Skip to main content
SpringerLink
Log in

Bioinformatics Approach to Analyze Influenza Viruses

  • Conference paper
  • First Online:
Applied Computer Sciences in Engineering (WEA 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 916))

Included in the following conference series:

Abstract

Influenza viruses are highly contagious respiratory illness and responsible for the severe annual morbidity and mortality worldwide. They are classified into types, influenza A, B and C. Influenza viruses accumulate point mutations during replication, especially in three proteins: matrix-membrane, hemagglutinin, and neuraminidase. Nucleotide and amino acid variations may produce selective advantages for viral strains, in the matrix-membrane and neuraminidase may be related to eluding host immunity, while variations in the hemagglutinin are responsible for the appearance of antigenic drift that evade preexisting host immunity and cause reinfections. In this paper, we present a bioinformatics study for detecting mutations implicated in variability in the hemagglutinin, neuraminidase and matrix-membrane of influenza strains using our bioinformatics tool BMA. In this study, we calculate, compare, and analyze genetic variations associated with antigenic drift in hemagglutinin protein from influenza A H1N1. BMA allows users to identify mutations in sequences quickly and efficiently for the detection of antigenic drift.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://bma.itiud.org/.

  2. 2.

    https://www.ncbi.nlm.nih.gov/genbank/.

  3. 3.

    http://platform.gisaid.org/.

  4. 4.

    https://pymol.org/2/.

References

  1. Lamb, R.A.: Orthomyxoviridae: the viruses and their replication. In: Fields Virology (2001)

    Google Scholar 

  2. Obenauer, J.C., et al.: Large-scale sequence analysis of avian influenza isolates. Science 311(5767), 1576–1580 (2006)

    Article  Google Scholar 

  3. Osterhaus, A., Rimmelzwaan, G., Martina, B., Bestebroer, T., Fouchier, R.: Influenza B virus in seals. Science 288(5468), 1051–1053 (2000)

    Article  Google Scholar 

  4. Youzbashi, E., Marschall, M., Chaloupka, I., Meier-Ewert, H.: Distribution of influenza C virus infection in dogs and pigs in Bavaria. Tierarztl. Prax. 24(4), 337–342 (1996)

    Google Scholar 

  5. Webster, R.G., Bean, W.J., Gorman, O.T., Chambers, T.M., Kawaoka, Y.: Evolution and ecology of influenza A viruses. Microbiol. Rev. 56(1), 152–179 (1992)

    Google Scholar 

  6. Centers for Disease Control and Prevention (CDC), et al.: Update: influenza activity-united states and worldwide, 1999–2000 season, and composition of the 2000–01 influenza vaccine. MMWR Morb. Mortal. Wkly. Rep. 49(17), 375 (2000)

    Google Scholar 

  7. Treanor, J.J.: Influenza vaccination. N. Engl. J. Med. 375(13), 1261–1268 (2016). PMID: 27682035

    Article  Google Scholar 

  8. Barbey-Martin, C., et al.: An antibody that prevents the hemagglutinin low pH fusogenic transition. Virology 294(1), 70–74 (2002)

    Article  Google Scholar 

  9. Matrosovich, M.N., Matrosovich, T.Y., Gray, T., Roberts, N.A., Klenk, H.D.: Neuraminidase is important for the initiation of influenza virus infection in human airway epithelium. J. Virol. 78(22), 12665–12667 (2004)

    Article  Google Scholar 

  10. Yen, H.L., et al.: Importance of neuraminidase active-site residues to the neuraminidase inhibitor resistance of influenza viruses. J. Virol. 80(17), 8787–8795 (2006)

    Article  Google Scholar 

  11. Lamb, R.A., Lai, C.J., Choppin, P.W.: Sequences of mRNAs derived from genome RNA segment 7 of influenza virus: colinear and interrupted mRNAs code for overlapping proteins. Proc. Natl. Acad. Sci. 78(7), 4170–4174 (1981)

    Article  Google Scholar 

  12. Furuse, Y., Suzuki, A., Kamigaki, T., Oshitani, H.: Evolution of the M gene of the influenza A virus in different host species: large-scale sequence analysis. Virol. J. 6(1), 67 (2009)

    Article  Google Scholar 

  13. Eyer, L., Hruska, K., et al.: Antiviral agents targeting the influenza virus: a review and publication analysis. Vet. Med. 58(3), 113–185 (2013)

    Article  Google Scholar 

  14. Bloom, J.D., Gong, L.I., Baltimore, D.: Permissive secondary mutations enable the evolution of influenza oseltamivir resistance. Science 328(5983), 1272–1275 (2010)

    Article  Google Scholar 

  15. McKimm-Breschkin, J.L., et al.: Generation and characterization of variants of NWS/G70C influenza virus after in vitro passage in 4-amino-Neu5Ac2en and 4-guanidino-Neu5Ac2en. Antimicrob. Agents Chemother. 40(1), 40–46 (1996)

    Article  Google Scholar 

  16. Yang, P., Bansal, A., Liu, C., Air, G.M.: Hemagglutinin specificity and neuraminidase coding capacity of neuraminidase-deficient influenza viruses. Virology 229(1), 155–165 (1997)

    Article  Google Scholar 

  17. Blick, T.J., et al.: The interaction of neuraminidase and hemagglutinin mutations in influenza virus in resistance to 4-guanidino-Neu5Ac2en. Virology 246(1), 95–103 (1998)

    Article  Google Scholar 

  18. Hensley, S.E., et al.: Hemagglutinin receptor binding avidity drives influenza A virus antigenic drift. Science 326(5953), 734–736 (2009)

    Article  Google Scholar 

  19. Medina, R.A.: 1918 influenza virus: 100 years on, are we prepared against the next influenza pandemic? Nat. Rev. Microbiol. 16(2), 61–62 (2018)

    Article  Google Scholar 

  20. Salvatierra, K., Florez, H.: Biomedical mutation analysis (BMA): a software tool for analyzing mutations associated with antiviral resistance. F1000Research 5 (2016)

    Article  Google Scholar 

  21. Salvatierra, K., Florez, H.: Pathogen sequence signature analysis (PSSA): a software tool for analyzing sequences to identify microorganism genotypes. F1000Research 6 (2017)

    Google Scholar 

  22. Salvatierra, K., Florez, H.: Analysis of hepatitis C virus in hemodialysis patients. Infectio 20(3), 130–137 (2016)

    Article  Google Scholar 

  23. Salvatierra, K., Florez, H.: Prevalence of hepatitis B and C infections in hemodialysis patients. F1000Research 5 (2016)

    Article  Google Scholar 

  24. Florez, H., Salvatierra, K.: A web-based approach for analyzing microorganism sequences. In: Figueroa-García, J.C., López-Santana, E.R., Villa-Ramírez, J.L., Ferro-Escobar, R. (eds.) WEA 2017. CCIS, vol. 742, pp. 96–107. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-66963-2_10

    Chapter  Google Scholar 

  25. Florez, H., Salvatierra, K.: Bioinformatics study of mutations of resistance to antivirals in the NS5A Gen of HCV. Information 20(9), 6665–6672 (2017)

    Google Scholar 

  26. Paessler, S., Veljkovic, V.: Using electronic biology based platform to predict flu vaccine efficacy for 2018/2019. F1000Research 7 (2018)

    Article  Google Scholar 

Download references

Acknowledgment

Authors are grateful for the support received from the Information Technologies Innovation Research Group.

Author information

Authors and Affiliations

  1. Universidad Nacional de Misiones, Posadas, Argentina

    Karina Salvatierra

  2. Universidad Distrital Francisco Jose de Caldas, Bogotá, Colombia

    Hector Florez

Authors
  1. Karina Salvatierra
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hector Florez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hector Florez .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Juan Carlos Figueroa-García

  2. Department of Industrial Engineering, University of Antioquia, Medellín, Colombia

    Juan G. Villegas

  3. Department of Electronics and Telecomunications Engineering, University of Antioquia, Medellín, Colombia

    Juan Rafael Orozco-Arroyave

  4. Department of Industrial Engineering, University of Antioquia, Medellín, Colombia

    Pablo Andres Maya Duque

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Salvatierra, K., Florez, H. (2018). Bioinformatics Approach to Analyze Influenza Viruses. In: Figueroa-García, J., Villegas, J., Orozco-Arroyave, J., Maya Duque, P. (eds) Applied Computer Sciences in Engineering. WEA 2018. Communications in Computer and Information Science, vol 916. Springer, Cham. https://doi.org/10.1007/978-3-030-00353-1_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-00353-1_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00352-4

  • Online ISBN: 978-3-030-00353-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation