Electron cryomicroscopy

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Single-particle electron cryomicroscopy (cryo-EM) has become an important method for determining macromolecular structures[1]. It is the basis for the 2017 Nobel Prize in Chemistry. Although resolution is usually poorer than that obtained by X-ray crystallography, cryo-EM has the great advantage of not requiring crystallization[2]. Cryo-EM is particularly suited to determination of the structures of large complexes containing multiple proteins or nucleic acids, often the most difficult to crystallize.

For a quick overview of the method, see this silent 3 min video by Gabe Lander. For a historical view of the development of modern cryo-EM, see this scientific background for the 2017 Nobel prize. For a more detailed discussion, see this primer[1].


Docking crystal structures into cryo-EM maps

Early studies showed that docking of monomer crystal structures into even poor-resolution (e.g. 15 Å) cryo-EM maps of larger assemblies could reliably predict structure[3]. Subsequently, many methods, including docking while allowing flexibility in the monomers, have been developed[4].


Drag the structure with the mouse to rotate

Density Maps


Density map for heme and two histidines in the 3.4
Å cryo-EM structure of a cytochrome (6nef).

The result of a cryo-EM experiment is a density map. Just as for X-ray diffraction, it is then necessary to fit an atomic model optimally into the map[1].

Cryo-EM "has the advantage of recording images containing both amplitude and phase information, so there is no phase problem as in [X-ray] crystallography"[6].

Electrons are diffracted by the charges in the sample, in contrast to X-rays that are diffracted by electron density, producing electron density maps. Consequently, EM maps may be termed "electron potential maps"[6], "Coulomb potential maps"[7], or "electric potential maps"[8]. Electron densities are all positive, while electron potential maps can be positive or negative[8][7]. Wang (2017)[9] provided a way to convert electron potential maps to charge density maps (using Chimera), where densities have better resolution and better reflect the positions of atomic nuclei.

Visualizing EM Maps

FirstGlance in Jmol makes it easy to visualize EM density maps, as shown in the example at right. Load your PDB ID (or 6nef). Then, use Find.. (in the Focus Box) to locate the residues of interest (or "503,169,360" for 6nef -- In 6nef, these happen to be unambiguous sequence numbers for HEC503, HIS169, and HIS360.) Click on "EM Density Map". After adjusting the view as you wish, click "Save Image or Animation for Powerpoint". An example of an animation saved from FirstGlance is above in this page.

Density map viewers are also available at each of the 3 branches of the wwPDB. They are somewhat more complex and technical than the map viewer in FirstGlance. These viewers are also capable of saving animations, although the interfaces are more technical than what FirstGlance offers.

The Electron Microscopy Data Bank

The Electron Microscopy Data Bank (EMDB) archives EM density maps. Only "all features" maps are deposited, as cryo-EM analysis has no equivalent to the difference map of X-ray diffraction.

Temperatures (B factors)

PDB files for models determined by cryo-EM often specify values in the temperature/B factor field. However, a 2017 analysis concluded that "the treatment of the atomic displacement (B) factors was meaningless in almost all analyzed cryo-EM models"[10].


Protein Identification

In the 21st century, the amino acid sequence identity of a protein is nearly always known before its structure is determined. This is because the gene is usually cloned, the protein expressed and purified, prior to crystallization. However, it is also possible to purify macromolecular assemblies in which the proteins are not identified in advance, and determine their structures by cryo-EM. If sufficient resolution is achieved (~3.5 Å or better), candidate amino acid sequences can be matched, or excluded, as components of the structure. Thus, typically combined with mass spectrometry, cryo-EM can help identify which proteins are present in a structure[12][13].

An example is the electrically-conductive protein nanowires made by bacteria, notably Geobacter sulfurreducens. Cryo-EM structure revealed that some of these fibers are assembled from C-type cytochrome OmcS[14][15]. This was a surprise since they had long been thought to be assembled from a completely different protein, pilA.

See Also


Electron cryo-microscopy, Cryo-electron microscopy and Cryo-EM redirect to this page.

Notes and References

  1. 1.0 1.1 1.2 1.3 1.4 Cheng Y, Grigorieff N, Penczek PA, Walz T. A primer to single-particle cryo-electron microscopy. Cell. 2015 Apr 23;161(3):438-449. doi: 10.1016/j.cell.2015.03.050. PMID:25910204 doi:http://dx.doi.org/10.1016/j.cell.2015.03.050
  2. Obtaining highly-ordered crystals is perhaps the major obstacle to determination of structure by X-ray diffraction. Less than half of cloned, expressed, purified proteins are sufficiently soluble for structure determination. Of these, diffraction-quality crystals are obtained for only about one in five. See Structural Genomics Progress, 2011.
  3. Roseman AM. Docking structures of domains into maps from cryo-electron microscopy using local correlation. Acta Crystallogr D Biol Crystallogr. 2000 Oct;56(Pt 10):1332-40. PMID:10998630
  4. Kim DN, Sanbonmatsu KY. Tools for the cryo-EM gold rush: going from the cryo-EM map to the atomistic model. Biosci Rep. 2017 Dec 5;37(6). pii: BSR20170072. doi: 10.1042/BSR20170072. Print, 2017 Dec 22. PMID:28963369 doi:http://dx.doi.org/10.1042/BSR20170072
  5. 5.0 5.1 See cryo-EM Resolution compared with X-ray diffraction resolution: tinyurl.com/method-vs-resolution.
  6. 6.0 6.1 Rosenthal PB. Interpreting the cryo-EM map. IUCrJ. 2019 Jan 1;6(Pt 1):3-4. doi: 10.1107/S2052252518018304. eCollection 2019, Jan 1. PMID:30713698 doi:http://dx.doi.org/10.1107/S2052252518018304
  7. 7.0 7.1 Marques MA, Purdy MD, Yeager M. CryoEM maps are full of potential. Curr Opin Struct Biol. 2019 Oct;58:214-223. doi: 10.1016/j.sbi.2019.04.006. Epub , 2019 Aug 7. PMID:31400843 doi:http://dx.doi.org/10.1016/j.sbi.2019.04.006
  8. 8.0 8.1 Wang J, Moore PB. On the interpretation of electron microscopic maps of biological macromolecules. Protein Sci. 2017 Jan;26(1):122-129. doi: 10.1002/pro.3060. Epub 2016 Oct 15. PMID:27706888 doi:http://dx.doi.org/10.1002/pro.3060
  9. Wang J. Experimental charge density from electron microscopic maps. Protein Sci. 2017 Aug;26(8):1619-1626. doi: 10.1002/pro.3198. Epub 2017 May 31. PMID:28543856 doi:http://dx.doi.org/10.1002/pro.3198
  10. Wlodawer A, Li M, Dauter Z. High-Resolution Cryo-EM Maps and Models: A Crystallographer's Perspective. Structure. 2017 Oct 3;25(10):1589-1597.e1. doi: 10.1016/j.str.2017.07.012. Epub, 2017 Aug 31. PMID:28867613 doi:http://dx.doi.org/10.1016/j.str.2017.07.012
  11. Zhao J, Benlekbir S, Rubinstein JL. Electron cryomicroscopy observation of rotational states in a eukaryotic V-ATPase. Nature. 2015 May 14;521(7551):241-5. doi: 10.1038/nature14365. PMID:25971514 doi:http://dx.doi.org/10.1038/nature14365
  12. Ho CM, Li X, Lai M, Terwilliger TC, Beck JR, Wohlschlegel J, Goldberg DE, Fitzpatrick AWP, Zhou ZH. Bottom-up structural proteomics: cryoEM of protein complexes enriched from the cellular milieu. Nat Methods. 2019 Nov 25. pii: 10.1038/s41592-019-0637-y. doi:, 10.1038/s41592-019-0637-y. PMID:31768063 doi:http://dx.doi.org/10.1038/s41592-019-0637-y
  13. Terwilliger TC, Sobolev OV, Afonine PV, Adams PD, Ho CM, Li X, Zhou ZH. Protein identification from electron cryomicroscopy maps by automated model building and side-chain matching. Acta Crystallogr D Struct Biol. 2021 Apr 1;77(Pt 4):457-462. doi:, 10.1107/S2059798321001765. Epub 2021 Mar 30. PMID:33825706 doi:http://dx.doi.org/10.1107/S2059798321001765
  14. Wang F, Gu Y, O'Brien JP, Yi SM, Yalcin SE, Srikanth V, Shen C, Vu D, Ing NL, Hochbaum AI, Egelman EH, Malvankar NS. Structure of Microbial Nanowires Reveals Stacked Hemes that Transport Electrons over Micrometers. Cell. 2019 Apr 4;177(2):361-369.e10. doi: 10.1016/j.cell.2019.03.029. PMID:30951668 doi:http://dx.doi.org/10.1016/j.cell.2019.03.029
  15. Filman DJ, Marino SF, Ward JE, Yang L, Mester Z, Bullitt E, Lovley DR, Strauss M. Cryo-EM reveals the structural basis of long-range electron transport in a cytochrome-based bacterial nanowire. Commun Biol. 2019 Jun 19;2:219. doi: 10.1038/s42003-019-0448-9. eCollection 2019. PMID:31240257 doi:http://dx.doi.org/10.1038/s42003-019-0448-9

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