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ISSN: 2153-0602
Journal of Data Mining in Genomics & Proteomics
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Microbial Proteomics Approach for Sensitive Quantitative Predictions of MHC Binding Peptide from Taenia Ovis

Gomase VS* and Chitlange NR

Department of Bioinformatics, JJT University, Jhunjhunu, Rajasthan, India

*Corresponding Author:
Gomase VS
Department of Bioinformatics
JJT University, Jhunjhunu
Rajasthan, 333001, India
E-mail: [email protected]

Received date: July 30, 2012; Accepted date: October 25, 2012;Published date: November 02, 2012

Citation: Gomase VS, Chitlange NR (2012) Microbial Proteomics Approach for Sensitive Quantitative Predictions of MHC Binding Peptide from Taenia ovis. J Data Mining Genomics Proteomics 3:121. doi: 10.4172/2153-0602.1000121

Copyright: © 2012 Gomase VS, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Taenia ovis is a tapeworm parasite with the adult stage of the parasite found in the intestines of dogs, while the intermediate or larval stage is found in the muscles of sheep, causes sheep measles. Peptide fragments of antigen protein can be used to select nonamers for use in rational vaccine design, and to increase the understanding of roles of the immune system in infectious diseases. Analysis shows MHC class II binding peptides of antigen protein from Taenia ovis are important determinants for protection of host from parasitic infection. In this assay, we used PSSM and SVM algorithms for antigen design and predicted the binding affinity of antigen protein having 254 amino acids, which shows 246 nonamers. Binding ability prediction of antigen peptides to Major Histocompatibility Complex (MHC) class I & II molecules is important in vaccine development against sheep measles.

Keywords

Cysticercosis; Antigen protein; Epitope; PSSM; SVM; MHC; Peptide vaccine

Abbreviations

MHC: Major Histocompatibility Complex; PSSMs: Position Specific Scoring Matrices; SVM: Support Vector Machine

Introduction

Taenia ovis are the smallest nematode parasite of sheep, are responsible for ovine cysticercosis (Sheep Measles), have an unusual life cycle, and are one of the most widespread and clinically important parasites in the world [1,2]. The small adult worms mature in the intestines of an intermediate host, such as a dog [1,2]. Taenia ovis antigen peptides are most suitable for subunit vaccine development, because with single epitope the immune response can be generated in a large population. This approach is based on the phenomenon of cross-protection, whereby infected with a mild strain and is protected against a more severe strain of the same. The phenotype of the resistant transgenic hosts includes fewer centers of initial infection, a delay in symptom development and low accumulation. Antigen protein from Taenia ovis is necessary for new paradigm of synthetic vaccine development and target validation [3-5].

Pathogen Transmission

The sheep ingests an egg. The egg hatches in the small intestine and the larval tapeworm burrows through the intestinal wall, and travels to the heart and muscles via the blood. The cysticercus develops in the cardiac and skeletal muscles, reaching the infective stage in about 46 days. When the dog eats the sheep and ingests the cysticercus, the protoscolex attaches to the small intestinal wall and the worm begins to form proglottids, and the lifecycle continues.

Methodology

In this research work, antigenic epitopes of antigen protein from Taenia ovis is determined using the Kyte and Doolittle [6], Bull and Breese [7], Parker et al. [8], Chothia [9], Hopp and Woods [10], Welling et al. [11], Manavalan and Ponnuswamy [12], Gomase et al. [13], hydrophobicity scale and Deleage and Roux, Chou and Fasman, Levitt (parameters) have used to predict the probability that a given sequence of amino acids would form a beta strand in antigenic epitopes [6-14]. The Major Histocompatibility Complex (MHC) peptide binding of antigen protein is predicted using neural networks trained on C terminals of known epitopes. In analysis predicted, MHC/peptide binding of antigen protein is a log-transformed value related to the IC50 values in nM units. MHC2 predicts peptide binders to MHCI and MHCII molecules from protein sequences or sequence alignments, using Position Specific Scoring Matrices (PSSMs). Support Vector Machine (SVM) based method for prediction of promiscuous MHC class II binding peptides; SVM has been trained on the binary input of single amino acid sequence [15-20]. In addition, we predict those MHC ligands from whose C-terminal end is likely to be the result of proteosomal cleavage [21-25].

Results and Interpretations

Binding of peptides to a number of different alleles using Position Specific Scoring Matrix have been found through this study. An antigen protein sequence is 254 residues long having antigenic MHC binding peptides. MHC molecules are cell surface glycoproteins, which take active part in host immune reactions and involvement of MHC class-I and MHC II in response to almost all antigens. PSSM based server predict the peptide binders to MHCI molecules of antigen protein sequence which are as 11mer_H2_Db, 10mer_H2_Db, 9mer_H2_Db, 8mer_H2_Db, and also peptide binders to MHCII molecules of antigen protein sequence as I_Ab.p, I_Ad.p; analysis found antigenic epitopes region in putative antigen protein (Table 1). Additionally, SVM based MHCII-IAb peptide regions were also found; MHCII-IAd peptide regions; MHCII-IAg7 peptide regions and MHCII- RT1.B peptide regions were also found, which represented predicted binders from bacterial antigen protein (Table 2). The predicted binding affinity is normalized by the 1% fractal. Through this study, an improved method for predicting linear epitopes has been described (Table 2). The region of maximal hydrophilicity is likely to be an antigenic site, having hydrophobic characteristics (Figure 1-4), because terminal regions of antigen protein is solvent accessible and unstructured; antibodies against those regions are also likely to recognize the native protein (Figure 5-7). It was shown that an antigen protein is hydrophobic in nature and contains segments of low complexity and high-predicted flexibility (Figure 8-10). Predicted antigenic fragments can bind to MHC molecule, and is the first bottlenecks in vaccine design (Figure 1-4).

MHC-I POS. N Sequence C MW Da) Score % OPT.
8mer_H2_Db 129 DTD PMQNCFIW GPV 997.23 16.483 31.40 %
8mer_H2_Db 74 TSD LSNTKTTY AEL 908.99 9.998 19.05 %
8mer_H2_Db 191 VDG LVPDTLYI VTL 915.1 9.447 18.00 %
8mer_H2_Db 40 FTW GPVFSEFI GLN 877.02 7.125 13.57 %
8mer_H2_Db 49 FIG LNWNKDAF HDA 966.09 5.692 10.84 %
8mer_H2_Db 87 LGD GSATLDEL TPN 786.84 5.432 10.35 %
8mer_H2_Db 2 M ASQLCLIL LAT 842.07 5.367 10.22 %
8mer_H2_Db 32 RHQ SLRDIFTW GPV 996.17 3.894 7.42 %
8mer_H2_Db 230 ATV VTTSGSAI VSA 716.78 3.492 6.65 %
8mer_H2_Db 16 AVL ASDYKDTI ERT 893.95 1.852 3.53 %
8mer_H2_Db 93 TLD ELTPNATY LVT 889.96 1.822 3.47 %
8mer_H2_Db 26 IER TVARHQSL RDI 893.01 1.469 2.80 %
8mer_H2_Db 153 QLD PEDTHDMI VTL 939.01 0.403 0.77 %
8mer_H2_Db 113 GNT ILALSSTI HTP 798.98 -0.095 -0.18 %
8mer_H2_Db 239 AIV SAILGLLL TCM 781.01 -0.337 -0.64 %
9mer_H2_Db 48 EFI GLNWNKDAF HDA 1023.14 23.089 45.84 %
9mer_H2_Db 93 TLD ELTPNATYL VTA 1003.12 14.322 28.44 %
10mer_H2_Db 72 VLT SDLSNTKTTY AEL 1111.16 21.688 36.85 %
10mer_H2_Db 92 ATL DELTPNATYL VTA 1118.21 16.58 28.17 %
10mer_H2_Db 125 TPA NDTDPMQNCF IWG 1166.24 10.033 17.05 %
10mer_H2_Db 189 VAV DGLVPDTLYI VTL 1087.24 10.023 17.03 %
10mer_H2_Db 202 VTL TVLKDGRQFF NST 1192.38 7.674 13.04 %
10mer_H2_Db 14 ATA VLASDYKDTI ERT 1106.24 7.079 12.03 %
10mer_H2_Db 75 SDL SNTKTTYAEL GDG 1109.19 5.956 10.12 %
10mer_H2_Db 105 VTA TANISGNTIL ALS 985.09 2.588 4.40 %
10mer_H2_Db 111 ISG NTILALSSTI HTP 1014.18 2.045 3.47 %
10mer_H2_Db 107 ATA NISGNTILAL SST 997.15 1.914 3.25 %
10mer_H2_Db 82 TTY AELGDGSATL DEL 914.97 1.723 2.93 %
10mer_H2_Db 233 VTT SGSAIVSAIL GLL 899.06 0.415 0.71 %
10mer_H2_Db 164 VTL TAETASKPRV ERS 1041.17 0.185 0.31 %
10mer_H2_Db 47 SEF IGLNWNKDAF HDA 1136.3 -0.387 -0.66 %
10mer_H2_Db 37 RDI FTWGPVFSEF IGL 1175.35 -0.697 -1.18 %
10mer_H2_Db 239 AIV SAILGLLLTC MAL 985.25 -0.957 -1.63 %
10mer_H2_Db 85 AEL GDGSATLDEL TPN 958.98 -1.594 -2.71 %
10mer_H2_Db 235 TSG SAIVSAILGL LLT 925.14 -1.977 -3.36 %
11mer_H2_Db 234 TTS GSAIVSAILGL LLT 982.19 9.022 11.35 %
11mer_H2_Db 227 HKE ATVVTTSGSAI VSA 988.09 1.554 1.95 %
11mer_H2_Db 39 IFT WGPVFSEFIGL NWN 1210.44 0.512 0.64 %
11mer_H2_Db 201 IVT LTVLKDGRQFF NST 1305.54 -0.221 -0.28 %
11mer_H2_Db 106 TAT ANISGNTILAL SST 1068.23 -1.84 -2.31 %
11mer_H2_Db 46 FSE FIGLNWNKDAF HDA 1283.48 -2.028 -2.55 %
11mer_H2_Db 188 EVA VDGLVPDTLYI VTL 1186.37 -2.329 -2.93 %
11mer_H2_Db 235 TSG SAIVSAILGLL LTC 1038.3 -2.982 -3.75 %
11mer_H2_Db 236 SGS AIVSAILGLLL TCM 1064.38 -3.416 -4.30 %
11mer_H2_Db 5 ASQ LCLILLATAVL ASD 1124.49 -3.72 -4.68 %
11mer_H2_Db 171 ASK PRVERSESARF TRG 1315.48 -4.096 -5.15 %

Table 1: PSSM based prediction of MHC ligands, from whose C-terminal ends are proteosomal cleavage sites.

MHC ALLELE Rank Sequence Residue No. Peptide Score
I-Ab 1 TASKPRVER 167 0.987
I-Ab 2 TLTAETASK 162 0.856
I-Ab 3 NATYLVTAT 97 0.822
I-Ab 4 RTLXTGHKE 218 0.762
I-Ad 1 MASQLCLIL 1 0.703
I-Ad 2 GSAIVSAIL 234 0.636
I-Ad 3 NATYLVTAT 97 0.632
I-Ad 4 LATAVLASD 10 0.622
I-Ag7 1 FHDAEHEVL 56 1.673
I-Ag7 2 TKTTYAELG 77 1.614
I-Ag7 3 NKDAFHDAE 52 1.591
I-Ag7 4 YLVTATANI 100 1.587
RT1.B 1 TKTTYAELG 77 1.136
RT1.B 2 TTSGSAIVS 231 0.961
RT1.B 3 NTKTTYAEL 76 0.890
RT1.B 4 DGSATLDEL 86 0.836

Table 2: SVM based prediction of promiscuous MHC class II binding peptides from antigen protein.

data-mining-genomics-Hydrophobicity-plot-antigen

Figure 1: Hydrophobicity plot of antigen protein by Hphob/Kyte & Doolittle scale.

data-mining-genomics-plot-antigen-protein

Figure 2: Hydrophobicity plot of antigen protein by Hphob/Bull & Breeze scale.

data-mining-genomics-antigen-protein-Hphob

Figure 3: Hydrophobicity plot of antigen protein by Hphob. HPLC/Parker & et al., scale.

data-mining-genomics-Hphob-Chothia-scale

Figure 4: Hydrophobicity plot of antigen protein by Hphob./Chothia scale.

data-mining-genomics-Hphob-Woods-scale

Figure 5: Hydrophobicity plot of antigen protein by Hphob./Hopp & Woods scale.

data-mining-genomics-Hphob-Welling-scale

Figure 6: Hydrophobicity plot of antigen protein by Hphob./Welling scale.

data-mining-genomics-Hydrophobicity-plot-antigen-protein

Figure 7: Hydrophobicity plot of antigen protein by Hphob./Manavalan et al. scale.

data-mining-genomics-Antigenicity-plot-antigen

Figure 8: Antigenicity plot of antigen protein by alpha-helix/Deleage & Rouxscale.

data-mining-genomics-plot-antigen-protein

Figure 9: Antigenicity plot of antigen protein by beta-turn/Levitt scale.

data-mining-genomics-protein-beta-turn-Chou

Figure 10: Antigenicity plot of antigen protein by beta-turn/Chou & Fasman scale.

Conclusion

An antigen protein from Taenia ovis peptide nonamers are from a set of aligned peptides known to bind to a given MHC molecule as the predictor of MHC-peptide binding. MHCII molecules bind peptides in similar yet different modes, and alignments of MHCII-ligands were obtained to be consistent with the binding mode of the peptides to their MHC class; this means the increase in affinity of MHC binding peptides may result in enhancement of immunogenicity of antigen protein. These predictions of antigen protein, antigenic peptides to MHC class molecules are important in vaccine development from Taenia ovis.

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