- The electron detector detects the electrons to create the protein image. 
- Electron detectors have a detective quantum efficiency, or DQE, which shows the signal:noise ratio of the incoming signal is degraded by errors in the detection process. An ideal detector would not add any noise.  
- MAPS – monolithic active pixel sensors are direct electron detectors. They have detectors where electrons pass through a membrane and are backscattered. 
- However, improvements in the DQE lowers the “noise” created from removing the matrix and having a very thin detector that allows the electrons to pass through without backscattering too. 


Direct electron detectors and importance in Cryo-EM structures

- When the electron beam hits the thin film of vitreous ice, chemical bonds are broken and charges start to build up. This destroys the sample and can induce motion which causes blurring. 
- Improvements of resolution of reconstructed maps were obtained in projects. A motion-correction algorithm was developed that tracked motions of individual particles which showed the asymmetric particles, 4A details, and side chain densities which are major improvements for Cryo-EM structures. 
- When combined with the new detectors Cryo-EM is more promising. Images with stronger signal led to higher resolution maps but less noisy images allowed the new image-processing algorithms to make more than before. This also led to less blurry images.


Improvements in Image processing 

- With Cryo-EM improvements, we can solve structures de novo (structure shown below is de novo Cryo-EM structuree of a TRPV1 ion channel that is close to 3 Angstroms).
- Cryo-EM density maps are reminiscent of those from X-ray crystallography. Cryo-EM is clearer because the phase information that is normal lost in X-ray crystallography structures. This makes them clearer than X-ray crystal structures. 
- Visualizing small molecule compounds – new resolutions also allow for small molecules to be seen like co-factors and inhibitors. 
- the ability to improve the quality protein images is important in so many fields - in combating antibiotic resistance, drug design, and determine mechanisms and functions of proteins. 


What is now possible with Cryo-EM structures? 

- It is typically difficult to determine the structure of samples with more than one unique structure. 
- The development of many statistical algorithms based on maximum-likelihood procedures have been made with promising results. 
- Statistical analyses and 3D variance calculation, non-statistical multi particle refinement calculations were added as well. This was implemented in the RELION program which has been a very powerful tool for 3D classification and high-resolution reconstruction that has quickly gained popularity. 

Solving complex 3D structures with Cryo-EM structures 

- New generation of electron detectors
- Improved image processing 
- Ability to solve complex structures


Grand Valley State University

- In the beginning of cryo-EM technology, 3D image calculations from 2D images were used in combination with cyro-EM. This approach was successful for proteins with certain structures like helical shapes. 
- For subjects that lack orderly patterns, cryo-EM single-particle analysis which uses a purified solution of macromolecules that may be imaged directly, was used. 3D constructions are calculated from projections of complexes and particles. However, the orientation of the particles are unknown. 
- Gradual progress occurred with a 40 Angstrom (very low resolution structure) to a near 10 Angstrom image around the 2000s. 


Brief history and progression of Cryo-EM technology  

Bai, X., McMullan, G., & Scheres, S. H. W. (2015). How cryo-EM is revolutionizing structural biology. Trends in Biochemical Sciences, 40(1), 49–57. https://doi.org/10.1016/j.tibs.2014.10.005

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