The H1N1 viral strain implicated in the 2009 flupandemic among humans often is called “swine flu” (New York Times, 2009). The 2009 H1N1 virus is not zoonotic swine flu, as it is not transmitted from pigs to humans, but from person to person (Trifonov et al., 2009). Clinical features of H1N1 swine flu are body aches, especially joints and throat, extreme coldness and fever, fatigue, headache, irritated watering and reddened eyes. In children, gastrointestinal symptoms such as diarrhea and abdominal pain may occur (CDC, 2009).

Swine influenza A viruses are RNA viruses with a segmented genome that is comprised of eight negative-sense, single-stranded RNA segments, belong to the viral family of Orthomyxoviridae. These eight segments encode eleven proteins (Brockwell-Staats et al., 2009). The polymerase complex includes the PB2, PB1 and PA proteins as well as the nucleoprotein (NP). There are two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA) (Brockwell-Staats et al., 2009). Swine flu viruses are causing a huge amount of death to both human and swine. The World Health Organization (WHO) figures show that worldwide more than 209 countries and overseas territories or communities have reported laboratory confirmed cases of pandemic influenza H1N1 2009, including at least 15174 deaths (WHO, 2010). Protection against influenza infection is conferred by neutralizing antibody for the two surface proteins, namely the hemagglutinin (HA) and the neuraminidase(NA) (Luke and Subbarao, 2006). It has been difficult to develop a vaccine for H1N1 influenza A virus that provides long lasting immunity. This is due to the antigenic drift of the virus where the circulating strain in an infectious cycle is different from the previously circulating strain (Thomas et al., 2006; Boni et al., 2006). Current inactivated vaccines provide essential protection when the vaccine antigen and the circulating viruses share high degree of similarity in the structural protein. Since new influenza virus antigenic variants emerge frequently from accumulation of point mutations in the structural protein, influenza vaccine antigens need to be updated frequently.

The preparation of a vaccine against H1N1 influenza needs some basic considerations about the working of the H1N1 influenza vaccine. Hemagglutinin protein is responsible for attachment of the virus to the sialic acid α-2,3 or α-2,6 galactose sugar receptor on the human host cell surface (Wan and Perez, 2006). It is reasonable to presume that influenza vaccines do not generate antibodies against the receptor binding region of the protein as this region is not subjected to much antigenic drift which would seriously compromise the infectivity of the virus. In fact, mutation in this region has resulted in change in sugar specificity leading to change of host specificity, and loosing infectivity for the original host species (Wan and Perez, 2006). Antibodies directed against this region therefore are likely to provide protection against the influenza strains.

T cell immunity has been implicated in rapid clearance of influenza virus (Thomas et al., 2006). This means that the individual with good T cell response would suffer from milder form of the disease, get cured sooner, which is reflected in decreased fatality and less spread of the virus in population. Therefore, a vaccine generating robust T cell immunity against influenza needs serious attention. Good T cell immunity along with antibody response focused on receptor binding region of the hemagglutinin protein and enzymatic active site of neuraminidase, would meet the needs of a vaccine. Especially the internal proteins contain many conserved peptides which are potential T cell antigens and hence need serious consideration as T cell focused vaccine candidates.

In this communication, we have computationally analyzed the proteome of H1N1 influenza (A/Minnesota/2009) [NCBI] to identify putative epitopes for the formulation of a vaccine for T cell immunity. This vaccine should cover the HLA haplotype of the target population, be effective against influenza A strains and generate good immune memory response. A variety of computational tools are now available for prediction of T cell epitopes (Korber et al., 2006). We have analyzed overlapping nonameric peptides of all the proteins of H1N1 influenza virus for binding to human HLA class I molecules by PROPRED I algorithm, and for binding to class II alleles by PROPRED algorithm to select peptides for develop a robust T cell vaccine. Synthethic peptides can use as vaccines to induce either humoral or cell mediated immunity requires an understanding of the nature of T cell and B cell epitopes has been reported (Singh and Raghava, 2001; Bhasin et al., 2003; Singh and Raghava, 2003).

Hemagglutinin (ADD21431), neuraminidase (ACQ76351), polymerase PA (ACU13105), Polymerase PB1(ACQ76349), Polymerase PB2(ACQ76350), Nucleocapsid protein (ACR38842), matrix protein (ACU44211) are proteins of H1N1 2009 Minnesota strain have been used for this imminoinformatic analysis. The complete sequences of H1N1 2009 Minnesota strain are available in the NCBI protein database(http://www.ncbi.nlm.nih.gov/). Physicochemical analysis such as molecular weight and isoelectric point (pI) were also analyzed using ExPasy (http://www.expasy.org/)

All the seven structural proteins were analyzed for potential T cell epitope using immunoinformatic tools. Propred and propred I were used to analyse binding of all over lapping peptides to all HLA class I and class II alleles. This tools helped to identify those antigenic determinants peptides in all seven proteins which binds to several HLA molecules with good binding affinity.

All these peptides were predicted on the 4% threshold value with highest binding score with HLA class I and HLA class II molecule. The propred algorithms which predict binding of nonameric peptides to HLA alleles. Those nonameric peptides have highest binding affinity and maximum coverage of HLA alleles were selected.

In order to produce library of H1N1 peptides to determine the antigenic determinants for vaccine design. We analyzed the whole proteome of H1N1 2009 Minnesota strain by propred and propred I immunoinformatic tools. In this study all seven proteins of H1N1 were also analyzed for physicochemical analysis such as molecular weight and isoelectric point. The polymerase PB1 protein and Matrix protein has highest molecular weight (86.35 kDa) and lowest molecular weight (27.82 kDa) respectively. Isoelectric points (pI) of these proteins were ranged between 5.42-9.49 (Table 1). pI value of any protein indicates the stability of proteins in that particular isoelectric points. For predictions of potential T cell antigenic determinants in proteome of H1N1, we took seven putative proteins sequences of H1N1 2009 strain was divided into all possible nonamers. Each peptide undergone for binding analysis with all HLA alleles. Those peptide shown highest binding score and also coverage of maximum number of HLA alleles were selected as potent immunodominant epitopes for vaccine design. Those peptides which have higher affinity for HLA molecules are more likely to be recognized by TCR of specific T cells. Binding specificity of peptides to HLA Class I and Class II molecule by propred I and propred were analyzed at 4% threshold value respectively (Table 2 and Table 3). A total of 15 and 14 peptides were predicted as potent antigenic determinants, presented by HLA class I and II supertypes respectively. Out of these 29 peptides ‘FTTANADTL’ (Hemagglutinin), ‘GQSVVSVKL’ (Neuraminidase) peptides showed maximum binding with HLA class I molecules and for HLA class II molecules maximum binding peptides are ‘VVLLYTFTT’ (Hemagglutinin), ‘MRAIGTHPS’ (Matrix protein) and ‘LRILVRGNS’ (Polymerase PB2).

Table 1: Physicochemical properties of different putative proteins of influenza H1N1.

Table 2: Selected peptides of H1N1 proteome and their HLA class allele coverage (The given peptides are predicted to bind to the depicted HLA class I molecules, PROPRED I~4%).

Table 3: Selected peptides of H1N1 proteome and their allele coverage (The given peptides are predicted to bind to the depicted HLA class II molecules, PROPRED~4%).

Highly immunogenic, cross-conserved epitopes can be designed by carefully overlapping conserved and immunogenic 9-mer sequences found in the influenza strains of interest (De Groot et al., 2009). Computational analysis of proteome of H5N1 avian influenza virus to define T cell epitopes with vaccine potential was evaluated for vaccine potential (Parida et al., 2007). Comparative Sequence Analysis on Different Strains of Swine Influenza Virus Sub-type H1N1 for Neuraminidase and Hemagglutinin was also done (Sharma et al., 2010). Inactivated influenza vaccines elicit neutralizing antibody responses that provide reasonable protection against the homologous H1N1, H3N2, and B viruses (Palese, 2006). However, antibody-mediated selection drives changes (known as antigenic drift) in the viral hemagglutinin and neuraminidase surface glycoproteins, which in turn dictate the frequent production of a new vaccine (Peter, 2008).

Immunoinformatics approaches are currently used for prediction of antigenic determinants in the proteins sequence of influenza virus (H1N1) without using their cultures. The prediction of influenza virus nanomer epitope for T cells is recognized against HLA class I and HLA class II. The predicted epitopes may be served as a useful diagnostic reagent for evaluating T-cell responses in the context of natural infection and also might be helpful for designing of either a DNA vaccine or a subunit vaccine against H1N1influenza.

The authors are grateful to Prof. Ashok Kumar (Dean,I.B.M.E.R, Mangalayatan University Aligarh, U.P, India) for providing necessary facilites and encouragement. The authors are also thankful to all faculty members of the Institute of Biomedical Education and Research, Mangalayatan University Aligarh, U.P, India for their generous help and suggestions during the course of experimental work and manuscript preparation.