Single particle analysis based on Zernike phase contrast transmission electron microscopy

Danev, Radostin; Nagayama, Kuniaki

doi:10.1016/j.jsb.2007.10.015

Cited by 107 publications

(106 citation statements)

References 29 publications

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“…We then symmetrized each of these models using SSA and selected the best one (based on the resemblance of its features to the known structure of ε15) as a reference to seed iterative gold-standard icosahedral refinement with the entire set of particles. It is important to note that for phase plate data, applying a highpass filter can sometimes be essential to accomplish accurate alignment since it ameliorates the cut-on frequency artifact that characterizes ZPC images (Danev & Nagayama 2008). The data converged to a final ~24 Å resolution ( Figure 4B,D,E), in excellent agreement with the ~25 Å resolution value previously reported for this dataset (Muarata et al 2010).…”

Section: Iterative Refinement Of Subtomogramssupporting

confidence: 85%

Single Particle Tomography in EMAN2

et al. 2012

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Single particle tomography (SPT or subtomogram averaging) offers a powerful alternative to traditional 2-D single particle reconstruction for studying conformationally or compositionally heterogeneous macromolecules. It can also provide direct observation (without labeling or staining) of complexes inside cells at nanometer resolution. The development of computational methods and tools for SPT remains an area of active research. Here we present the EMAN2.1 SPT toolbox, which offers a full SPT processing pipeline, from particle picking to post-alignment analysis of subtomogram averages, automating most steps. Different algorithm combinations can be applied at each step, providing versatility and allowing for procedural cross-testing and specimen-specific strategies. Alignment methods include all-vs-all, binary tree, iterative singlemodel refinement, multiple-model refinement, and self-symmetry alignment. An efficient angular search, Graphic Processing Unit (GPU) acceleration and both threaded and distributed parallelism are provided to speed up processing. Finally, automated simulations, per particle reconstruction of subtiltseries, and per-particle Contrast Transfer Function (CTF) correction have been implemented. Processing examples using both real and simulated data are shown for several structures.

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Section: Iterative Refinement Of Subtomogramssupporting

confidence: 85%

Single Particle Tomography in EMAN2

et al. 2012

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“…Cryo-EM of GroEL with (a) defocus phase contrast and (b) Zernike phase contrast generated by a thin amorphous-carbon phase plate. Reproduced with permission from Danev & Nagayama (2008). images are vital, since in many cases structures of interest only assemble or only exhibit functional conformations in their cellular environment. Usually, tomographic imaging leads directly to mechanistic hypotheses.…”

Section: Resultsmentioning

confidence: 99%

Electron tomography of cells

Gan

Jensen

2011

Quart. Rev. Biophys.

154

130

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Abstract. The electron microscope has contributed deep insights into biological structure since its invention nearly 80 years ago. Advances in instrumentation and methodology in recent decades have now enabled electron tomography to become the highest resolution threedimensional (3D) imaging technique available for unique objects such as cells. Cells can be imaged either plastic-embedded or frozen-hydrated. Then the series of projection images are aligned and back-projected to generate a 3D reconstruction or ' tomogram '. Here, we review how electron tomography has begun to reveal the molecular organization of cells and how the existing and upcoming technologies promise even greater insights into structural cell biology.

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“…By heating the carbon film to about 200°t o minimize hydrocarbon contamination, and by using modern focused-ion-beam technology to drill a hole with a radius of only 0.25 μm, his laboratory has recently produced spectacular results that seem certain to usher in a new era of biological electron microscopy. 8 As an example, the visibility of the GroEL protein complex is markedly improved when a phase plate, rather than image defocus, is used to provide phase contrast, as shown in figure 3. Although more contrast could be generated by defocusing the image much farther than the roughly 2 μm used in figure 3a, doing so comes at the expense of greater loss of signal at higher resolution.…”

Section: Imaging the Phasementioning

confidence: 99%