Skip to main content
Top
Published in: BMC Immunology 1/2010

Open Access 01-12-2010 | Research article

Using epitope predictions to evaluate efficacy and population coverage of the Mtb72f vaccine for tuberculosis

Authors: Lucy A McNamara, Yongqun He, Zhenhua Yang

Published in: BMC Immunology | Issue 1/2010

Login to get access

Abstract

Background

The Mtb72f subunit vaccine for tuberculosis, currently in clinical trials, is hoped to provide improved protection compared to the current BCG vaccine. It is not clear, however, whether Mtb72f would be equally protective in the different human populations suffering from a high burden of tuberculosis. Previous work by Hebert and colleagues demonstrated that the PPE18 protein of Mtb72f had significant variability in a sample of clinical M. tuberculosis isolates. However, whether this variation might impact the efficacy of Mtb72f in the context of the microbial and host immune system interactions remained to be determined. The present study assesses Mtb72f's predicted efficacy in people with different DRB1 genotypes to predict whether the vaccine will protect against diverse clinical strains of M. tuberculosis in a diverse host population.

Results

We evaluated the binding of epitopes in the vaccine to different alleles of the human DRB1 Class II MHC protein using freely available epitope prediction programs and compared protein sequences from clinical isolates to the sequences included in the Mtb72f vaccine. This analysis predicted that the Mtb72f vaccine would be less effective for several DRB1 genotypes, due either to limited vaccine epitope binding to the DRB1 proteins or to binding primarily by unconserved PPE18 epitopes. Furthermore, we found that these less-protective DRB1 alleles are found at a very high frequency in several populations with a high burden of tuberculosis.

Conclusion

Although the Mtb72f vaccine candidate has shown promise in animal and clinical trials thus far, it may not be optimally effective in some genotypic backgrounds. Due to variation in both M. tuberculosis protein sequences and epitope-binding capabilities of different HLA alleles, certain human populations with a high burden of tuberculosis may not be optimally protected by the Mtb72f vaccine. The efficacy of the Mtb72f vaccine should be further examined in these particular populations to determine whether additional protective measures might be necessary for these regions.
Appendix
Available only for authorised users
Literature
1.
go back to reference Anderson P: Tuberculosis -- an update. Nat Rev Micro. 2007, 5 (7): 484-487. 10.1038/nrmicro1703.CrossRef Anderson P: Tuberculosis -- an update. Nat Rev Micro. 2007, 5 (7): 484-487. 10.1038/nrmicro1703.CrossRef
2.
go back to reference Hoft DF: Tuberculosis vaccine development: goals, immunological design, and evaluation. Lancet. 2008, 372 (9633): 164-175. 10.1016/S0140-6736(08)61036-3.CrossRefPubMed Hoft DF: Tuberculosis vaccine development: goals, immunological design, and evaluation. Lancet. 2008, 372 (9633): 164-175. 10.1016/S0140-6736(08)61036-3.CrossRefPubMed
3.
go back to reference Brennan MJ, Fruth U, Milstien J, Tiernan R, de Andrade Nishioka S, Chocarro L: Development of new tuberculosis vaccines: a global perspective on regulatory issues. PLoS Med. 2007, 4 (8): e252-10.1371/journal.pmed.0040252.PubMedCentralCrossRefPubMed Brennan MJ, Fruth U, Milstien J, Tiernan R, de Andrade Nishioka S, Chocarro L: Development of new tuberculosis vaccines: a global perspective on regulatory issues. PLoS Med. 2007, 4 (8): e252-10.1371/journal.pmed.0040252.PubMedCentralCrossRefPubMed
4.
go back to reference De Groot AS, McMurry J, Marcon L, Franco J, Rivera D, Kutzler M, Weiner D, Martin B: Developing an epitope-driven tuberculosis (TB) vaccine. Vaccine. 2005, 23: 2121-2131. 10.1016/j.vaccine.2005.01.059.CrossRefPubMed De Groot AS, McMurry J, Marcon L, Franco J, Rivera D, Kutzler M, Weiner D, Martin B: Developing an epitope-driven tuberculosis (TB) vaccine. Vaccine. 2005, 23: 2121-2131. 10.1016/j.vaccine.2005.01.059.CrossRefPubMed
5.
go back to reference Skeiky YA, Alderson MR, Ovendale PJ, Guderian JA, Brandt L, Dillon DC, Campos-Neto A, Lobet Y, Dalemans W, Orme IM, et al.,: Differential immune responses and protective efficacy induced by components of a tuberculosis polyprotein vaccine, Mtb72F, delivered as naked DNA or recombinant protein. J Immunol. 2004, 172 (12): 7618-7628.CrossRefPubMed Skeiky YA, Alderson MR, Ovendale PJ, Guderian JA, Brandt L, Dillon DC, Campos-Neto A, Lobet Y, Dalemans W, Orme IM, et al.,: Differential immune responses and protective efficacy induced by components of a tuberculosis polyprotein vaccine, Mtb72F, delivered as naked DNA or recombinant protein. J Immunol. 2004, 172 (12): 7618-7628.CrossRefPubMed
6.
go back to reference Dillon DC, Alderson MR, Day CH, Lewinsohn DM, Coler R, Bement T, Campos-Neto A, Skeiky YA, Orme IM, Roberts A, et al.,: Molecular characterization and human T-cell responses to a member of a novel Mycobacterium tuberculosis mtb39 gene family. Infect Immun. 1999, 67 (6): 2941-2950.PubMedCentralPubMed Dillon DC, Alderson MR, Day CH, Lewinsohn DM, Coler R, Bement T, Campos-Neto A, Skeiky YA, Orme IM, Roberts A, et al.,: Molecular characterization and human T-cell responses to a member of a novel Mycobacterium tuberculosis mtb39 gene family. Infect Immun. 1999, 67 (6): 2941-2950.PubMedCentralPubMed
7.
go back to reference Reed SG, Coler RN, Dalemans W, Tan EV, DeLa Cruz EC, Basaraba RJ, Orme IM, Skeiky YA, Alderson MR, Cowgill KD, et al.,: Defined tuberculosis vaccine, Mtb72F/AS02A, evidence of protection in cynomolgus monkeys. Proc Natl Acad Sci USA. 2009, 106 (7): 2301-2306. 10.1073/pnas.0712077106.PubMedCentralCrossRefPubMed Reed SG, Coler RN, Dalemans W, Tan EV, DeLa Cruz EC, Basaraba RJ, Orme IM, Skeiky YA, Alderson MR, Cowgill KD, et al.,: Defined tuberculosis vaccine, Mtb72F/AS02A, evidence of protection in cynomolgus monkeys. Proc Natl Acad Sci USA. 2009, 106 (7): 2301-2306. 10.1073/pnas.0712077106.PubMedCentralCrossRefPubMed
8.
go back to reference Hebert AM, Talarico S, Yang D, Durmaz R, Marrs CF, Zhang L, Foxman B, Yang Z: DNA polymorphisms in the pepA and PPE18 genes among clinical strains of Mycobacterium tuberculosis: implications for vaccine efficacy. Infect Immun. 2007, 75 (12): 5798-5805. 10.1128/IAI.00335-07.PubMedCentralCrossRefPubMed Hebert AM, Talarico S, Yang D, Durmaz R, Marrs CF, Zhang L, Foxman B, Yang Z: DNA polymorphisms in the pepA and PPE18 genes among clinical strains of Mycobacterium tuberculosis: implications for vaccine efficacy. Infect Immun. 2007, 75 (12): 5798-5805. 10.1128/IAI.00335-07.PubMedCentralCrossRefPubMed
9.
go back to reference Kimman TG, Vandebriel RJ, Hoebee B: Genetic variation in the response to vaccination. Community Genet. 2007, 10 (4): 201-217. 10.1159/000106559.CrossRefPubMed Kimman TG, Vandebriel RJ, Hoebee B: Genetic variation in the response to vaccination. Community Genet. 2007, 10 (4): 201-217. 10.1159/000106559.CrossRefPubMed
10.
go back to reference Gey van Pittius NCSLS, Lee H, Kim Y, van Helden PD, Warren RM: Evolution and expansion of the Mycobacterium tuberculosis PE and PPE multigene families and their association with the duplication of the ESAT-6 (esx) gene cluster regions. BMC Evolutionary Biology. 2006, 6: 95-10.1186/1471-2148-6-95.PubMedCentralCrossRefPubMed Gey van Pittius NCSLS, Lee H, Kim Y, van Helden PD, Warren RM: Evolution and expansion of the Mycobacterium tuberculosis PE and PPE multigene families and their association with the duplication of the ESAT-6 (esx) gene cluster regions. BMC Evolutionary Biology. 2006, 6: 95-10.1186/1471-2148-6-95.PubMedCentralCrossRefPubMed
11.
go back to reference Nielsen M, Lundegaard C, Blicher T, Peters B, Sette A, Justesen S, Buus S, Lund O: Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan. PLoS Comput Biol. 2008, 4 (7): e1000107-10.1371/journal.pcbi.1000107.PubMedCentralCrossRefPubMed Nielsen M, Lundegaard C, Blicher T, Peters B, Sette A, Justesen S, Buus S, Lund O: Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan. PLoS Comput Biol. 2008, 4 (7): e1000107-10.1371/journal.pcbi.1000107.PubMedCentralCrossRefPubMed
12.
go back to reference Lin HH, Ray S, Tongchusak S, Reinherz EL, Brusic V: Evaluation of MHC class I peptide binding prediction servers: Applications for vaccine research. BMC Immunol. 2008, 9 (1): Lin HH, Ray S, Tongchusak S, Reinherz EL, Brusic V: Evaluation of MHC class I peptide binding prediction servers: Applications for vaccine research. BMC Immunol. 2008, 9 (1):
13.
go back to reference Lin HH, Zhang GL, Tongchusak S, Reinherz EL, Brusic V: Evaluation of MHC-II peptide binding prediction servers: applications for vaccine research. BMC Bioinformatics. 2008, 9 (Suppl 12): S22-10.1186/1471-2105-9-S12-S22.PubMedCentralCrossRefPubMed Lin HH, Zhang GL, Tongchusak S, Reinherz EL, Brusic V: Evaluation of MHC-II peptide binding prediction servers: applications for vaccine research. BMC Bioinformatics. 2008, 9 (Suppl 12): S22-10.1186/1471-2105-9-S12-S22.PubMedCentralCrossRefPubMed
14.
go back to reference Gowthaman U, Agrewala JN: In Silico Tools for Predicting Peptides Binding to HL-Class II Molecules: More Confusion than Conclusion. J Proteome Res. 2008, 7 (1): 154-163. 10.1021/pr070527b.CrossRefPubMed Gowthaman U, Agrewala JN: In Silico Tools for Predicting Peptides Binding to HL-Class II Molecules: More Confusion than Conclusion. J Proteome Res. 2008, 7 (1): 154-163. 10.1021/pr070527b.CrossRefPubMed
15.
go back to reference Wang P, Sidney J, Dow C, Mothe B, Sette A, Peters B: A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Comput Biol. 2008, 4 (4): e1000048-10.1371/journal.pcbi.1000048.PubMedCentralCrossRefPubMed Wang P, Sidney J, Dow C, Mothe B, Sette A, Peters B: A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Comput Biol. 2008, 4 (4): e1000048-10.1371/journal.pcbi.1000048.PubMedCentralCrossRefPubMed
16.
go back to reference Trost B, Bickis M, Kusalik A: Strength in numbers: achieving greater accuracy in MHC-I binding prediction by combining the results from multiple prediction tools. Immunome Res. 2007, 3: 5-10.1186/1745-7580-3-5.PubMedCentralCrossRefPubMed Trost B, Bickis M, Kusalik A: Strength in numbers: achieving greater accuracy in MHC-I binding prediction by combining the results from multiple prediction tools. Immunome Res. 2007, 3: 5-10.1186/1745-7580-3-5.PubMedCentralCrossRefPubMed
17.
go back to reference Wang Y, Smith JA, Kamradt T, Gefter ML, Perkins DL: Silencing of immunodominant epitopes by contiguous sequences in complex synthetic peptides. Cell Immunol. 1992, 143 (2): 284-297. 10.1016/0008-8749(92)90026-L.CrossRefPubMed Wang Y, Smith JA, Kamradt T, Gefter ML, Perkins DL: Silencing of immunodominant epitopes by contiguous sequences in complex synthetic peptides. Cell Immunol. 1992, 143 (2): 284-297. 10.1016/0008-8749(92)90026-L.CrossRefPubMed
18.
go back to reference Bloom BR, Fine PEM: The BCG experience: implications for future vaccines against tuberculosis. Tuberculosis: protection, pathogenesis, and control. 1994, Washington, DC: ASM PressCrossRef Bloom BR, Fine PEM: The BCG experience: implications for future vaccines against tuberculosis. Tuberculosis: protection, pathogenesis, and control. 1994, Washington, DC: ASM PressCrossRef
19.
go back to reference Fleischmann R, Alland D, Eisen J, Carpenter L, White O, Peterson J, DeBoy R, Dodson R, Gwinn M, Haft D, et al.,: Whole-genome comparion of Mycobacterium tuberculosis clinical and laboratory strains. J Bacteriol. 2002, 184 (19): 5479-5490. 10.1128/JB.184.19.5479-5490.2002.PubMedCentralCrossRefPubMed Fleischmann R, Alland D, Eisen J, Carpenter L, White O, Peterson J, DeBoy R, Dodson R, Gwinn M, Haft D, et al.,: Whole-genome comparion of Mycobacterium tuberculosis clinical and laboratory strains. J Bacteriol. 2002, 184 (19): 5479-5490. 10.1128/JB.184.19.5479-5490.2002.PubMedCentralCrossRefPubMed
20.
go back to reference Ribeiro-Guimaraes ML, Pessolani MCV: Comparative genomics of mycobacterial proteases. Microbial Pathogenesis. 2007, 43: 173-178. 10.1016/j.micpath.2007.05.010.CrossRefPubMed Ribeiro-Guimaraes ML, Pessolani MCV: Comparative genomics of mycobacterial proteases. Microbial Pathogenesis. 2007, 43: 173-178. 10.1016/j.micpath.2007.05.010.CrossRefPubMed
21.
go back to reference Bui HH, Sidney J, Li W, Fusseder N, Sette A: Development of an epitope conservancy analysis tool to facilitate the design of epitope-based diagnostics and vaccines. BMC Bioinformatics. 2007, 8: 361-10.1186/1471-2105-8-361.PubMedCentralCrossRefPubMed Bui HH, Sidney J, Li W, Fusseder N, Sette A: Development of an epitope conservancy analysis tool to facilitate the design of epitope-based diagnostics and vaccines. BMC Bioinformatics. 2007, 8: 361-10.1186/1471-2105-8-361.PubMedCentralCrossRefPubMed
22.
go back to reference McMurry J, Sbai H, Gennaro ML, Carter EJ, Martin W, De Groot AS: Analyzing Mycobacterium tuberculosis proteomes for candidate vaccine epitopes. Tuberculosis (Edinb). 2005, 85 (1-2): 95-105. 10.1016/j.tube.2004.09.005.CrossRef McMurry J, Sbai H, Gennaro ML, Carter EJ, Martin W, De Groot AS: Analyzing Mycobacterium tuberculosis proteomes for candidate vaccine epitopes. Tuberculosis (Edinb). 2005, 85 (1-2): 95-105. 10.1016/j.tube.2004.09.005.CrossRef
23.
go back to reference Reche PA, Glutting JP, Reinherz EL: Prediction of MHC class I binding peptides using profile motifs. Hum Immunol. 2002, 63 (9): 701-709. 10.1016/S0198-8859(02)00432-9.CrossRefPubMed Reche PA, Glutting JP, Reinherz EL: Prediction of MHC class I binding peptides using profile motifs. Hum Immunol. 2002, 63 (9): 701-709. 10.1016/S0198-8859(02)00432-9.CrossRefPubMed
24.
go back to reference Shams H, Klucar P, Weis SE, Lalvani A, Moonan PK, Safi H, Wizel B, Ewer K, Nepom GT, Lewinsohn DM, et al.,: Characterization of a Mycobacterium tuberculosis peptide that is recognized by human CD4+ and CD8+ T cells in the context of multiple HLA alleles. J Immunol. 2004, 173 (3): 1966-1977.CrossRefPubMed Shams H, Klucar P, Weis SE, Lalvani A, Moonan PK, Safi H, Wizel B, Ewer K, Nepom GT, Lewinsohn DM, et al.,: Characterization of a Mycobacterium tuberculosis peptide that is recognized by human CD4+ and CD8+ T cells in the context of multiple HLA alleles. J Immunol. 2004, 173 (3): 1966-1977.CrossRefPubMed
26.
go back to reference Organization WH: Global tuberculosis control - epidemiology, strategy, financing. 2009, Geneva: Wolrd HealthOrganization, 411- Organization WH: Global tuberculosis control - epidemiology, strategy, financing. 2009, Geneva: Wolrd HealthOrganization, 411-
27.
go back to reference Weichold FF, Mueller S, Kortsik C, Hitzler WE, Wulf MJ, Hone DM, Sadoff JC, Maeurer MJ: Impact of MHC class I alleles on the M. tuberculosis antigen-specific CD8+ T-cell response in patients with pulmonary tuberculosis. Genes Immun. 2007, 8 (4): 334-343. 10.1038/sj.gene.6364392.CrossRefPubMed Weichold FF, Mueller S, Kortsik C, Hitzler WE, Wulf MJ, Hone DM, Sadoff JC, Maeurer MJ: Impact of MHC class I alleles on the M. tuberculosis antigen-specific CD8+ T-cell response in patients with pulmonary tuberculosis. Genes Immun. 2007, 8 (4): 334-343. 10.1038/sj.gene.6364392.CrossRefPubMed
28.
go back to reference Blythe MJ, Zhang Q, Vaughan K, de Castro R, Salimi N, Bui HH, Lewinsohn DM, Ernst JD, Peters B, Sette A: An analysis of the epitope knowledge related to Mycobacteria. Immunome Res. 2007, 3: 10-10.1186/1745-7580-3-10.PubMedCentralCrossRefPubMed Blythe MJ, Zhang Q, Vaughan K, de Castro R, Salimi N, Bui HH, Lewinsohn DM, Ernst JD, Peters B, Sette A: An analysis of the epitope knowledge related to Mycobacteria. Immunome Res. 2007, 3: 10-10.1186/1745-7580-3-10.PubMedCentralCrossRefPubMed
29.
go back to reference Contini S, Pallante M, Vejbaesya S, Park MH, Chierakul N, Kim HS, Saltini C, Amicosante M: A model of phenotypic susceptibility to tuberculosis: deficient in silico selection of Mycobacterium tuberculosis epitopes by HLA alleles. Sarcoidosis Vasc Diffuse Lung Dis. 2008, 25 (1): 21-28.PubMed Contini S, Pallante M, Vejbaesya S, Park MH, Chierakul N, Kim HS, Saltini C, Amicosante M: A model of phenotypic susceptibility to tuberculosis: deficient in silico selection of Mycobacterium tuberculosis epitopes by HLA alleles. Sarcoidosis Vasc Diffuse Lung Dis. 2008, 25 (1): 21-28.PubMed
30.
go back to reference Sturniolo T, Bono E, Ding J, Raddrizzani L, Tuereci O, Sahin U, Braxenthaler M, Gallazzi F, Protti MP, Sinigaglia F, et al.,: Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices. Nat Biotechnol. 1999, 17 (6): 555-561. 10.1038/9858.CrossRefPubMed Sturniolo T, Bono E, Ding J, Raddrizzani L, Tuereci O, Sahin U, Braxenthaler M, Gallazzi F, Protti MP, Sinigaglia F, et al.,: Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices. Nat Biotechnol. 1999, 17 (6): 555-561. 10.1038/9858.CrossRefPubMed
31.
go back to reference Liu W, Meng X, Xu Q, Flower DR, Li T: Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models. BMC Bioinformatics. 2006, 7: 182-10.1186/1471-2105-7-182.PubMedCentralCrossRefPubMed Liu W, Meng X, Xu Q, Flower DR, Li T: Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models. BMC Bioinformatics. 2006, 7: 182-10.1186/1471-2105-7-182.PubMedCentralCrossRefPubMed
32.
go back to reference Wan J, Liu W, Xu Q, Ren Y, Flower DR, Li T: SVRMHC prediction server for MHC-binding peptides. BMC Bioinformatics. 2006, 7: 463-10.1186/1471-2105-7-463.PubMedCentralCrossRefPubMed Wan J, Liu W, Xu Q, Ren Y, Flower DR, Li T: SVRMHC prediction server for MHC-binding peptides. BMC Bioinformatics. 2006, 7: 463-10.1186/1471-2105-7-463.PubMedCentralCrossRefPubMed
33.
go back to reference Guan P, Doytchinova IA, Zygouri C, Flower DR: MHCPred: A server for quantitative prediction of peptide-MHC binding. Nucleic Acids Res. 2003, 31 (13): 3621-3624. 10.1093/nar/gkg510.PubMedCentralCrossRefPubMed Guan P, Doytchinova IA, Zygouri C, Flower DR: MHCPred: A server for quantitative prediction of peptide-MHC binding. Nucleic Acids Res. 2003, 31 (13): 3621-3624. 10.1093/nar/gkg510.PubMedCentralCrossRefPubMed
34.
go back to reference Guan P, Doytchinova IA, Zygouri C, Flower DR: MHCPred: bringing a quantitative dimension to the online prediction of MHC binding. Appl Bioinformatics. 2003, 2 (1): 63-66.PubMed Guan P, Doytchinova IA, Zygouri C, Flower DR: MHCPred: bringing a quantitative dimension to the online prediction of MHC binding. Appl Bioinformatics. 2003, 2 (1): 63-66.PubMed
35.
go back to reference Hattotuwagama CK, Guan P, Doytchinova IA, Zygouri C, Flower DR: Quantitative online prediction of peptide binding to the major histocompatibility complex. J Mol Graph Model. 2004, 22 (3): 195-207. 10.1016/S1093-3263(03)00160-8.CrossRefPubMed Hattotuwagama CK, Guan P, Doytchinova IA, Zygouri C, Flower DR: Quantitative online prediction of peptide binding to the major histocompatibility complex. J Mol Graph Model. 2004, 22 (3): 195-207. 10.1016/S1093-3263(03)00160-8.CrossRefPubMed
36.
go back to reference Cui J, Han LY, Lin HH, Tang ZQ, Jiang L, Cao ZW, Chen YZ: MHC-BPS: MHC-binder prediction server for identifying peptides of flexible lengths from sequence-derived physicochemical properties. Immunogenetics. 2006, 58 (8): 607-613. 10.1007/s00251-006-0117-2.CrossRefPubMed Cui J, Han LY, Lin HH, Tang ZQ, Jiang L, Cao ZW, Chen YZ: MHC-BPS: MHC-binder prediction server for identifying peptides of flexible lengths from sequence-derived physicochemical properties. Immunogenetics. 2006, 58 (8): 607-613. 10.1007/s00251-006-0117-2.CrossRefPubMed
37.
go back to reference Nielsen M, Lundegaard C, Lund O: Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinformatics. 2007, 4;8: 238-10.1186/1471-2105-8-238.CrossRef Nielsen M, Lundegaard C, Lund O: Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinformatics. 2007, 4;8: 238-10.1186/1471-2105-8-238.CrossRef
38.
go back to reference Loffredo JT, Sidney J, Piaskowski S, Szymanski A, Furlott J, Rudersdorf R, Reed J, Peters B, Hickman-Miller HD, Bardet W, et al.,: The high frequency Indian rhesus macaque MHC class I molecule, Mamu-B*01, does not appear to be involved in CD8+ T lymphocyte responses to SIVmac239. J Immunol. 2005, 175 (9): 5986-5997.CrossRefPubMed Loffredo JT, Sidney J, Piaskowski S, Szymanski A, Furlott J, Rudersdorf R, Reed J, Peters B, Hickman-Miller HD, Bardet W, et al.,: The high frequency Indian rhesus macaque MHC class I molecule, Mamu-B*01, does not appear to be involved in CD8+ T lymphocyte responses to SIVmac239. J Immunol. 2005, 175 (9): 5986-5997.CrossRefPubMed
39.
go back to reference Lian W, Juan L, Fei L: Prediction of MHC Class II Binding Peptides Using a Multi-Objective evolutionary Algorithm. International Conference on Computational Intelligence and Security: 2007. 2007, 101-104. full_text.CrossRef Lian W, Juan L, Fei L: Prediction of MHC Class II Binding Peptides Using a Multi-Objective evolutionary Algorithm. International Conference on Computational Intelligence and Security: 2007. 2007, 101-104. full_text.CrossRef
40.
go back to reference Xiang ZaYH: Vaxign: a web-based vaccine target design program for reverse vaccinology. Porcedia in Vaccinology. 2009, 1: 1-7. 10.1016/j.provac.2009.07.001.CrossRef Xiang ZaYH: Vaxign: a web-based vaccine target design program for reverse vaccinology. Porcedia in Vaccinology. 2009, 1: 1-7. 10.1016/j.provac.2009.07.001.CrossRef
42.
go back to reference Bui HH, Sidney J, Peters B, Sathiamurthy M, Sinichi A, Purton KA, Mothe BR, Chisari FV, Watkins DI, Sette A: Automated generation and evaluation of specific MHC binding predictive tools: ARB matrix applications. Immunogenetics. 2005, 57 (5): 304-314. 10.1007/s00251-005-0798-y.CrossRefPubMed Bui HH, Sidney J, Peters B, Sathiamurthy M, Sinichi A, Purton KA, Mothe BR, Chisari FV, Watkins DI, Sette A: Automated generation and evaluation of specific MHC binding predictive tools: ARB matrix applications. Immunogenetics. 2005, 57 (5): 304-314. 10.1007/s00251-005-0798-y.CrossRefPubMed
45.
go back to reference Singh H, Raghava GP: ProPred: prediction of HLA-DR binding sites. Bioinformatics. 2001, 17 (12): 1236-1237. 10.1093/bioinformatics/17.12.1236.CrossRefPubMed Singh H, Raghava GP: ProPred: prediction of HLA-DR binding sites. Bioinformatics. 2001, 17 (12): 1236-1237. 10.1093/bioinformatics/17.12.1236.CrossRefPubMed
46.
go back to reference Reche PA, Glutting JP, Zhang H, Reinherz EL: Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles. Immunogenetics. 2004, 56 (6): 405-419. 10.1007/s00251-004-0709-7.CrossRefPubMed Reche PA, Glutting JP, Zhang H, Reinherz EL: Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles. Immunogenetics. 2004, 56 (6): 405-419. 10.1007/s00251-004-0709-7.CrossRefPubMed
52.
go back to reference Kim HS, Park MH, Song EY, Park H, Kwon SY, Han SK, Shim YS: Association of HLA-DR and HLA-DQ genes with susceptibility to pulmonary tuberculosis in Koreans: preliminary evidence of associations with drug resistance, disease severity, and disease recurrence. Hum Immunol. 2005, 66 (10): 1074-1081. 10.1016/j.humimm.2005.08.242.CrossRefPubMed Kim HS, Park MH, Song EY, Park H, Kwon SY, Han SK, Shim YS: Association of HLA-DR and HLA-DQ genes with susceptibility to pulmonary tuberculosis in Koreans: preliminary evidence of associations with drug resistance, disease severity, and disease recurrence. Hum Immunol. 2005, 66 (10): 1074-1081. 10.1016/j.humimm.2005.08.242.CrossRefPubMed
53.
go back to reference Lombard Z, Dalton DL, Venter PA, Williams RC, Bornman L: Association of HLA-DR, -DQ, and vitamin D receptor alleles and haplotypes with tuberculosis in the Venda of South Africa. Hum Immunol. 2006, 67 (8): 643-654. 10.1016/j.humimm.2006.04.008.CrossRefPubMed Lombard Z, Dalton DL, Venter PA, Williams RC, Bornman L: Association of HLA-DR, -DQ, and vitamin D receptor alleles and haplotypes with tuberculosis in the Venda of South Africa. Hum Immunol. 2006, 67 (8): 643-654. 10.1016/j.humimm.2006.04.008.CrossRefPubMed
54.
go back to reference Ravikumar M, Dheenadhayalan V, Rajaram K, Lakshmi SS, Kumaran PP, Paramasivan CN, Balakrishnan K, Pitchappan RM: Associations of HLA-DRB1, DQB1 and DPB1 alleles with pulmonary tuberculosis in south India. Tuber Lung Dis. 1999, 79 (5): 309-317. 10.1054/tuld.1999.0213.CrossRefPubMed Ravikumar M, Dheenadhayalan V, Rajaram K, Lakshmi SS, Kumaran PP, Paramasivan CN, Balakrishnan K, Pitchappan RM: Associations of HLA-DRB1, DQB1 and DPB1 alleles with pulmonary tuberculosis in south India. Tuber Lung Dis. 1999, 79 (5): 309-317. 10.1054/tuld.1999.0213.CrossRefPubMed
55.
go back to reference Sriram U, Selvaraj P, Kurian SM, Reetha AM, Narayanan PR: HLA-DR2 subtypes & immune responses in pulmonary tuberculosis. Indian J Med Res. 2001, 113: 117-124.PubMed Sriram U, Selvaraj P, Kurian SM, Reetha AM, Narayanan PR: HLA-DR2 subtypes & immune responses in pulmonary tuberculosis. Indian J Med Res. 2001, 113: 117-124.PubMed
Metadata
Title
Using epitope predictions to evaluate efficacy and population coverage of the Mtb72f vaccine for tuberculosis
Authors
Lucy A McNamara
Yongqun He
Zhenhua Yang
Publication date
01-12-2010
Publisher
BioMed Central
Published in
BMC Immunology / Issue 1/2010
Electronic ISSN: 1471-2172
DOI
https://doi.org/10.1186/1471-2172-11-18

Other articles of this Issue 1/2010

BMC Immunology 1/2010 Go to the issue
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.