Computational Methods for Electron Tomography of Influenza Virus

  • Younes Benkarroum
  • Paul Gottlieb
  • Al Katz
  • Stuart W. Rowland
  • Doris Bucher
  • Gabor T. Herman
Part of the Applied and Numerical Harmonic Analysis book series (ANHA)


Influenza is a rapidly changing virus that appears seasonally in the human population. Every year a new strain of the influenza virus appears with the potential to cause a serious global pandemic. Knowledge of the structure and density of the surface proteins is of critical importance in a vaccine candidate. Reconstruction techniques from a series of tilted electron-tomographic projection images provide quantification of surface proteins. Two major categories of reconstruction techniques are transform methods such as weighted backprojection (WBP) and series expansion methods such as the algebraic reconstruction techniques (ART) and the simultaneous iterative reconstruction technique (SIRT). Series expansion methods aim at estimating the object to be reconstructed by a linear combination of some fixed basis functions and they typically estimate the coefficients in such an expansion by an iterative algorithm. The choice of the set of basis functions greatly influences the result of a series expansion method. It has been demonstrated repeatedly that using spherically symmetric basis functions (blobs), instead of the more traditional voxels, results in reconstructions of superior quality, provided that the free parameters that occur in the definition of the family of blobs are appropriately tuned. In this chapter, it is demonstrated that, with the recommended data-processing steps performed on the projection images prior to reconstruction, series expansion methods such as ART (with its free parameters appropriately tuned) will provide 3D reconstructions of viruses from tomographic tilt series that allow reliable quantification of the surface proteins and that the same is not achieved using WBP.


Influenza Virus Projection Image Line Integral Algebraic Reconstruction Technique Tilt Axis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The work presented here is currently supported by the National Science Foundation award number DMS-1114901. The authors are grateful to Joachim Frank, Carlos Óscar Sanchez Sorzano, José-María Carazo, and especially Hstau Liao for their advice and help with producing filtered WBP reconstructions.


  1. 1.
    Arranz R, Coloma R, Chichón FJ, Conesa JJ, Carrascosa JL, Valpuesta JM, Ortin J, Martin-Benito J (2012) The structure of native influenza virion ribonucleoproteins. Science 338: 1634–1637CrossRefGoogle Scholar
  2. 2.
    Bucher DJ, Kharitonenkov IG, Zakomirdin J, Grigoriev VB, Klimenko SM, Davis JF(1980) Incorporation of influenza virus M-protein into liposomes. J Virol 36:586–590Google Scholar
  3. 3.
    Burmeister WP, Ruigrok RW, Cusack S (1992) The 2.2 Å resolution crystal structure of influenza B neuraminidase and its complex with sialic acid. EMBO J 11:49–56Google Scholar
  4. 4.
    Calder LJ, Wasilewski S, Berriman JA, Rosenthal PB (2010) Structural organization of a filamentous influenza A virus. Proc Natl Acad Sci 107:10685–10690CrossRefGoogle Scholar
  5. 5.
    Carazo JM, Herman GT, Sorzano COS, Marabini R (2006) Algorithms for thee-dimensional reconstruction from the imperfect projection data provided by electron microscopy. In: Frank J (ed) Electron tomography: Methods for three-dimensional visualization of structures in the cell, 2nd edn. Springer, New York, pp 217–244CrossRefGoogle Scholar
  6. 6.
    Chen J, Lee KH, Steinhauer DA, Stevens DJ, Skehel JJ, Wiley DC (1998) Structure of the hemagglutinin precursor cleavage site, a determinant of influenza pathogenicity and the origin of the labile conformation. Cell 95:409–417CrossRefGoogle Scholar
  7. 7.
    DuBois RM, Zaraket H, Reddivari M, Heath RJ, White SW, Russell CJ (2011) Acid stability of the hemagglutinin protein regulates H5N1 influenza virus pathogenicity. PLoS Pathog 7:e1002,398Google Scholar
  8. 8.
    Farnsworth A, Cyr TD, Li C, Wang J, Li X (2011) Antigenic stability of H1N1 pandemic vaccines correlates with vaccine strain. Vaccine 29:1529–1533CrossRefGoogle Scholar
  9. 9.
    Fidler DP (2010) Negotiating equitable access to influenza vaccines: Global health diplomacy and the controversies surrounding avian influenza H5N1 and pandemic influenza H1N1. PLoS Med 7:e1000,247Google Scholar
  10. 10.
    Fouchier RA, Garcia-Sastre A, Kawaoka Y (2012a) Pause on avian flu transmission studies. Nature 481:443–443CrossRefGoogle Scholar
  11. 11.
    Fouchier RA, Garcia-Sastre A, Kawaoka Y, Barclay WS, Bouvier NM, Brown IH (2012b) Pause on avian flu transmission research. Science 335:400–401CrossRefGoogle Scholar
  12. 12.
    Frank J (2006a) Electron tomography: Methods for three-dimensional visualization of structures in the cell, 2nd edn. Springer, New YorkCrossRefGoogle Scholar
  13. 13.
    Frank J (2006b) Three-dimensional electron microscopy of macromolecular assemblies: Visualization of biological molecules in their native state. Oxford University Press, OxfordCrossRefGoogle Scholar
  14. 14.
    Gilbert P (1972) Iterative methods for the three-dimensional reconstruction of an object from projections. J Theor Biol 36:105–117CrossRefGoogle Scholar
  15. 15.
    Giocondi MC, Ronzon F, Nicolai MC, Dosset P, Milhiet PE, Chevalier M, Grimellec CL (2010) Organization of influenza A virus envelope at neutral and low pH. J Gen Virol 91:329–338CrossRefGoogle Scholar
  16. 16.
    Gordon R, Bender R, Herman GT (1970) Algebraic Reconstruction Techniques (ART) for three-dimensional electron microscopy and x-ray photography. J Theor Biol 29:471–481CrossRefGoogle Scholar
  17. 17.
    Harris A, Cardone G, Winkler DC, Heymann JB, Brecher M, White JM, Steven AC (2006) Influenza virus pleiomorphy characterized by cryoelectron tomography. Proc Natl Acad Sci 103:19,123–19,127Google Scholar
  18. 18.
    Herman GT (2009) Fundamentals of computerized tomography: Image reconstruction from projections, 2nd edn. Springer, LondonCrossRefGoogle Scholar
  19. 19.
    Herman GT, Meyer LB (1993) Algebraic reconstruction techniques can be made computationally efficient. IEEE Trans Med Imaging 12:600–609CrossRefGoogle Scholar
  20. 20.
    Herman GT, Lent A, Rowland SW (1973) ART: Mathematics and applications: A report on the mathematical foundations and on the applicability to real data of the algebraic reconstruction techniques. J Theor Biol 42:1–32CrossRefGoogle Scholar
  21. 21.
    Lewitt RM (1990) Multidimensional digital image representations using generalized Kaiser-Bessel window functions. J Opt Soc Am A 7:1834–1846CrossRefGoogle Scholar
  22. 22.
    Lewitt RM (1992) Alternatives to voxels for image representation in iterative reconstruction algorithms. Phys Med Biol 37:705–716CrossRefGoogle Scholar
  23. 23.
    Marabini R, Rietzel E, Schroder R, Herman GT, Carazo JM (1997) Three-dimensional reconstruction from reduced sets of very noisy images acquired following a single-axis tilt schema: Application of a new three-dimensional reconstruction algorithm and objective comparison with weighted backprojection. J Struct Biol 120:363–371CrossRefGoogle Scholar
  24. 24.
    Marabini R, Herman GT, Carazo JM (1998) 3D reconstruction in electron microscopy using ART with smooth spherically symmetric volume elements (blobs). Ultramicroscopy 72:53–65CrossRefGoogle Scholar
  25. 25.
    Mastronarde DN (2005) Automated electron microscope tomography using robust prediction of specimen movements. J Struct Biol 152:36–51CrossRefGoogle Scholar
  26. 26.
    Matej S, Lewitt RM (1995) Efficient 3D grids for image reconstruction using spherically-symmetric volume elements. IEEE Trans Nucl Sci 42:1361–1370CrossRefGoogle Scholar
  27. 27.
    Matej S, Lewitt RM (1996) Practical considerations for 3-D image reconstruction using spherically symmetric volume elements. IEEE Trans Med Imaging 15:68–78CrossRefGoogle Scholar
  28. 28.
    Radermacher M (2006) Weighted back-projection methods. In: Frank J (ed) Electron tomography: Methods for three-dimensional visualization of structures in the cell, 2nd edn. Springer, New York, pp 245–274CrossRefGoogle Scholar
  29. 29.
    Roberts PC, Lamb RA, Compans RW (1998) The M1 and M2 proteins of influenza A virus are important determinants in filamentous particle formation. Virology 240:127–137CrossRefGoogle Scholar
  30. 30.
    Ruigrok RWH, Krijgsman PCJ, De Ronde-Verloop FM, De Jong JC (1985) Natural heterogeneity of shape, infectivity and protein composition in an influenza A (H3N2) virus preparation. Virus Res 3:69–76CrossRefGoogle Scholar
  31. 31.
    Sorzano COS, Marabini R, Boisset N, Rietzel E, Schröder R, Herman GT, Carazo JM (2001) The effect of overabundant projection directions on 3D reconstruction algorithms. J Struct Biol 133:108–118CrossRefGoogle Scholar
  32. 32.
    Varghese JN, Laver WG, Colman PM (1983) Structure of the influenza virus glycoprotein antigen neuraminidase at 2.9 Å resolution. Nature 303:35–40CrossRefGoogle Scholar
  33. 33.
    Wan X, Zhang F, Chu Q, Zhang K, FSun, Yuan B, Liu Z (2011) Three-dimensional reconstruction using an adaptive simultaneous algebraic reconstruction technique in electron tomography. J Struct Biol 175:277–287Google Scholar
  34. 34.
    Wang Q, Tao YJ (2010) Influenza: Molecular virology. Caister Academic Press, NorfolkGoogle Scholar
  35. 35.
    Wang Q, Cheng F, Lu M, Tian X, Ma J (2008) Crystal structure of unliganded influenza B virus hemagglutinin. J Virol 82:3011–3020CrossRefGoogle Scholar
  36. 36.
    Wasilewski S, Calder LJ, Grant T, Rosenthal PB (2012) Distribution of surface glycoproteins on influenza A virus determined by electron cryotomography. Vaccine 30:7368–7373CrossRefGoogle Scholar
  37. 37.
    Wilson IA, Skehel JJ, Wiley DC (1981) Structure of the haemagglutinin membrane glycoprotein of influenza virus at 3 Å resolution. Nature 289:366–373CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Younes Benkarroum
    • 1
  • Paul Gottlieb
    • 2
  • Al Katz
    • 3
  • Stuart W. Rowland
    • 1
  • Doris Bucher
    • 4
  • Gabor T. Herman
    • 1
  1. 1.Department of Computer Science, The Graduate CenterCity University of New YorkNew YorkUSA
  2. 2.Department of Microbiology and Immunology, Sophie Davis School of Biomedical EducationThe City College of New YorkNew YorkUSA
  3. 3.Department of PhysicsThe City College of New YorkNew YorkUSA
  4. 4.Department of Microbiology and ImmunologyNew York Medical CollegeValhallaUSA

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