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The Vaxign Documentation

     In the post-genomic era, strategies of vaccine development have progressed dramatically from traditional Pasteur’s principles of isolating, inactivating and injecting the causative agent of an infectious disease, to reverse vaccinology that starts from bioinformatics analysis of the genome information. Vaxign is the first web-based vaccine design software program freely available for the purpose of facilitating reverse vaccinology.

Vaxign Publications:  

     He Y, Xiang Z, Mobley HLT. Vaxign: the first web-based vaccine design program for reverse vaccinology and an application for vaccine development. Journal of Biomedicine and Biotechnology. In press.

     Xiang Z, He Y. 2009. Vaxign: a web-based vaccine target design program for reverse vaccinology. Procedia in Vaccinology. Volume 1, Issue 1, Pages 23-29.

     Paper citing Vaxign:
     McNamara L, He Y, Yang Z. Using epitope predictions to evaluate efficacy and population coverage of the Mtb72f vaccine for tuberculosis. BMC Immunology. 2010 Mar 30;11(1):18. [PMID: 20353587] [Journal Link]

Vaxign Pipeline for Vaccine Target Prediction: 

     Vaxign includes a pipeline of software programs to predict possible vaccine targets based on various vaccine design criteria using microbial genomic and protein sequences as input data. The predicted features in the Vaxign pipeline include antigen sublocation, adhesion, epitope binding to MHC class I and class II, and sequence similarities to human and/or mouse proteins. This pipeline integrates both existing open source tools and an internally developed program (Vaxitope) with user-friendly web interfaces. Vaxign predicts vaccine targets based on protein sequences at a genome level or using individual protein sequences. This pipeline includes the following steps:

1. Subcellular localization: Surface-exposed proteins such as outer membrane proteins (esp. adhesins) and secreted proteins are usually ideal targets for vaccine developments. Non-surface proteins such as cytoplasmic/inner membrane proteins may not be good targets for vaccine development.
2. Topology and Transmembrane helices: It is very difficult to clone, express, and purify proteins with more than one transmembrane spanning region. Therefore, it might be better to ignore those proteins with multiple transmembrane spaaning regions in the first place.
3. Adhesin probability: Adhesins are often good vaccine targets.
4. Epitope prediction: This step predicts both MHC class I and class II binding epitopes using Vaxitope, an internally developed program.
5. Similarity to host genome sequences: A vaccine candidate with similar sequence to the host (e.g., human, mouse) is likely to cause autoimmunity in the host.

Open-Source Software Programs/Databases used in Vaxign and their Licenses:

1. PSORTb: PSORTb (v.2.0) is probably the most precise bacterial localization prediction tool. PSORTb is under the GNU General Public Licence (GNU GPL).
2. TMHMM: Prediction of transmembrane helices in proteins. TMHMM is uder Academic Software License Agreement.
3. SPAAN: Prediction of adhesins and adhesin-like proteins. According to the SPAAN publication, the SPAAN program is freely available.
4. BLAST: NCBI sequence similarity alignment and analysis program. BLAST is a USA NCBI program within the public domain.
5. IEDB: The Immune Epitope Database and Analysis Resource. The immune epitope data obtained from IEDB is used for training Vaxitope, our epitope prediction program. Please check the IEDB Term of Use.

Parameters/Options for Consideration and Filteration:

     Our automatic Vaxign pipeline allows users to select and/or modify the following parameters:

1. Subcellular localization: Please select the localizations you wish to include. Default setting includes (1) Cell Wall, (2) Cytoplasmic, (3) Cytoplasmic Membrane, (4) Extracellular, (5) Out Membrane, (6) Periplasmic, (7) Unknown, and (8) Any Localization (default choice). Please see more details in the PSORTb help page.
2. Transmembrane helices: Please enter maximum number of transmembrane helices. Default value is 1 (link to TMHMM help page).
3. Adhesin probability: Please specify the minimum value of adhesin. Default value is 0.51 (Sachdeva et al.).
4. No similarity to human proteins: Check this option if you wish to exclude any protein that shows any similarity to a human protein.
5. No similarity to mouse proteins: Check this option if you wish to exclude any protein that shows any similarity to a mouse protein.

Introduction of Vaxitope:

     Vaxitope is an MHC Class I and II binding epitope prediction tool developed in Dr. Yonggqun "Oliver" He's laboratory. Vaxitope is a position specific scoring matrice (PSSM)-based epitope prediction program. Vaxitope relies on statistical P value (instead of a percentage or top number) as the cutoff. Our studies indicate that the P value of 0.05 provides a cutoff with high and balanced sensitivity and specificity. Vaxitope also allows genome-wide query on different MHC host species. To evaluate the performance of Vaxitope, a receiver operating characteristic (ROC) curve was generated using HLA A*0201 specific PSSM. The result is shown below. The value of the Area Under the ROC Curve (AUC) of 0.929. The positive and negative testing dataset was obtained from http://mhcbindingpredictions.immuneepitope.org/dataset.html. The positive HLA A*0201 aelles were used to calculate the True Positive Rate (Sensitivity). The negative alleles were used to calculate the False Postive Rate (1-Specificity).

     The ROC AUCs for Other Alleles are also calculated and provided for users' reference. Overall, Vaxitope is a very specific and sensitive method for MHC Class I and II binding epitope prediction.

Selected References:

1. Rappuoli R. Reverse vaccinology. Curr Opin Microbiol. 2000 Oct;3(5):445-50. Review. PMID: 11050440.
   
2. Gardy JL, Laird MR, Chen F, Rey S, Walsh CJ, Ester M, Brinkman FS. PSORTb v.2.0: expanded prediction of bacterial protein subcellular localization and insights gained from comparative proteome analysis. Bioinformatic. 2005 Mar 1;21(5):617-23. PMID: 15501914.
3. Käll L, Krogh A, Sonnhammer EL. An HMM posterior decoder for sequence feature prediction that includes homology information. Bioinformatics. 2005 Jun;21 Suppl 1:i251-7. PMID: 15961464.
4. Sachdeva G, Kumar K, Jain P, Ramachandran S. SPAAN: a software program for prediction of adhesins and adhesin-like proteins using neural networks. Bioinformatics. 2005 Feb 15;21(4):483-91. PMID: 15374866.
5. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic Local Alignment Search Tool. J Mol Biol 215:403-410; 1990. PMID: 2231712.
6. Peters B, Sidney J, Bourne P, Bui HH, Buus S, Doh G, Fleri W, Kronenberg M, Kubo R, Lund O, Nemazee D, Ponomarenko JV, Sathiamurthy M, S choenberger S, Stewart S, Surko P, Way S, Wilson S, Sette A. The immune epitope database and analysis resource: from vision to blueprint. PLoS Biol. 2005 Mar;3(3):e91. PMID: 15760272.
   

Links:

1. AntiJen: A database containing quantitative binding data for peptides binding to MHC Ligand, TCR-MHC Complexes, T Cell Epitope, TAP, B Cell Epitope molecules and immunological Protein-Protein interactions.
2. Bcipep: A database of B cell epitopes.
3. IEDB Analysis Resource: A list of IEDB epitope prediction and anlaysis tools.
4. JenPep: A database of quantitative binding data for immunological protein-peptide interactions.
5. RANKPEP: A web-based computational program for prediction of binding peptides to Calss I & II MHC molecules.