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Cryogenic electron microscopy ( cryo-EM) is a transmission electron microscopy technique applied to samples cooled to cryogenic temperatures. For biological specimens, the structure is preserved by embedding in an environment of vitreous ice. An aqueous sample solution is applied to a grid-mesh and plunge-frozen in liquid ethane or a mixture of liquid ethane and propane. While development of the technique began in the 1970s, recent advances in detector technology and software algorithms have allowed for the determination of biomolecular structures at near-atomic resolution. This has attracted wide attention to the approach as an alternative to X-ray crystallography or NMR spectroscopy in the structural biology field.
In 2017, the Nobel Prize in Chemistry was awarded to Jacques Dubochet, Joachim Frank, and Richard Henderson "for developing cryo-electron microscopy for the high-resolution structure determination of biomolecules in solution." Nature Methods also named cryo-EM as the "Method of the Year" in 2015.
Thin crystals mounted on carbon film were found to be from 30 to 300 times more beam-resistant at 4 K than at room temperature... Most of our results can be explained by assuming that cryoprotection in the region of 4 K is strongly dependent on the temperature.
However, these results were not reproducible and amendments were published in Nature just two years later informing that the beam resistance was less significant than initially anticipated. The protection gained at 4 K was closer to "tenfold for standard samples of L-valine", than what was previously stated.
In 1981, Alasdair McDowall and Jacques Dubochet, scientists at the European Molecular Biology Laboratory, reported the first successful implementation of cryo-EM. McDowall and Dubochet Vitrification pure water in a thin film by spraying it onto a hydrophilic carbon film that was rapidly plunged into Cryogenics (liquid propane or liquid ethane cooled to 77 K). The thin layer of amorphous ice was less than 1 μm thick and an electron diffraction pattern confirmed the presence of amorphous/vitreous ice. In 1984, Dubochet's group demonstrated the power of cryo-EM in structural biology with analysis of Vitrification Adenoviridae type 2, T4 bacteriophage, Semliki Forest virus, Bacteriophage CbK, and Vesicular-Stomatitis-Virus. This paper is generally considered to mark the origin of Cryo-EM, and the technique has been developed to the point of becoming routine at numerous laboratories throughout the world.
The energy of the electrons used for imaging (80–300 kV) is, by far, high enough that Covalent bond of organic and biological samples can be broken in an inelastic scattering interaction. When imaging specimens are vulnerable to radiation damage, it is necessary to limit the electron exposure used to acquire the image. These low exposures require that the images of thousands or even millions of identical frozen molecules be selected, aligned, and averaged to obtain high-resolution maps, using specialized software. A significant improvement in structural features was achieved in 2012 by the introduction of direct electron detectors and better computational algorithms.
The 2010s were marked with drastic advancements of electron cameras. Notably, the improvements made to direct electron detectors have led to a "resolution revolution" pushing the resolution barrier beneath the crucial ~2-3 Å limit to resolve amino acid position and orientation.
Henderson (MRC Laboratory of Molecular Biology, Cambridge, UK) formed a consortium with engineers at the Rutherford Appleton Laboratory and scientists at the Max Planck Society to fund and develop a first prototype. The consortium then joined forces with the electron microscope manufacturer FEI Company to roll out and market the new design. At about the same time, Gatan Inc. of Pleasanton, California came out with a similar detector designed by Peter Denes (Lawrence Berkeley National Laboratory) and David Agard (University of California, San Francisco). A third type of camera was developed by Xuong Nguyen-Huu at the Direct Electron company (San Diego).More recently, advancements in the use of protein-based imaging scaffolds are helping to solve the problems of sample orientation bias and size limit. Though the minimum size for Cryo-EM remains undetermined, Protein smaller than ~50 kDa generally have too low a signal-to-noise ratio (SNR) to be able to resolve protein particles in the image, making 3D reconstruction difficult or impossible. Multiple techniques have been reported to improve SNR when determining the structures of small proteins. Based on high-affinity DARPin, nanobodies, antibody fragments, these methods rigidly bind the target protein and thereby increase the effective particle size and introduce symmetry to improve SNR for Cryo-EM map reconstruction.
The resolution of X-ray crystallography is limited by crystal homogeneity, and coaxing biological molecules with unknown ideal crystallization conditions into a crystalline state can be very time-consuming, in extreme cases taking months or even years. To contrast, sample preparation in cryo-EM may require several rounds of screening and optimization to overcome issues such as protein aggregation and preferred orientations, but it does not require the sample to form a crystal, rather samples for cryo-EM are flash-frozen and examined in their near-native states.
According to Proteopedia, the median resolution achieved by X-ray crystallography (as of May 19, 2019) on the Protein Data Bank is 2.05 Angstrom, and the highest resolution achieved on record (as of September 30, 2022) is 0.48 Å. As of 2020, the majority of the protein structures determined by cryo-EM are at a lower resolution of 3–4 Å. However, as of 2020, the best cryo-EM resolution has been recorded at 1.22 Å, making it a competitor in resolution in some cases.
Consequently, the images are extremely Signal noise. For some biological systems it is possible to average images to increase the signal-to-noise ratio and retrieve high-resolution information about the specimen using the technique known as single particle analysis. This approach in general requires that the things being averaged are identical, although some limited conformational heterogeneity can now be studied (e.g. ribosome). Three-dimensional reconstructions from CryoTEM images of protein complexes and Virus have been solved to sub-nanometer or near-atomic resolution, allowing new insights into the structure and biology of these large assemblies.
Analysis of ordered arrays of protein, such as 2-D crystals of transmembrane proteins or Helix arrays of proteins, also allows a kind of averaging which can provide high-resolution information about the specimen. This technique is called electron crystallography.
The maximum likelihood estimation approach comes to this field from the statistics. Here, all the possible orientations of particles are summed up to get the resulting probability distribution. We can compare this to a typical Least squares estimation where particles get exact orientations per image. This way, the particles in the sample get "fuzzy" orientations after calculations, weighted by corresponding probabilities. The whole process is iterative and with each next iteration the model gets better. The good conditions for making the model that closely represent the real structure is when the data does not have too much noise and the particles do not have any preferential direction. The main downside of maximum likelihood approach is that the result depends on the initial guess and model optimization can sometimes get stuck at local minimum.
The Bayesian approach that is now being used in cryo-TEM is empirical by nature. This means that the distribution of particles is based on the original dataset. Similarly, in the usual Bayesian method there is a fixed prior probability that is changed after the data is observed. The main difference from the maximum likelihood estimation lies in special reconstruction term that helps smoothing the resulting maps while also decreasing the noise during reconstruction. The smoothing of the maps occurs through assuming prior probability to be a Gaussian distribution and analyzing the data in the Fourier space. Since the connection between the prior knowledge and the dataset is established, there is less chance for human factor errors which potentially increases the objectivity of image reconstruction.
With emerging new methods of cryo-TEM imaging and image reconstruction the new software solutions appear that help to automate the process. After the empirical Bayesian approach have been implemented in the open source computer program RELION (REgularized LIkelihood OptimizatioN) for 3D reconstruction, the program became widespread in the cryo-TEM field. It offers a range of corrections that improve the resolution of reconstructed images, allows implementing versatile scripts using python language and executes the usual tasks of 2D/3D model classifications or creating de novo models.
The Danish National cryo-EM Facility also known as EMBION was inaugurated on December 1, 2016. EMBION is a cryo-EM consortium between Danish Universities (Aarhus University host and University of Copenhagen co-host).
(scale bar represents 200 nm)Xiao, C., Fischer, M.G., Bolotaulo, D.M., Ulloa-Rondeau, N., Avila, G.A., and Suttle, C.A. (2017) "Cryo-EM reconstruction of the Cafeteria roenbergensis virus capsid suggests novel assembly pathway for giant viruses". Scientific Reports, 7: 5484. .
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