A Coding Theoretical Approach to Predict Sequence Changes in H5N1 Influenza A Virus Hemagglutinin

Keiko Sato, Toshihide Hara, Masanori Ohya

2016

Abstract

The changes in the receptor binding domain of influenza A virus hemagglutinin lead to the appearance of new viral strains that evade the immune system. To prepare the future emergence of potentially dangerous outbreaks caused by divergent influenza strains including human-adapted H5N1 strains, it is imperative that we understand the rule stored in the sequence of the receptor binding domain. Information of life is stored as a sequence of nucleotides, and the sequence composed of four nucleotides seems to be a code. It is important to determine the code structure of the sequences. Once we know the code structure, we can make use of mathematical results concerning coding theory for research in life science. In this study, we applied various codes in coding theory to sequence analysis of the 220 loop in the receptor binding domain of H1, H3, H5 and H7 subtype viruses isolated from humans. Sequence diversity in the 220 loop has been observed even within the same hemagglutinin subtype. However, we found that the code structure of the 220 loop from the same subtype remains unchanged. Our results indicate that the sequences at the 220 loop have the structure of subtype-specific codes. In addition, in view of these finding, we predicted possible amino acid changes in the 220 loop of H5N1 strains that will emerge in the future. Our method will facilitate understanding of the evolutionary patterns of influenza A viruses, and further help the development of new antiviral drugs and vaccines.

References

  1. Bright, R.-A. et al., 2003, Impact of glycosylation on the immunogenicity of a DNA-based influenza H5 HA vaccine. Virology, 308, 270-278.
  2. Chen, M.-W. et al., 2011, Broadly neutralizing DNA vaccine with specific mutation alters the antigenicity and sugar-binding activities of influenza hemagglutinin, Proceedings of the National Academy of Sciences, 108, 3510-3515.
  3. Das, P. et al., 2009, Free energy simulations reveal a double mutant avian H5N1 virus hemagglutinin with altered receptor binding specificity, J. Comput. Chem., 30, 1654-1663.
  4. de Vries, R.-P. et al., 2013, Evolution of the hemagglutinin protein of the new pandemic H1N1 influenza virus: maintaining optimal receptor binding by compensatory substitutions. J. Virol., 87, 13868- 13877.
  5. de Vries, R.-P. et al., 2014, Hemagglutinin receptor specificity and Structural Analyses of Respiratory Droplet-transmissible H5N1 Viruses. J. Virol., 88, 768-773.
  6. Durand, L.-O. et al., 2015, Timing of Influenza A(H5N1) in Poultry and Humans and Seasonal Influenza Activity Worldwide, 2004-2013, Emerg. Infect. Dis., 21, 202-208.
  7. Imai, M. et al., 2012, Experimental adaptation of an influenza H5 HA confers respiratory droplet transmission to a reassortant H5 HA/H1N1 virus in ferrets, Nature, 486, 420-428.
  8. Jiang, S. et al., 2012, Receptor-binding domains of spike proteins of emerging or re-emerging viruses as targets for development of antiviral vaccines, Emerging Microbes & Infections, 1, e13.
  9. Katoh, K. and Toh, H., 2008. Recent developments in the MAFFT multiple sequence alignment program, Brief. Bioinform., 9, 286-298.
  10. Khurana, S. et al., 2011, Bacterial HA1 vaccine against pandemic H5N1 influenza virus: evidence of oligomerization, hemagglutination, and crossprotective immunity in ferrets, J. Virol., 85, 1246- 1256.
  11. McCullough, C. et al., 2012, Characterization of influenza hemagglutinin interactions with receptor by NMR, PloS one, 7, e33958.
  12. Ohya, M. and Sato, K., 2000, Use of information theory to study genome sequences. Reports on Mathematical Physics, 46, 419-428.
  13. Olsen, B. et al., 2006, Global patterns of influenza A virus in wild birds. Science, 312, 384-388.
  14. Pfeiffer, D.-U. et al., 2011, Implications of global and regional patterns of highly pathogenic avian influenza virus H5N1 clades for risk management, Vet. J., 190, 309-316.
  15. Rumschlag-Booms, E. and Rong, L., 2013, Influenza a virus entry: implications in virulence and future therapeutics, Advances in virology, 2013, 121924.
  16. Sato, K. et al., 2013, The code structure of the p53 DNAbinding domain and the prognosis of breast cancer patients. Bioinformatics, 29, 2822-2825.
  17. Schrauwen, E.-J., 2014, Host adaptation and transmission of influenza A viruses in mammals. Emerg. Microbes Infect., 3, e9.
  18. Stevens, J. et al., 2006, Structure and receptor specificity of the hemagglutinin from an H5N1 influenza. Science, 312, 404-410.
  19. Xu, Q. et al., 2010, Influenza H1N1 A/Solomon Island/3/06 virus receptor binding specificity correlates with virus pathogenicity, antigenicity, and immunogenicity in ferrets. J. Virol., 84, 4936-4945.
  20. Yamamoto, N. et al., 2011, Characterization of a nonpathogenic H5N1 influenza virus isolated from a migratory duck flying from Siberia in Hokkaido, Japan, in October 2009. Virol. J., 8, 65.
  21. Yen, H.-L. and Peiris, J.-S., 2012, Virology: bird flu in mammals, Nature, 486, 332-333.
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Paper Citation


in Harvard Style

Sato K., Hara T. and Ohya M. (2016). A Coding Theoretical Approach to Predict Sequence Changes in H5N1 Influenza A Virus Hemagglutinin . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 159-167. DOI: 10.5220/0005659701590167


in Bibtex Style

@conference{bioinformatics16,
author={Keiko Sato and Toshihide Hara and Masanori Ohya},
title={A Coding Theoretical Approach to Predict Sequence Changes in H5N1 Influenza A Virus Hemagglutinin},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)},
year={2016},
pages={159-167},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005659701590167},
isbn={978-989-758-170-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)
TI - A Coding Theoretical Approach to Predict Sequence Changes in H5N1 Influenza A Virus Hemagglutinin
SN - 978-989-758-170-0
AU - Sato K.
AU - Hara T.
AU - Ohya M.
PY - 2016
SP - 159
EP - 167
DO - 10.5220/0005659701590167