Electron Microscopy 3 Flashcards Preview

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Flashcards in Electron Microscopy 3 Deck (14):

How is the image produced related to the actual object?

The image is a 2D projection of a 3D object.


What does intensity represent in the 2D image?



Why are multiple 2D images used?

These projections show different orientations of the 3D object.


To overcome the bad signal-to-noise ratio what must assume about the single particles and what must be done to them?

Must assume that they are all the same.
Then average the single particles and filter out the noise.


What must be done to create the 3D model from the 2D images?

Must use the relationship between 2D and 3D Fourier transforms to obtain a 3D model.


What is a Fourier Transform?

It is a convenient mathematical representation of images - (sine waves)


What can you use a Fourier Transform to do?

You can go back and forth between real space (image) and reciprocal/Fourier space (transform) by using the Fourier transform equation and its inverse equation.


What is the method to generate the structure?

Collect all 2D images (orientations) - use the Fourier transform to relate all them together - then do the inverse Fourier transform of the all the related orientations to generate the structure.
(Note = think paper in box analogy).


What does the projection theorem describe?

The relationship between 2D projections collected on the electron microscope and the 3D Fourier transform of the original object.


What does the positioning of the central sections of the 3D Fourier transform depend on?

The orientation parameters of the 2D projection.


What are the Fourier transforms in EM?

These are the different orientations of the molecule.


Why will the averages of the single particles differ slightly from the original object?

They do not completely align - they are all in slightly different orientations.


What can averaging significantly different images do to the overall image?

Degrade the quality and make very noisy.


What happens if the protein has different conformations when averaging?

Can end up with a bad model - combinations of different conformations.