribution and characteristics of Escherichia coli clonal group A, Emerging infectious diseases 11(1) (2005) 141.
J.R. Johnson, S. Jelacic, L.M. Schoening, C. Clabots, N. Shaikh, H.L. Mobley, P.I. Tarr, The IrgA homologue adhesin Iha is an Escherichia coli virulence factor in murine urinary tract infection, Infection and immunity 73(2) (2005) 965-971.
A. Jahangiri, I. Rasooli, S.L.M. Gargari, P. Owlia, M.R. Rahbar, J. Amani, S. Khalili, An in silico DNA vaccine against Listeria monocytogenes, Vaccine 29(40) (2011) 6948-6958.
P. Bawono, J. Heringa, PRALINE: a versatile multiple sequence alignment toolkit, Multiple Sequence Alignment Methods, Springer2014, pp. 245-262.
E. Gasteiger, C. Hoogland, A. Gattiker, M.R. Wilkins, R.D. Appel, A. Bairoch, Protein identification and analysis tools on the ExPASy server, The proteomics protocols handbook, Springer2005, pp. 571-607.
I.A. Doytchinova, D.R. Flower, VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines, BMC bioinformatics 8(1) (2007) 4.
F. Sefid, A.A. Bahrami, M. Darvish, R. Nazarpour, Z. Payandeh, In Silico Analysis for Determination and Validation of Iron-Regulated Protein from Escherichia coli, International Journal of Peptide Research and Therapeutics 25(4) (2019) 1523-1537.
C. Geourjon, G. Deleage, SOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments, Bioinformatics 11(6) (1995) 681-684.
L.A. Kelley, S. Mezulis, C.M. Yates, M.N. Wass, M.J. Sternberg, The Phyre2 web portal for protein modeling, prediction and analysis, Nature protocols 10(6) (2015) 845.
K.D. Tsirigos, C. Peters, N. Shu, L. Käll, A. Elofsson, The TOPCONS web server for consensus prediction of membrane protein topology and signal peptides, Nucleic acids research 43(W1) (2015) W401-W407.
A. Krogh, B. Larsson, G. Von Heijne, E.L. Sonnhammer, Predicting transmembrane protein topology with a hidden markov model: application to complete genomes1, Journal of molecular biology 305(3) (2001) 567-580.
H. Viklund, A. Bernsel, M. Skwark, A. Elofsson, SPOCTOPUS: a combined predictor of signal peptides and membrane protein topology, Bioinformatics 24(24) (2008) 2928-2929.
P.G. Bagos, T.D. Liakopoulos, I.C. Spyropoulos, S.J. Hamodrakas, PRED-TMBB: a web server for predicting the topology of β-barrel outer membrane proteins, Nucleic acids research 32(suppl_2) (2004) W400-W404.
T.N. Petersen, S. Brunak, G. Von Heijne, H. Nielsen, SignalP 4.0: discriminating signal peptides from transmembrane regions, Nature methods 8(10) (2011) 785.
C.-C. Chen, J.-K. Hwang, J.-M. Yang, 2-v2: template-based protein structure prediction server, Bmc Bioinformatics 10(1) (2009) 366.
T. Schwede, J. Kopp, N. Guex, M.C. Peitsch, SWISS-MODEL: an automated protein homology-modeling server, Nucleic acids research 31(13) (2003) 3381-3385.
S. Wu, Y. Zhang, LOMETS: a local meta-threading-server for protein structure prediction, Nucleic acids research 35(10) (2007) 3375-3382.
O. Carugo, K. Djinović-Carugo, Half a century of Ramachandran plots, Acta Crystallographica Section D: Biological Crystallography 69(8) (2013) 1333-1341.
D. Xu, Y. Zhang, Improving the physical realism and structural accuracy of protein models by a two-step atomic-level energy minimization, Biophysical journal 101(10) (2011) 2525-2534.
L. Holm, Using Dali for Protein Structure Comparison, Structural Bioinformatics, Springer2020, pp. 29-42.
M.A. Lomize, I.D. Pogozheva, H. Joo, H.I. Mosberg, A.L. Lomize, OPM database and PPM web server: resources for positioning of proteins in membranes, Nucleic acids research 40(D1) (2012) D370-D376.
S.S. Negi, C.H. Schein, N. Oezguen, T.D. Power, W. Braun, InterProSurf: a web server for predicting interacting sites on protein surfaces, Bioinformatics 23(24) (2007) 3397-3399.
T. Kawabata, Detection of multiscale pockets on protein surfaces using mathematical morphology, Proteins: Structure, Function, and Bioinformatics 78(5) (2010) 1195-1211.
J. Dundas, Z. Ouyang, J. Tseng, A. Binkowski, Y. Turpaz, J. Liang, CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues, Nucleic acids research 34(suppl_2) (2006) W116-W118.
K.P. Tan, T.B. Nguyen, S. Patel, R. Varadarajan, M.S. Madhusudhan, Depth: a web server to compute depth, cavity sizes, detect potential small-molecule ligand-binding cavities and predict the pKa of ionizable residues in proteins, Nucleic acids research 41(W1) (2013) W314-W321.
R. Vita, J.A. Overton, J.A. Greenbaum, J. Ponomarenko, J.D. Clark, J.R. Cantrell, D.K. Wheeler, J.L. Gabbard, D. Hix, A. Sette, The immune epitope database (IEDB) 3.0, Nucleic acids research 43(D1) (2014) D405-D412.
S. Saha, G. Raghava, BcePred: prediction of continuous B-cell epitopes in antigenic sequences using physico-chemical properties, International Conference on Artificial Immune Systems, Springer, 2004, pp. 197-204.
M.C. Jespersen, B. Peters, M. Nielsen, P. Marcatili, BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes, Nucleic acids research 45(W1) (2017) W24-W29.
B. Yao, L. Zhang, S. Liang, C. Zhang, SVMTriP: a method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity, PloS one 7(9) (2012) e45152.
M.N. Davies, D.R. Flower, Harnessing bioinformatics to discover new vaccines, Drug discovery today 12(9-10) (2007) 389-395.
J. Ponomarenko, H.-H. Bui, W. Li, N. Fusseder, P.E. Bourne, A. Sette, B. Peters, ElliPro: a new structure-based tool for the prediction of antibody epitopes, BMC bioinformatics 9(1) (2008) 514.
H.W. Bauer, S. Alloussi, G. Egger, H.-M. Blümlein, G. Cozma, C.C. Schulman, M.U.S. Group, A long-term, multicenter, double-blind study of an Escherichia coli extract (OM-89) in female patients with recurrent urinary tract infections, European urology 47(4) (2005) 542-548.
D.T. Uehling, W.J. Hopkins, J.E. Elkahwaji, D.M. Schmidt, G.E. Leverson, Phase 2 clinical trial of a vaginal mucosal vaccine for urinary tract infections, The Journal of urology 170(3) (2003) 867-869.
F. Sefid, I. Rasooli, A. Jahangiri, In silico determination and validation of baumannii acinetobactin utilization a structure and ligand binding site, BioMed research international 2013 (2013).
Z. Payandeh, M. Rajabibazl, Y. Mortazavi, A. Rahimpour, In Silico Analysis for Determination and Validation of Human CD20 Antigen 3D Structure, International Journal of Peptide Research and Therapeutics (2017) 1-13.
G.J. Kleywegt, T.A. Jones, Databases in protein crystallography, Acta Crystallographica Section D: Biological Crystallography 54(6) (1998) 1119-1131.
K. Brillet, C. Reimmann, G.L. Mislin, S. Noël, D. Rognan, I.J. Schalk, D. Cobessi, Pyochelin enantiomers and their outer-membrane siderophore transporters in fluorescent pseudomonads: structural bases for unique enantiospecific recognition, Journal of the American Chemical Society 133(41) (2011) 16503-16509.
J.S. Oakhill, B.J. Sutton, A.R. Gorringe, R.W. Evans, Homology modelling of transferrin-binding protein A from Neisseria meningitidis, Protein Engineering Design and Selection 18(5) (2005) 221-228.
F. Sefid, I. Rasooli, Z. Payandeh, Homology modeling of a Camelid antibody fragment against a conserved region of Acinetobacter baumannii biofilm associated protein (Bap), Journal of theoretical biology 397 (2016) 43-51.
P.G. Bagos, T.D. Liakopoulos, S.J. Hamodrakas, Evaluation of methods for predicting the topology of β-barrel outer membrane proteins and a consensus prediction method, BMC bioinformatics 6(1) (2005) 7.
W. Liu, Y.H. Chen, High epitope density in a single protein molecule significantly enhances antigenicity as well as immunogenicity: a novel strategy for modern vaccine development and a preliminary investigation about B cell discrimination of monomeric proteins, European journal of immunology 35(2) (2005) 505-514.
- Abstract Viewed: 49 times
- PDF Downloaded: 27 times