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. 2005 Jan;14(1):257-69.
doi: 10.1110/ps.041148605.

A voyage to the inner space of cells

Wolfgang Baumeister  1
Affiliations

A voyage to the inner space of cells

Wolfgang Baumeister. Protein Sci. 2005 Jan.
No abstract available

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Figures

Figure 1.
Figure 1.
Pioneers of electron microscopy. (Left) Ernst Ruska (1906–1988). (Right) Helmut Ruska (1908–1973).
Figure 2.
Figure 2.
(A) Electron micrograph of a metal-shadowed HPI-layer as obtained by detergent extraction of the Deinococcus radiodurans cell envelope. Areas marked R show the rough inner surface; areas marked S show the smoother outer surface. For details, see Baumeister et al. (1981). (B) An 8 Å projection map of the HPI-layer embedded in aurothioglucose. (For details, see Rachel et al. 1986.)
Figure 3.
Figure 3.
(A) The Staphylothermus marinus surface layer as revealed by freeze-etching (left). In the absence of MgCl2 the detergent extracted surface layer dissociates into micelles formed by the tetrabrachion-protease complexes (right). (B) The tetrabrachion-protease complex. (Left) Model showing the mode of interaction of the tetrabrachion-protein complexes in the layer structure. (Center) Electron micrograph of the negatively stained complex released from the surface layer meshwork by SDS-heat treatment (for details, see Peters et al. 1995). (Right) Folding topology of tetrabrachion. The location of N-terminal residues, cysteine residues, and the unique proline residue separating the left- and right-handed supercoiled domains are marked by circles. Putative disulfide bridges are indicated. The flexible hinge segment, the protease-binding region, and the membrane anchor are marked by rectangles. (For details, see Peters et al. 1996.)
Figure 4.
Figure 4.
The 20S proteasome from Thermoplasma acidophilum. (A) Electron micrograph of recombinant 20S proteasomes in vitreous ice. (B,top left) Structure of the 20S proteasome in surface representation, low-pass filtered to 1 nm resolution. The α- and β-subunits are located in the outer and the inner rings, respectively. (Top right) The same structure cut open along the sevenfold axis to display the inner compartments with the active sites of the β-subunits in the central chamber marked in red. (Bottom left and right) Similar fold of the α- (left) and β- subunits (right). Both subunits contain a sandwich of two, five-stranded antiparallel β-sheets flanked by helices. (For details, see Löwe et al. 1995; Zwickl et al. 2002.)
Figure 5.
Figure 5.
The protein quality control system in Thermoplasma acidophilum. Components of the proteolytic pathway are shown in yellow; chaperones, in green. The numbers refer to the ORF code. (For details, see Ruepp et al. 2000.)
Figure 6.
Figure 6.
Cryoelectron tomography of Dictyostelium discoideum cell. (A) Visualization of the actin network and cytoplasmic complexes in a Dictyostelium cell grown directly on an EM grid and embedded in vitreous ice (for details, see Medalia et al. 2002). (B) Visualization of a 26S proteasome within an intact Dictyostelium cell. (Left) Slice from a tomogram. Dominant features are ribosomes, some of them attached to the endoplasmic reticulum (lower left corner), and actin filaments. The encircled particle is a 26S proteasome. (Right) enlarged contour plot of the single (unaveraged) 26S proteasome (projection of a stack of slices from tomogram).
Figure 7.
Figure 7.
Strategy for the detection and identification of macromolecules in cellular volumes. Because of the crowded nature of cells and the high noise levels in tomograms (left), an interactive segmentation and feature extraction is, in most cases, not feasible. It requires automated pattern recognition techniques to exploit the rich information content of such tomograms. An approach that has been demonstrated to work is based on the recognition of the structural signature (size, shape) of molecules by template matching. Templates of the macromolecules under scrutiny are obtained by high- or medium-resolution techniques. Theses templates are then used to search the volume of the tomograms (Vin) systematically for matching structures by cross-correlation. The tomogram has to be scanned for all possible Eulerian angles around three different axes, with templates of all the different protein structures in which one is interested. The search is computationally demanding, but can be parallelized efficiently. The output information (Vout) is a set of coordinates that describes the positions and orientation of all the molecules found in the tomogram. (For details, see Frangakis et al. 2002.)
Figure 8.
Figure 8.
Mapping molecular landscapes by pattern recognition. Volume-rendered representation of an ice-embedded “phantom cell” containing thermosomes (blue) and 20S proteasomes (yellow) with a 1:1 molar ratio. The two protein species were identified by template matching and are represented by averages derived from the tomogram. (For details, see Frangakis et al. 2002.)
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