Towards automatic electron tomography II. Implementation of autofocus and low-dose procedures

Dierksen, Karen P.; Typke, Dieter; Hegerl, R.; Baumeister, Wolfgang

doi:10.1016/0304-3991(93)90217-l

Cited by 120 publications

(65 citation statements)

References 12 publications

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“…12 A series of 2D projections, i.e., a 'tilt-series', is collected under 'low electron dose' conditions (typically <60 e -/A 2 ) to prevent radiation damage to the sample. 13,14 The tilt-series is subsequently aligned to a common frame in order to reconstruct the 3D volume of the specimen, namely a tomogram 12 (Fig. 2).…”

Section: Visualizing Cellular Architecture By Cryo-electron Tomographymentioning

confidence: 99%

Toward correlating structure and mechanics of platelets

Sorrentino

Studt

Horev

et al. 2016

Cell Adhesion & Migration

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The primary physiological function of blood platelets is to seal vascular lesions after injury and form hemostatic thrombi in order to prevent blood loss. This task relies on the formation of strong cellular-extracellular matrix interactions in the subendothelial lesions. The cytoskeleton of a platelet is key to all of its functions: its ability to spread, adhere and contract. Despite the medical significance of platelets, there is still no high-resolution structural information of their cytoskeleton. Here, we discuss and present 3-dimensional (3D) structural analysis of intact platelets by using cryoelectron tomography (cryo-ET) and atomic force microscopy (AFM). Cryo-ET provides in situ structural analysis and AFM gives stiffness maps of the platelets. In the future, combining highresolution structural and mechanical techniques will bring new understanding of how structural changes modulate platelet stiffness during activation and adhesion.

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Section: Visualizing Cellular Architecture By Cryo-electron Tomographymentioning

confidence: 99%

Toward correlating structure and mechanics of platelets

Sorrentino

Studt

Horev

et al. 2016

Cell Adhesion & Migration

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“…tal setup for automated tomographic data collection has been described (6,7). A slice through the reconstruction is shown in Fig.…”

Section: Fig 3 Artificial Electron-tomographic Volumes Of (A) Thermmentioning

confidence: 99%

“…Rapid freezing techniques have been developed, which allow the ''vitrification'' of biological materials and thus ensure their close-to-life preservation (4,5). With the advent of automated electron tomography (6)(7)(8)(9) it has become possible to obtain three-dimensional (3D) data sets of whole ice-embedded cells or organelles (10,11) with subcritical doses. Currently, the resolution obtained in electron tomography of cellular structures ( Fig.…”

mentioning

confidence: 99%

Toward detecting and identifying macromolecules in a cellular context: Template matching applied to electron tomograms

Böhm

Frangakis²,

Hegerl³

et al. 2000

Proc. Natl. Acad. Sci. U.S.A.

213

139

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Electron tomography is the only technique available that allows us to visualize the three-dimensional structure of unfixed and unstained cells currently with a resolution of 6 -8 nm, but with the prospect to reach 2-4 nm. This raises the possibility of detecting and identifying specific macromolecular complexes within their cellular context by virtue of their structural signature. Templates derived from the high-resolution structure of the molecule under scrutiny are used to search the reconstructed volume. Here we outline and test a computationally feasible two-step procedure: In a first step, mean-curvature motion is used for segmentation, yielding subvolumes that contain with a high probability macromolecules in the expected size range. Subsequently, the particles contained in the subvolumes are identified by cross-correlation, using a set of three-dimensional templates. With simulated and real tomographic data we demonstrate that such an approach is feasible and we explore the detection limits. Even structurally similar particles, such as the thermosome, GroEL, and the 20S proteasome can be identified with high fidelity. This opens up exciting prospects for mapping the territorial distribution of macromolecules and for analyzing molecular interactions in situ. It has been a dream of cell biologists to catch a glimpse of the molecular architecture inside cells or cellular organelles, ideally by using a noninvasive technique (1-3). Rapid freezing techniques have been developed, which allow the ''vitrification'' of biological materials and thus ensure their close-to-life preservation (4, 5). With the advent of automated electron tomography (6-9) it has become possible to obtain three-dimensional (3D) data sets of whole ice-embedded cells or organelles (10, 11) with subcritical doses. Currently, the resolution obtained in electron tomography of cellular structures ( Fig. 1) is in the range of 6 to 8 nm. It is reasonable to expect that high-end instrumentation will bring us into the realm of molecular resolution (2-4 nm). The goal of cellular electron tomography is not to obtain a high-resolution structure of a particular macromolecule; the goal is to identify a molecule by virtue of its structural signature and to locate it in the context of its cellular environment. Inevitably, the electron tomograms will suffer from a low signal-to-noise ratio (SNR), and so-called denoising techniques (12, 13) can provide only partial remedy. However, if we have high-or medium-resolution structures of the molecule under scrutiny, furnished by x-ray crystallography, electron microscopy, or any combination of structural biology techniques, these can be used as templates to search the reconstructed cellular volume. This type of scan will make it possible not only to map the distribution of molecules within the cell; it also will reveal the spatial relationships of molecules in functional modules.The purpose of this paper is to outline a computationally feasible strategy for the detection and identification of macromolecules in to...

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“…Automated routines for obtaining tomographic datasets are already available and running on certain microscopes [1,5]. These routines minimize the electron dose to the specimen thereby decreasing beam damage and also the amount of time a human operator needs to spend in obtaining the large datasets.…”

Section: IVmentioning

confidence: 99%