Three Dimensional Electron Microscopy/What is 3DEM?

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What is 3DEM?[edit | edit source]

Flow chart showing the steps involved in 3DEM.
Cryogenic Conditions in EM

Cryogenic electron microscopy, often abbreviated as ‘cryo-EM’ has evolved to encompass a wide range of experimental methods. Cryo-EM is increasingly becoming a mainstream technology for studying cells, viruses, and protein structures at molecular resolution[1]. Images are produced using a electron microscope, using electrons as radiation, emitted by a source that is housed under a high vacuum, and then pushed down the microscope column at accelerating voltages in the range of 80-300 kV[1]. A very large difference in electron microscopy compared to optical microscopy is the resolving power of the two methods, with electron microscopy having a much high resolving power. The resolving power of a microscope is directly related to the wavelength of the irradiation used to form an image. The electron irradiation used causes extensive damage to the biological sample. One-way to reduce the electron induced sample damage is to perform the technique in cryogenic temperatures. Freezing aqueous solutions in cryogen, such as liquid ethane cooled by liquid nitrogen is a method commonly used to prepare specimens for cryo-EM applications[1]. This method has proved to reduce the effects of radiation damage in a large way, which in turn lets researchers use higher doses of electrons to increase the signal to noise ratio, because of less radiation damage. The commonly used variant of cryo-EM is single particle analysis. Using this technique data from a large number of 2D projection images such as identical copies of protein complexes in different orientations are combined to generate a 3D reconstruction of the structure [1].

Particle Picking[edit | edit source]

Particle picking attempts to correctly the position of particles, and differentiate between the particles and any contamination in an image [2]. Particles may be chosen manually or through the use of an automated algorithm. The automated algorithm strives to separate the “positive class” of particles from the “negative class” of contaminants or noise[3]. Automated algorithms may be prone to a type 1 or type 2 error, which falsely identify positives or negatives. .

Contrast Transfer Function[edit | edit source]

The contrast transfer function (CTF) is a distortion of the image data collected due to flawed optical properties in a transmission electron microscope[4]. There are two cause of the CTF and both are related to the lens system in electron microscopy. The first cause is spherical aberrations that cause many focal points, which blurs the image. The second cause of the CTF is the under focus used in electron microscopy. To obtain a high resolution 3D image, the CTF must be corrected.

Particle Extraction and Stack Creation[edit | edit source]

3DEM example.

A stack is a collection of similar images of the same structure. Individual images can be obtained by removing unnecessary information to increase processing speed[5]. Particle boxing cuts out the image 150% the particle’s pixel size. Particle contrast differentiates between particles on a negative stain and on vitreous ice, inverting when the particles are black against a light background. CTF correction alternates the particles between the data and its inverse to correct the particles.

Particle Alignment[edit | edit source]

In particle alignment images of a particle are shifted and rotated in many different directions to attempt to align the particles. They must be shifted and rotated to align together to obtain an average image. The goal when averaging is to maximize the cross correlation of the images[6]. Particle alignment can either be classified as reference based or reference free. Depending on the classification, different types of automated packages may be used for alignment e.g. Xmipp Maxium Likelihood Alignment, Spider Reference Liklihood, and EMAN Refine 2D Refrence-free Alignment[7].

Initial Model Creation[edit | edit source]

Multiple 2D images are required to obtain the structure of a 3D image. Particles are chosen and organized by structural characteristics including common lines, shapes, and tilts[8]. The particles are clustered with other structurally similar particles, and then averaged together [2]. Reconstruction of a 3D model is reliant on the particle orientation, as stated by the central projection theorem[1].

3D Reconstruction[edit | edit source]

After getting an initial 3D structure by using one of a number of methods, such as random conical tilt or angular reconstitution, the obtained map is used as a 3D reference to refine the single particle orientation parameters (two for position and three for orientation). The structure can then be iteratively improved, alternating position and orientation determination with 3D reconstruction. The FSC Fourier shell correlation) and other resolution criteria can be used to follow the progress of the structure refinement, which is terminated when there is no further improvement. Different program such as IMAGIC, SPIDER, FREALIGN can be used for this purpose[9].

References[edit | edit source]

  1. a b c d e Milne, Jacqueline L, Mario J Borgnia, and Alberto Bartesaghi. "Cryo-electron microscopy – a primer for the non-microscopist." Febs Journal.280 (2012): n. page. Print. Invalid <ref> tag; name "electron" defined multiple times with different content Invalid <ref> tag; name "electron" defined multiple times with different content
  2. a b Voss, Neil. "Particle Picking." Roosevelt University, Schaumburg. 13 Sept. 2013. Lecture.
  3. Langlois, Robert, and Joachim Frank. "A Clarification of the Terms Used in Comparing Semi-automated Particle Selection Algorithms in Cryo-EM." Journal of Structural Biology 175.3 (2011): 348-52. Science Direct. Howard Hughes Medical Institute. Web. 3 Dec. 2013.
  4. Voss, Neil. "Contrast Transfer Function." Roosevelt University, Schaumburg. 27 Sept. 2013. Lecture.
  5. Voss, Neil. "Particle Boxing." Roosevelt University, Schaumburg. 27 Sept. 2013. Lecture.
  6. Sigworth, F.J. "A Maximum-Likelihood Approach to Single-Particle Image Refinement." Journal of Structural Biology.122 (1998): n. page. Print.
  7. Voss, Neil. "Particle Alignment." Roosevelt University, Schaumburg. 4 Oct. 2013. Lecture.
  8. Voss, Neil. "Initial Model Problem." Roosevelt University, Schaumburg. 8 Nov. 2013. Lecture.
  9. Voss, Neil. "3D Reconstruction." Roosevelt University, Schaumburg. 25 Oct. 2013. Lecture.