Skip to main content
SpringerLink
Log in

A Method for Generation of Synthetic 2D and 3D Cryo-EM Images

  • Published:
Programming and Computer Software Aims and scope Submit manuscript

Abstract

Cryo-electron microscopy (cryo-EM) is widely used in structural biology for resolving 3D models of particles with Angstrom resolution. The most popular techniques for such high-resolution model reconstruction are single-particle cryo-EM and cryo-electron tomography (cryo-ET). The cornerstone of both techniques is the registration of images: 2D images in cryo-EM and 3D images in cryo-ET. There are several registration methods for 2D and 3D cryo-EM images; however, it is hard to evaluate these methods due to the lack of ground truth for real data. Moreover, evaluation of image registration methods on real data is complicated by a high level of noise. In this paper, we propose image synthesis methods for generating realistic 2D single-particle cryo-EM images and 3D cryo-ET subtomogram images. The proposed algorithms model the artifacts typical of the real EM image acquisition pipeline: EM-specific noise, missing wedge effect, 2D projection, and contrast transfer function. We also present some examples of the 2D and 3D synthetic images generated.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.
Fig. 10.
Fig. 11.

Similar content being viewed by others

REFERENCES

  1. Milne, J.L.S., Borgnia, M.J., Bartesaghi, A.B., Tran, E.E.H., Earl, L.A., Schauder, D.M., Lengyel, J., Pierson, J., Patwardhan, A., and Subramaniam, S., Cryo-electron microscopy: A primer for the non-microscopist, Fed. Eur. Biochem. Soc. J., 2013, vol. 280, no. 1, pp. 28–45.

    Google Scholar 

  2. Hoenger, A. and Bouchet-Marquis, C., Cellular tomography, Adv. Protein Chem. Struct. Biol., 2011, vol. 82, pp. 67–90.

    Article  Google Scholar 

  3. Tocheva, E.I., Li, Z., and Jensen, G.J., Electron cryotomography, Cold Spring Harbor Perspect. Biol., 2010, vol. 2, no. 6.

  4. Al-Amoudi, A., Jiin-Ju Chang, J.-J., Leforestier, A., McDowall, A., Salamin, L.M., Norlen, L.P.O., Richter, K., Sartori Blanc, N., Studer, D., and Dubochet, J., Cryo-electron microscopy of vitreous sections, Eur. Mol. Biol. Organ. J., 2004, vol. 23, no. 18, pp. 3583–3588.

    Article  Google Scholar 

  5. Glaeser, R.M., Limitations to significant information in biological electron microscopy as a result of radiation damage, J. Ultrastruct. Res., 1971, vol. 36, no. 3, pp. 466–482.

    Article  Google Scholar 

  6. Schmid, M.F., Single-particle electron cryotomography (cryoet), Adv. Protein Chem. Struct. Biol., 2011, vol. 82, pp. 37–65.

    Article  Google Scholar 

  7. Mamaev, N.V., Lukin, A.S., and Yurin, D.V., Henlm-la: A locally adaptive non-local means algorithm based on Hermite functions expansion, Program. Comput. Software, 2014, vol. 40, no. 4, pp. 199–207.

    Article  MathSciNet  Google Scholar 

  8. McEwen, B.F., Radermacher, M., Rieder, C.L., and Frank, J., Tomographic three-dimensional reconstruction of cilia ultrastructure from thick sections, Proc. National Acad. Sci., 1986, vol. 83, no. 23, pp. 9040–9044.

    Article  Google Scholar 

  9. Lander, G.C., Stagg, S.M., Voss, N.R., Cheng, A., Fellmann, D., Pulokas, J., Yoshioka, C., Irving, C., Mulder, A., Lau, P.-W., et al., Appion: An integrated, database-driven pipeline to facilitate EM image processing, J. Struct. Biol., 2009, vol. 166, no. 1, pp. 95–102.

    Article  Google Scholar 

  10. Lyumkis, D., Brilot, A.F., Theobald, D.L., and Grigorieff, N., Likelihood-based classification of cryo-EM images using frealign, J. Struct. Biol., 2013, vol. 183, no. 3, pp. 377–388.

    Article  Google Scholar 

  11. Mills, D.J., Vitt, S., Strauss, M., Shima, S., and Vonck, J., De novo modeling of the f420-reducing [nife]-hydrogenase from a methanogenic archaeon by cryo-electron microscopy, Elife, 2013, vol. 2.

  12. Gatsogiannis, C., Hofnagel, O., Markl, J., and Raunser, S., Structure of megahemocyanin reveals protein origami in snails, Structure, 2015, vol. 23, no. 1, pp. 93–103.

    Article  Google Scholar 

  13. Perlin, K., An image synthesizer, ACM Siggraph Comput. Graphics, 1985, vol. 19, no. 3, pp. 287–296.

    Article  Google Scholar 

  14. Chang, Y.-W., Rettberg, L.A., Ortega, D.R., and Jensen, G.J., In vivo structures of an intact type vi secretion system revealed by electron cryotomography, Eur. Mol. Biol. Organ. Rep., 2017.

  15. Vulovic, M., Modeling of Image Formation in Cryo-Electron Microscopy, Delft: Delft Univ. Technol., 2013.

    Google Scholar 

  16. Wade, R.H., The phase contrast characteristics in bright field electron microscopy, Ultramicroscopy, 1978, vol. 3, pp. 329–334.

    Article  Google Scholar 

  17. Sigworth, F.J., Principles of cryo-EM single-particle image processing, Microscopy, 2016, vol. 65, no. 1, pp. 57–67.

    Article  Google Scholar 

  18. Anoshina, N.A., Krylov, A.S., and Sorokin, D.V., Correlation-based 2D registration method for single particle cryo-EM images, Proc. Int. Conf. Image Processing Theory, Tools, and Applications (IPTA), 2017.

Download references

ACKNOWLEDGMENTS

This work was supported by the Russian Science Foundation, project no. 17-11-01279.

Author information

Authors and Affiliations

  1. Laboratory of Mathematical Methods of Image Processing, Department of Computational Mathematics and Cybernetics, Moscow State University, Moscow, Russia

    N. A. Anoshina, T. B. Sagindykov & D. V. Sorokin

Authors
  1. N. A. Anoshina
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. T. B. Sagindykov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. D. V. Sorokin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to N. A. Anoshina, T. B. Sagindykov or D. V. Sorokin.

Additional information

Translated by Yu. Kornienko

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Anoshina, N.A., Sagindykov, T.B. & Sorokin, D.V. A Method for Generation of Synthetic 2D and 3D Cryo-EM Images. Program Comput Soft 44, 240–247 (2018). https://doi.org/10.1134/S0361768818040023

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0361768818040023

Key words:

Search

Navigation