Cell mediated immune response plays a key role in combating viral infection and thus identification of new vaccine targets manifesting T cell mediated response may serve as an ideal approach for influenza vaccine. The present study involves the application of an immunoinformatics-based consensus approach for epitope prediction (three epitope prediction tools each for CD4+ and CD8+ T cell epitopes) and molecular docking to identify peptide sequences containing T cell epitopes using the conserved sequences from all the Matrix 1 protein sequences of H1N1 virus available until April 2015. Three peptides comprising CD4+ and CD8+ T cell epitopes were obtained, which were not exactly reported in earlier studies. Population coverage study of these multi-epitope peptides revealed that they are capable of inducing a potent immune response belonging to individuals from different populations and ethnicity distributed around the globe. Conservation study with other subtypes of influenza virus infecting humans (H2N2, H5N1, H7N9, and H3N2) revealed that these three peptides were conserved (>90%), with 100% identity in most of these strains. Hence, these peptides can impart immunity against H1N1 as well as other subtypes of influenza virus. A molecular docking study of the predicted peptides with class I and II human leukocyte antigen (HLA) molecules has shown that the majority of them have comparable binding energies to that of native peptides. Hence, these peptides from Matrix 1 protein of H1N1 appear to be promising candidates for universal vaccine design.
Get full access to this article
View all access options for this article.
References
1.
AlbertsB, JohnsonA, LewisJ, et al.Molecular Biology of the Cell. 4th ed. New York: Garland Science, 2002.
2.
AltschulSF, GishW, MillerW, et al.Basic local alignment search tool. J Mol Biol, 1990; 215:403–410.
3.
AntrobusRD, BerthoudTK, MullarkeyCE, et al.Coadministration of seasonal influenza vaccine and MVA-NP+M1 simultaneously achieves potent humoral and cell-mediated responses. Mol Ther, 2014; 22:233–238.
4.
AssarssonE, BuiHH, SidneyJ, et al.Immunomic analysis of the repertoire of T-cell specificities for influenza A virus in humans. J Virol, 2008; 82:12241–12251.
5.
AtanasovaM, DimitrovI, FlowerDR, et al.HLA class II binding prediction by molecular docking. Mol Inf, 2011; 30:368–375.
6.
BuiHH, SidneyJ, DinhK, et al.Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinformatics, 2006; 7:153.
7.
BlumenshineP, ReingoldA, EgerterS, et al.Pandemic influenza planning in the United States from a health disparities perspective. Emerg Infect Dis, 2008; 14:709–715.
8.
BurleighLM, CalderLJ, SkehelJJ, et al.Influenza a viruses with mutations in the M1 helix six domain display a wide variety of morphological phenotypes. J Virol, 2005; 79:1262–1270.
9.
ChavesFA, LeeAH, NayakJL, et al.The utility and limitations of current Web-available algorithms to predict peptides recognized by CD4 T cells in response to pathogen infection. J Immunol, 2012; 188:4235–4248.
10.
ChenCL, XiaoL, ZhouYP, et al.Ethnic differences in susceptibilities to A(H1N1) flu: an epidemic parameter indicating a weak viral virulence. Afr J Biotechnol, 2009; 8:7379–7382.
11.
ChenF, ZhaiMX, ZhuYH, et al.In vitro and in vivo identification of a novel cytotoxic T lymphocyte epitope from Rv3425 of Mycobacterium tuberculosis. Microbiol Immunol, 2012; 56:548–553.
12.
ChoiJG, KimMC, KangHM, et al.Protective efficacy of baculovirus-derived influenza virus-like particles bearing H5 HA alone or in combination with M1 in chickens. Vet Microbiol, 2013; 162:623–630.
13.
DoytchinovaIA, and FlowerDR. In silico identification of supertypes for class II HLAs. J Immunol, 2005; 174:7085–7095.
14.
DuvvuriVR, DuvvuriB, AliceC, et al.Preexisting CD4+ T-cell immunity in human population to avian influenza H7N9 virus: whole proteome-wide immunoinformatics analyses. PLoS One, 2014; 9:e91273.
15.
DuvvuriVR, DuvvuriB, JamnikV, et al.T cell memory to evolutionarily conserved and shared hemagglutinin epitopes of H1N1 viruses: a pilot scale study. BMC Infect Dis, 2013; 13:204–215.
16.
DuvvuriVR, Marchand-AustinA, EshaghiA, et al.Potential T cell epitopes within swine-origin triple reassortant influenza A (H3N2) variant virus which emerged in 2011: an immunoinformatics study. Vaccine, 2012; 30:6054–6063.
17.
EdgarRC. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics, 2004; 5:113–131.
18.
FujiyoshiY, KumeNP, SakataK, et al.Fine structure of influenza A virus observed by electron cryo-microscopy. EMBO J, 1994; 13:318–326.
19.
GianfraniC, OseroffC, SidneyJ, et al.Human memory CTL response specific for influenza A virus is broad and multispecific. Hum Immunol, 2000; 61:438–452.
20.
GideonHP, WilkinsonKA, RustadTR, et al.Bioinformatic and empirical analysis of novel hypoxia-inducible targets of the human antituberculosis T cell response. J Immunol, 2012; 189:5867–5876.
21.
GustianandaM. Immunoinformatics analysis of H5N1 proteome for designing an epitope-derived vaccine and predicting the prevalence of pre-existing cellular-mediated immunity toward bird flu virus in Indonesian population. Immunome Res, 2011; 7:1–11.
22.
HamadaH, BassityE, FliesA, et al.Multiple redundant effector mechanisms of CD8+ T cells protect against influenza infection. J Immunol, 2013; 190:296–306.
23.
HouY, GuoY, WuC, et al.Prediction and identification of T cell epitopes in the H5N1 influenza virus nucleoprotein in chicken. PLoS One, 2012; 7:e39344.
24.
KhanMK, ZamanS, ChakrabortyS, et al.In silico predicted mycobacterial epitope elicits in vitro T-cell responses. Mol Immunol, 2014; 61:16–22.
25.
KhuranaS, SuguitanALJr, RiveraY, et al.Antigenic fingerprinting of H5N1 avian influenza using convalescent sera and monoclonal antibodies reveals potential vaccine and diagnostic targets. PLoS Med, 2009; 6:e1000049.
26.
LarsenMV, LundegaardC, LamberthK, et al.Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction. BMC Bioinformatics, 2007; 8:424–435.
27.
LohiaN, and BaranwalM. Conserved peptides containing overlapping CD4+ and CD8+ T-cell epitopes in the H1N1 influenza virus: an immunoinformatics approach. Viral Immunol, 2014; 27:225–234.
28.
MiottoO, HeinyA, TanTW, et al.Identification of human-to-human transmissibility factors in PB2 proteins of influenza A by large-scale mutual information analysis. BMC Bioinformatics, 2008; 9:S18.
29.
MoutaftsiM, PetersB, PasquettoV, et al.A consensus epitope prediction approach identifies the breadth of murine T (CD8+)-cell responses to vaccinia virus. Nat Biotechnol, 2006; 24:817–819.
30.
NavaranjanD, RosellaLC, KwongJC, et al.Ethnic disparities in acquiring 2009 pandemic H1N1 influenza: a case-control study. BMC Public Health, 2014; 14:214–223.
31.
NaylorPH, EganJE, and BerinsteinNL. Peptide based vaccine approaches for cancer-a novel approach using a WT-1 synthetic long peptide and the IRX-2 immunomodulatory regimen. Cancers (Basel), 2011; 3:3991–4009.
32.
NielsenM, and LundO. NN-align. An artificial neural network-based alignment algorithm for HLA class II peptide binding prediction. BMC Bioinformatics, 2009; 10:296–305.
33.
NielsenM, LundegaardC, and LundO. Prediction of HLA class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinformatics, 2007; 8:238–249.
34.
ParkerKC, BednarekMA, and ColiganJE. Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains. J Immunol, 1994; 152:163–175.
35.
PatronovA, DimitrovI, FlowerDR, et al.Peptide binding prediction for the human class II HLA allele HLA-DP2: a molecular docking approach. BMC Str Biol, 2011; 11:32–41.
36.
PereiraBA, SilvaFS, RebelloKM, et al.In silico predicted epitopes from the COOH-terminal extension of cysteine proteinase B inducing distinct immune responses during Leishmania (Leishmania) amazonensis experimental murine infection. BMC Immunol, 2011; 12:44–55.
37.
PurcellAW, McCluskeyJ, and RossjohnJ. More than one reason to rethink the use of peptides in vaccine design. Nat Rev Drug Discov, 2007; 6:404–414.
RammenseeH, BachmannJ, EmmerichNP, et al.SYFPEITHI: database for HLA ligands and peptide motifs. Immunogenetics, 1999; 50:213–209.
40.
SafoMK, MusayevFN, MosierPD, et al.Crystal structures of influenza A virus matrix protein M1: variations on a theme. PLoS One, 2014; 9:e109510.
41.
SeyedN, ZahedifardF, SafaiyanS, et al.In silico analysis of six Leishmania major antigens and in vitro evaluation of specific epitopes eliciting HLA-A2 restricted CD8 T cell response. PLoS Negl Trop Dis, 2011; 5:e1295.
42.
SidneyJ, PetersB, FrahmN, et al.HLA class I supertypes: a revised and updated classification. BMC Immunol, 2008; 9:1–15.
43.
SinghH, and RaghavaGP. ProPred: prediction of HLA-DR binding sites. Bioinformatics, 2001; 17:1236–1237.
44.
SubathraM, SanthakumarP, Satyam NaiduS, et al.Expression of avian influenza virus (H5N1) hemagglutinin and matrix protein 1 in Pichia pastoris and evaluation of their immunogenicity in mice. Appl Biochem Biotechnol, 2014; 172:3635–3645.
45.
SuiZ, ChenQ, FangF, et al.Cross-protection against influenza virus infection by intranasal administration of M1-based vaccine with chitosan as an adjuvant. Vaccine, 2010; 28:7690–7698.
46.
SunY, LiuJ, YangM, et al.Identification and structural definition of H5-specific CTL epitopes restricted by HLA-A*0201 derived from the H5N1 subtype of influenza A viruses. J Gen Virol, 2010; 91:919–930.
47.
TerajimaM, and EnnisFA. Nuclear export signal and immunodominant CD8+ T cell epitope in influenza A virus matrix protein 1. J Virol, 2012; 86:10258.
48.
ThevenetP, ShenY, MaupetitJ, et al.PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptides. Nucleic Acids Res, 2012; 40:W288–293.
49.
TrottO, and OlsonAJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. J Comput Chem, 2010; 31:455–461.
50.
WangW, LiR, DengY, et al.Protective Efficacy of the Conserved NP, PB1, and M1 Proteins as Immunogens in DNA- and Vaccinia Virus-Based Universal Influenza A Virus Vaccines in Mice. Clin Vaccine Immunol, 2015; 22:618–630.
51.
WeiK, ChenY, LinY, et al.Genetic dynamic analysis of the influenza A H5N1 NS1 gene in China. PLoS One, 2014; 9:e101384.
WiseHM, HutchinsonEC, JaggerBW, et al.Identification of a novel splice variant form of the influenza A virus M2 ion channel with an antigenically distinct ectodomain. PLoS Pathog, 2012; 8:e1002998.
54.
WoodlandDL. Antibody responses to influenza a virus infection. Viral Immunol, 2014; 27:367.
55.
WoodlandDL, HoganRJ, and ZhongW. Cellular immunity and memory to respiratory virus infections. Immunol Res, 2001; 24:53–67.
56.
YangP, WangW, GuH, et al.Protection against influenza H7N9 virus challenge with a recombinant NP-M1-HSP60 protein vaccine construct in BALB/c mice. Antiviral Res, 2014; 111:1–7.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
