Abstract
The Transmission Electron Microscope (TEM) is an electron-based imaging system used to reveal the atomic or molecular details of a specimen. High-energy electrons are used to probe the object in question, resulting in the generation of a two-dimensional (2D) image of the object's three-dimensional (3D) information. The electrons in use, with typical energies of greater than 100 kV, have wavelengths less than a tenth of an Ångström, theoretically allowing for imaging resolution far below the sub-Ångström range. However, due to the presence of imperfect imaging conditions such as lens aberrations and sample irradiation, the information transferred from biological specimens via TEM has yet to reach the sub-Ångström limit.
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Further Reading
Baker T, Olson N, Fuller S. 1999. Adding the third dimension to virus life cycles: three-dimensional reconstruction of icosahedral viruses from cryo-electron micrographs. Microbiol Mol Biol Rev 63(4):862-922.
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Williams D, Carter C. 1996. Transmission electron microscopy: basics I. New York: Springer.
References
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7.1 Electronic Supplementary material
Figure 7.1.
Schematic cross-section diagram and effect of lenses on the electron beam in TEM. (A) The electron beam generated from the gun passes through a series of lenses and apertures, as well as the specimen, before a magnified image is formed by striking a phosphorescent screen or charged-coupled device (CCD). (B) (facing page) Image formation in a lens can be described as a double-diffraction process. Incoming parallel beams interact with the sample and undergo a corresponding phase shift. These phaseshifted electrons are then focused by the objective lens and screened by the objective aperture. The objective lens generates an optical Fourier transform of the specimen, which can be seen as a diffraction pattern at the back focal plane. Subsequent lenses perform an inverse Fourier transform of the diffraction pattern producing a magnified image of the specimen. Please visit http://extras.springer.com/ to view a high resolution full-color version of this illustration. (PDF 2,786 KB)
Figure 7.2.
Schematic of the aberrations contributed by the objective lens. (A) Differential focusing of the electrons by the lens along its diameter results in spherical aberration. (B) Similarly, differential focusing of electrons of varying energies generates a chromatic aberration. (C) Finally, non-isotropic directional focusing leads to astigmatic effects. Please visit http://extras.springer.com/ to view a high-resolution full color version of this illustration. (PDF 2,770 KB)
Figure 7.4.
Plots of simulated contrast transfer functions (CTFs). (A) CTF at 2000-nm defocus without suppression from an envelope function by having spatial frequency as the variable of the function. (B) Spatial attenuation at high frequencies due to the envelope function. (C) (facing page) CTFs at 1500- (purple) and 2500-nm (green) defocus reveal slower CTF oscillations and a higher point-to-point resolution for the lower defocus and faster CTF oscillations and a lower point-to-point resolution for the higher defocus. Please visit http://extras.springer.com/ to view a high-resolution full-color version of this illustration. (PDF 2,799 KB)
Figure 7.5.
Projection theorem at a glance. A 3D object is imaged via TEM in varying orientations, generating 2D projections of itself. FTs of the 2D projections are oriented relative to one another in 3D Fourier space, followed by a Fourier back transform that regenerates a representation of the starting object. Please visit http://extras.springer.com/ to view a high-resolution full-color version of this illustration. (PDF 2,819 KB)
Figure 7.8.
First thirty eigenimages generated from a mock dataset of reprojected lumazine synthase capsids lowpass filtered to 5 Å. The first eigenimage corresponds to the center of mass of the full datacloud and represents the average of the dataset. The early eigenimages reveal lower-order symmetry modulations, while subsequent ones reveal higher-order symmetry modulations that characterize finer capsid details. Please visit http://extras.springer.com/ to view a high-resolution full-color version of this illustration. (PDF 2,787 KB)
Figure 7.9.
Images distribution of in multidimensional eigenspace. (A) Example of a 2D projection of image vectors in eigenspace onto the first and second eigenvectors. Principal variation occurs across eigenvector 1, with eigenvalues spanning from -1 to +1. Less variation is seen along the direction of eigenvector 2, with eigenvalues only ranging from -0.5 to +0.5. (B) Classification of a dataset projected onto the first and second eigenvectors, as determined by K-means clustering. Images within a class share similar eigenvalues with one another across both eigenvectors and can be grouped into nearly homogeneous classes. The classes in green and purple show some overlap, as there is not a complete distinction between them based solely on two eigenvectors. Please visit http://extras.springer.com/ to view a high-resolution full-color version of this illustration. (PDF 2,813 KB)
Figure 7.11.
Workflow of reference-based refinement. Please visit http://extras.springer.com/ to view a high-resolution full-color version of this illustration. (PDF 2,796 KB)
Figure 7.13.
Self-common lines of a viral capsid. (A) FT of a projection oriented near the 3-fold axis. (B) Introduction of a symmetry-related projection generates a common line between the two projections. (C) Introduction of a third symmetry-related projection generates a set of three common lines, with each projection containing only two of the three possible common lines. The Fourier amplitude and phase values along these pairs of lines are identical to one another. Please visit http://extras.springer.com/ to view a high resolution full-color version of this illustration. (PDF 2,808 KB)
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Green, D.J., Cheng, R.H. (2010). Transmission Electron Microscopy and Computer-Aided Image Processing for 3D Structural Analysis of Macromolecules. In: Jue, T. (eds) Biomedical Applications of Biophysics. Handbook of Modern Biophysics, vol 3. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60327-233-9_7
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