Enhancing in silico protein-based vaccine discovery for eukaryotic pathogens using predicted peptide-MHC binding and peptide conservation scores

PLoS ONE

Volumn 9, Issue 12, 2014, Pages

  Goodswen, Stephen J ^a   Kennedy, Paul J ^a   Ellis, John T ^a  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID; EPITOPE; MAJOR HISTOCOMPATIBILITY ANTIGEN CLASS 1; MICROBIAL PRODUCTS NOT CLASSIFIED ELSEWHERE; PROTEOME; T LYMPHOCYTE RECEPTOR; TOXOPLASMA GONDII PROTEIN; UNCLASSIFIED DRUG; VACCINE; PEPTIDE; PROTEIN; PROTEIN BINDING; PROTOZOAL VACCINE;

ACCURACY; ALLELE; AMINO ACID SEQUENCE; ANTIGEN BINDING; ANTIGEN PRESENTING CELL; ARTICLE; BINDING AFFINITY; CAENORHABDITIS ELEGANS; CELL MEMBRANE; CELLULAR DISTRIBUTION; CELLULAR IMMUNITY; COMPUTER AIDED DESIGN; COMPUTER PREDICTION; COMPUTER PROGRAM; EUKARYOTE; GENETIC CONSERVATION; HIGH THROUGHPUT SCREENING; HUMORAL IMMUNITY; IC50; LEARNING ALGORITHM; MAJOR HISTOCOMPATIBILITY COMPLEX; MATHEMATICAL ANALYSIS; MOUSE; NONHUMAN; ONLINE SYSTEM; PEPTIDE CONSERVATION SCORE; PLASMODIUM FALCIPARUM; PROTEIN BINDING; PROTEIN LOCALIZATION; PROTEIN SECRETION; RANDOM FOREST; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS; T LYMPHOCYTE; TOXOPLASMA GONDII; VACCINE PRODUCTION; VALIDATION STUDY; ALGORITHM; ARTIFICIAL INTELLIGENCE; BIOLOGY; CHEMISTRY; CLASSIFICATION; COMPUTER SIMULATION; GENE; HUMAN; IMMUNOLOGY; METABOLISM; PARASITOLOGY; PROTEIN DATABASE; TOXOPLASMA;

EUKARYOTA; TOXOPLASMA GONDII;

ALGORITHMS; AMINO ACIDS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATABASES, PROTEIN; EPITOPES, T-LYMPHOCYTE; GENES, MHC CLASS I; HUMANS; PEPTIDES; PROTEIN BINDING; PROTEINS; PROTOZOAN VACCINES; T-LYMPHOCYTES; TOXOPLASMA;

EID: 84920148723     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0115745     Document Type: Article

References (61)

1. Kelly D, Rappuoli R (2005) Reverse Vaccinology and Vaccines for Serogroup B Neisseria meningitidis. In: Pollard A, Finn A, , editors. Hot Topics in Infection and Immunity in Children II. Springer US. pp. 217-223.
2. Leuzzi R, Savino S, Pizza M, Rappuoli R (2006) Genome Mining and Reverse Vaccinology. Handbook of Meningococcal Disease. Wiley-VCH Verlag GmbH & Co. pp. 391-402.
3. Rappuoli R (2001) Reverse vaccinology, a genome-based approach to vaccine development. Vaccine 19: 2688-2691.
4. Serino L, Pizza M, Rappuoli R (2006) Reverse Vaccinology: Revolutionizing the Approach to Vaccine Design. Pathogenomics. Wiley-VCH Verlag GmbH & Co. pp. 533-554.
5. Sette A, Rappuoli R (2010) Reverse Vaccinology: Developing Vaccines in the Era of Genomics. Immunity 33: 530-541.
6. Vivona S, Gardy JL, Ramachandran S, Brinkman FSL, Raghava GPS, et al. (2008) Computer-aided biotechnology: from immuno-informatics to reverse vaccinology. Trends in Biotechnology 26: 190-200.
7. Goodswen SJ, Kennedy PJ, Ellis JT (2013) A guide to in silico vaccine discovery for eukaryotic pathogens. Briefings in Bioinformatics 14: 753-774.
8. Goodswen S, Kennedy P, Ellis J (2013) A novel strategy for classifying the output from an in silico vaccine discovery pipeline for eukaryotic pathogens using machine learning algorithms. BMC Bioinformatics 14: 315.
9. Deavin AJ, Auton TR, Greaney PJ (1996) Statistical comparison of established T-cell epitope predictors against a large database of human and murine antigens. Molecular Immunology 33: 145-155.
10. Rappuoli R (2007) Bridging the knowledge gaps in vaccine design. Nature Biotechnology 25: 1361-1366.
11. Rappuoli R, Ulmer JY (2007) Vaccines research and development: poised for rapid growth. Current Opinion in Biotechnology 18: 521-522.
12. Peters B, Sidney J, Bourne P, Bui HH, Buus S, et al. (2005) The immune epitope database and analysis resource: From vision to blueprint. PLoS Biology 3: 379-381.
13. Ariel N, Zvi A, Grosfeld H, Gat O, Inbar Y, et al. (2002) Search for Potential Vaccine Candidate Open Reading Frames in the Bacillus anthracis Virulence Plasmid pXO1: In Silico and In Vitro Screening. Infection and Immunity 70: 6817-6827.
14. Montigiani S, Falugi F, Scarselli M, Finco O, Petracca R, et al. (2002) Genomic Approach for Analysis of Surface Proteins in Chlamydia pneumoniae. Infection and Immunity 70: 368-379.
15. Ross BC, Czajkowski L, Hocking D, Margetts M, Webb E, et al. (2001) Identification of vaccine candidate antigens from a genomic analysis of Porphyromonas gingivalis. Vaccine 19: 4135-4142.
16. Serruto D, Serino L, Masignani V, Pizza M (2009) Genome-based approaches to develop vaccines against bacterial pathogens. Vaccine 27: 3245-3250.
17. Wizemann TM, Heinrichs JH, Adamou JE, Erwin AL, Kunsch C, et al. (2001) Use of a Whole Genome Approach To Identify Vaccine Molecules Affording Protection against Streptococcus pneumoniae Infection. Infection and Immunity 69: 1593-1598.
18. Che F-Y, Madrid-Aliste C, Burd B, Zhang H, Nieves E, et al. (2010) Comprehensive proteomic analysis of membrane proteins in toxoplasma gondii. Molecular & Cellular Proteomics 10. doi: 10.1074/mcp.M110.000745.
19. Kim K, Weiss LM (2004) Toxoplasma gondii: the model apicomplexan. International Journal for Parasitology 34: 423-432.
20. Roos DS (2005) Themes and variations in apicomplexan parasite biology. Science 309: 72-73.
21. Montoya JG, Liesenfeld O (2004) Toxoplasmosis. The Lancet 363: 1965-1976.
22. Cong H, Mui EJ, Witola WH, Sidney J, Alexander J, et al. (2010) Human immunome, bioinformatic analyses using HLA supermotifs and the parasite genome, binding assays, studies of human T cell responses, and immunization of HLA-A∗1101 transgenic mice including novel adjuvants provide a foundation for HLA-A03 restricted CD8+T cell epitope based, adjuvanted vaccine protective against Toxoplasma gondii. Immunome Research 6: 12.
23. Fatoohi F, Cozon GJN, Wallon M, Kodjlklan L, Peyron F (2006) Systemic T cell response to Toxoplasma gondii antigen in patients with ocular toxoplasmosis. Japanese Journal of Ophthalmology 50: 103-110.
24. Guglietta S, Beghetto E, Spadoni A, Buffolano W, Del Porto P, et al. (2007) Age-dependent impairment of functional helper T cell responses to immunodominant epitopes of Toxoplasma gondii antigens in congenitally infected individuals. Microbes and Infection 9: 127-133.
25. Jordan KA, Wilson EH, Tait ED, Fox BA, Roos DS, et al. (2009) Kinetics and Phenotype of Vaccine-Induced CD8(+) T-Cell Responses to Toxoplasma gondii. Infection and Immunity 77: 3894-3901.
26. Prigione I, Chiesa S, Taverna P, Ceccarelli R, Frulio R, et al. (2006) T cell mediated immune responses to Toxoplasma gondii in pregnant women with primary toxoplasmosis. Microbes and Infection 8: 552-560.
27. Flower DR, Macdonald IK, Ramakrishnan K, Davies MN, Doytchinova IA (2010) Computer aided selection of candidate vaccine antigens. Immunome Research 6 Suppl 2: S1.
28. Cong H, Gu QM, Yin HE, Wang JW, Zhao QL, et al. (2008) Multi-epitope DNA vaccine linked to the A(2)/B subunit of cholera toxin protect mice against Toxoplasma gondii. Vaccine 26: 3913-3921.
29. Cong H, Mui EJ, Witola WH, Sidney J, Alexander J, et al. (2012) Toxoplasma gondii HLA-B∗0702- restricted GRA7(20-28) peptide with adjuvants and a universal helper Tcell epitope elicits CD8(+) Tcells producing interferon-gamma and reduces parasite burden in HLA-B∗0702 mice. Human Immunology 73: 1-10.
30. Cong H, Mui EJ, Witola WH, Sidney J, Alexander J, et al. (2011) Towards an immunosense vaccine to prevent toxoplasmosis: Protective Toxoplasma gondii epitopes restricted by HLA-A∗0201. Vaccine 29: 754-762.
31. Godard I, Estaquier J, Zenner L, Bossus M, Auriault C, et al. (1994) Antigenicity and immunogenicity of P30-derived peptides in experimental models of toxoplasmosis. Molecular Immunology 31: 1353-1363.
32. Nielsen HV, Lauemoller SL, Christiansen L, Buus S, Fomsgaard A, et al. (1999) Complete protection against lethal Toxoplasma gondii infection in mice immunized with a plasmid encoding the SAG1 gene. Infection and Immunity 67: 6358-6363.
33. Tan TG, Mui E, Cong H, Witola WH, Montpetit A, et al. (2010) Identification of T-gondii epitopes, adjuvants, and host genetic factors that influence protection of mice and humans. Vaccine 28: 3977-3989.
34. Yano A, Aosai F, Yang TH, He N, Mun HS, et al. (1997) Correlation between direct binding ability of synthetic T-gondii SAG1 peptides to HLA-A2 measured by a sensor for surface plasmon resonance and antigenicity of the peptides for T-gondii-infected cell-specific CTL. Biochemical and Biophysical Research Communications 236: 257-261.
35. Sacks D, Sher A (2002) Evasion of innate immunity by parasitic protozoa. Nature Immunology 3: 1041-1047.
36. Batchelor JD, Zahm JA, Tolia NH (2011) Dimerization of Plasmodium vivax DBP is induced upon receptor binding and drives recognition of DARC. Nature Structural & Molecular Biology 18: 908-U967.
37. Elsheikha HM, Mansfield LS (2004) Sarcocystis neurona major surface antigen gene 1 (SAG1) shows evidence of having evolved under positive selection pressure. Parasitology Research 94: 452-459.
38. Escobar AJG, Arenas AF, Gomez-Marin JE (2006) Molecular evolution of serine/arginine splicing factors family (SR) by positive selection. In silico biology 6: 347-350.
39. Valizadeh V, Zakeri S, Mehrizi AA, Djadid ND (2014) Population genetics and natural selection in the gene encoding the Duffy binding protein II in Iranian Plasmodium vivax wild isolates. Infection Genetics and Evolution 21: 424-435.
40. Bui H-H, Sidney J, Li W, Fusseder N, Sette A (2007) Development of an epitope conservancy analysis tool to facilitate the design of epitope-based diagnostics and vaccines. BMC Bioinformatics 8.
41. Valdar WSJ (2002) Scoring residue conservation. Proteins-Structure Function and Bioinformatics 48: 227-241.
42. Johansson F, Toh H (2010) A comparative study of conservation and variation scores. BMC Bioinformatics 11.
43. Lin HH, Ray S, Tongchusak S, Reinherz EL, Brusic V (2008) Evaluation of MHC class I peptide binding prediction servers: Applications for vaccine research. BMC Immunology 9.
44. Peters B, Bui H-H, Frankild S, Nielsen M, Lundegaard C, et al. (2006) A community resource benchmarking predictions of peptide binding to MHC-I molecules. PLOS Computational Biology 2: 574-584.
45. Williams TM (2001) Human leukocyte antigen gene polymorphism and the histocompatibility laboratory. Journal of Molecular Diagnostics 3: 98-104.
46. Tong JC, Tan TW, Ranganathan S (2007) Methods and protocols for prediction of immunogenic epitopes. Briefings in Bioinformatics 8: 96-108.
47. Horton P, Park K-J, Obayashi T, Fujita N, Harada H, et al. (2007) WoLF PSORT: protein localization predictor. Nucleic Acids Research 35: W585-W587.
48. Petersen TN, Brunak S, von Heijne G, Nielsen H (2011) SignalP 4.0: discriminating signal peptides from transmembrane regions. Nature Methods 8: 785-786.
49. Emanuelsson O, Brunak S, von Heijne G, Nielsen H (2007) Locating proteins in the cell using TargetP, SignalP and related tools. Nature Protocols 2: 953-971.
50. Krogh A, Larsson B, von Heijne G, Sonnhammer ELL (2001) Predicting transmembrane protein topology with a hidden markov model: application to complete genomes. Journal of Molecular Biology 305: 567-580.
51. Kall L, Krogh A, Sonnhammer ELL (2004) A combined transmembrane topology and signal peptide prediction method. Journal of Molecular Biology 338: 1027-1036.
52. Moutaftsi M, Peters B, Pasquetto V, Tscharke DC, Sidney J, et al. (2006) A consensus epitope prediction approach identifies the breadth of murine TCD8+-cell responses to vaccinia virus. Nature Biotechnology 24: 817-819.
53. Wang P, Sidney J, Dow C, Mothe B, Sette A, et al. (2008) A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLOS Computational Biology 4: e1000048.
54. Nielsen M, Lundegaard C, Worning P, Lauemøller SL, Lamberth K, et al. (2003) Reliable prediction of T-cell epitopes using neural networks with novel sequence representations. Protein Science 12: 1007-1017.
55. Peters B, Sette A (2005) Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinformatics 6: 132.
56. Sidney J, Assarsson E, Moore C, Ngo S, Pinilla C, et al. (2008) Quantitative peptide binding motifs for 19 human and mouse MHC class I molecules derived using positional scanning combinatorial peptide libraries. Immunome Research 4: 2.
57. Hoof I, Peters B, Sidney J, Pedersen LE, Sette A, et al. (2009) NetMHCpan, a method for MHC class I binding prediction beyond humans. Immunogenetics 61: 1-13.
58. Morrison DA (2009) Evolution of the Apicomplexa: where are we now? Trends in Parasitology 25: 375-382.
59. Breiman L (2001) Random forests. Machine Learning 45: 5-32.
60. Platt JC (1999) Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods. Cambridge, MA: MIT Press.
61. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, et al. (2009) BLAST plus: architecture and applications. BMC Bioinformatics 10.