A Bayesian approach for suppression of limited angular sampling artifacts in single particle 3D reconstruction

Toshio Moriya, Erman Acar, R. Holland Cheng, Ulla Ruotsalainen

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

In the single particle reconstruction, the initial 3D structure often suffers from the limited angular sampling artifact. Selecting 2D class averages of particle images generally improves the accuracy and efficiency of the reference-free 3D angle estimation, but causes an insufficient angular sampling to fill the information of the target object in the 3D frequency space. Similarly, the initial 3D structure by the random-conical tilt reconstruction has the well-known "missing cone" artifact. Here, we attempted to solve the limited angular sampling problem by sequentially applying maximum a posteriori estimate with expectation maximization algorithm (sMAP-EM). Using both simulated and experimental cryo-electron microscope images, the sMAP-EM was compared to the direct Fourier method on the basis of reconstruction error and resolution. To establish selection criteria of the final regularization weight for the sMAP-EM, the effects of noise level and sampling sparseness on the reconstructions were examined with evenly distributed sampling simulations. The frequency information filled in the missing cone of the conical tilt sampling simulations was assessed by developing new quantitative measurements. All the results of visual and numerical evaluations showed the sMAP-EM performed better than the direct Fourier method, regardless of the sampling method, noise level, and sampling sparseness. Furthermore, the frequency domain analysis demonstrated that the sMAP-EM can fill the meaningful information in the unmeasured angular space without detailed a priori knowledge of the objects. The current research demonstrated that the sMAP-EM has a high potential to facilitate the determination of 3D protein structures at near atomic-resolution.

Original languageEnglish (US)
Article number6755
Pages (from-to)318-331
Number of pages14
JournalJournal of Structural Biology
Volume191
Issue number3
DOIs
StatePublished - Sep 1 2015

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Bayes Theorem
Artifacts
Noise
Patient Selection
Electrons
Weights and Measures
Research
Proteins

Keywords

  • Cryo-electron microscopy
  • Maximum a posteriori probability estimation
  • Median root prior reconstruction
  • Missing cone
  • Poisson image formation model
  • Sparse angular sampling

ASJC Scopus subject areas

  • Structural Biology

Cite this

A Bayesian approach for suppression of limited angular sampling artifacts in single particle 3D reconstruction. / Moriya, Toshio; Acar, Erman; Cheng, R. Holland; Ruotsalainen, Ulla.

In: Journal of Structural Biology, Vol. 191, No. 3, 6755, 01.09.2015, p. 318-331.

Research output: Contribution to journalArticle

Moriya, Toshio ; Acar, Erman ; Cheng, R. Holland ; Ruotsalainen, Ulla. / A Bayesian approach for suppression of limited angular sampling artifacts in single particle 3D reconstruction. In: Journal of Structural Biology. 2015 ; Vol. 191, No. 3. pp. 318-331.
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