Structural Information Obtained by
Electron Microscopy
Christiane Berger-Schaffitzel, 21.05.2015
Resolution Revolution in Cryo-EM
E.Coli 70S-EF-Tu complex, ~2.65-2.9 Å
Fischer et al., Nature 2015
Structure of TRPV1 ion channel, 3.4 Å
Liao et al., Nature 2013
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Green alga mitochondrial F-type
ATP synthase, 6.2 Å
Allegretti et al., Nature 2015
Complex I from B. taurus heart mitochondria,
5Å
Vinothkumar et al., Nature 2014
Smaller Asymmetrical Membrane Proteins
Human g-secretase complex, 5.4 Å
170 kDa
Lu et al., Nature 2014
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Electron Microscopy
• Sample preparation – negative stain vs. cryo
• Data collection
• Image processing
• Advances in detector hardware
• New image processing strategies
• Further improvements, structure validation
4
How can we study structures at the molecular level by
electron microscopy?
Light
Microscope
Resolution:
~ 100 nm
Electron
Microscope
Resolution:
Near-atomic
(2.2 Å)
Electron Microscope
Single Particle EM – Different Techniques
Negative Stain EM
Slide: John Briggs
6
Single Particle EM – Negative Stain
Negative Stain EM
Advantage:
Disadvantage:
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Scale bar : 20 nm
nice contrast of the molecules
can be done at room temperature, fast
great for sample quality control
the resolution is limited by the stain.
staining artefacts, flattening ,
only the envelope is obtained
Cryo-EM sample preparation
Freezing Grids
3-6 ml of sample (nanomolar concentration) required
Holey
carbon
film
vitreous ice (200-500 Å)
thick carbon (150 Å)
copper grid
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Cryo-Electron Microscopy
100 nm
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What is a Cryo-EM Image?
It is a projection image.
Mark Ian Berger
10
What is a Cryo-EM Image?
It is a very noisy projection image, lacking information.
11
It is noisy because of limited electron dose.
12
Beam Damage, an other example
The image lacks information because it is modulated by a
transfer function
contrast transfer function (CTF)
atoms will appear
bright on a dark
background
envelope
function
Information
limit
no contrast
atoms will
appear dark on
a bright
background
The regions with no
contrast depend on the
defocus of the image
• Images need to be phase-flipped to obtain high resolution.
• To fill the gap of information, images with different defocus
are recorded and used for structure calculation.
diagram:
Henning Stahlberg
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Single Particle EM – 2D Image Processing
S
4
9
16
25
36
1. We need to
average over
many images.
2. We need to sort
for different
views of our
object.
49
64
81
100
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Signal-to-noise ratio
growths with √n
Single Particle EM – Alignment
Averaging requires alignment:
Shift and Rotation
Alignment works better for larger particles.
For perfect images the theoretical lower size limit
is 40 kDa (Henderson, 1995).
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2D Alignment
Tomography versus Single Particle Analysis
Tomography
Split the electron dose.
One object is turned in the electron beam
 many 2D images with known orientation
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Single Particle Analysis
Use the max. electron dose for one image.
Many particles with unknown orientation
 Starting model required
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Workflow Refinement
3D Starting Model
e.g. from random conical tilt
reconstruction
3D reconstruction
Projections
used as reference for the
next round of projection
matching
Re-project
of the starting model
Euler Angles known
Back-project
Use the known
angular relationships
Alignment
Classification
Average
2D classes
rotation, shift
based on crosscorrelation
Generation of
2D class averages
Euler angles assigned
Data
Individual
Picked Particles
What is the reason for this jump in resolution?
• Cryo-EM sample preparation
• Data collection
• Image processing
• Advances in detector hardware
• New image processing strategies
• Further improvements, structure validation
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Direct Electron Detectors
Signal to noise ratio is the major challenge in cryo-EM.
•
•
more sensitive
faster than CCD camera &
photographic film.
New data collection strategy:
many frames per second
→ allows the detection of
movements on the Å scale.
DQE: frequency dependent measure for signal to noise ratio performance
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Li et al., Nat. Methods 2013
Motion Correction
Direct electron detectors record movie frames.
25-fold
exaggerated
particle
movement
10 Å
movements!
50 nm
Bai et al., elife 2013
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Motion Correction
•
•
•
average over similar frames
correct for motion
reject first and last frames due to
motion and beam damage
Gain in resolution: 1-2 Å
Li et al., Nat. Methods 2013
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Maximum Likelihood
Reference-based Alignment
Initial model, 2D
reference projection(s)
data
Rotation and Shift
Determination of the cross-correlation
max. cc , real space alignment
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Maximum Likelihood
Do not assign discrete orientations to the data and make hard
decisions if the noise in the data does not allow it.
Many iterations until convergence
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Scheres et al., Nat. Protocols 2008
Maximum Likelihood – 3D classification
~10 Å
Filter model to low resolution: 80 Å
fragmented,
low occupancy
Decide on number of volumes
Run many iterations until the maps
are stable
5.7 Å
Von Löffelholz et al., PNAS 2015
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Scheres et al., Nat. Methods 2007
• Cryo-EM sample preparation
• Data collection
• Image processing
• Advances in detector hardware
• New image processing strategies
• Further improvements, structure validation
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Recent Improvements
• Thinner detectors
• Faster readout rates
• New image recording procedures that reduce
beam-induced movements
• New Supports for grid preparation: graphene and
gold grids reduce beam-induced movement
(Russo & Passmore, Science 2014)
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Graphene and Gold Grids
Gold support is even superior (unpublished).
Russo & Passmore, Nat. Methods 2014
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Validation Tools
Data coverage & agreement between original data and map:
• Comparison of map projections and reference-free 2D class averages
• Plot for particle orientation distribution coverage (Euler angles)
Accuracy of the angular assignment and correct handedness:
• Tilt pair validation
Final resolution:
• ‘Gold-standard’ refinement
•
Agreement between visible features and claimed resolution: e.g. at 4.5 Å helical pitch
and b-strand separation should be visible and bulky side chains.
• Map variance, local resolution determination
→ A satisfactory validation tool does not exist yet.
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12 Å
10 Å
8Å
6Å
4Å
Combination of EM and SAXS/SANS
Example1:
Šulák O. et al. (2011)
Burkholderia cenocepacia BC2L-C Is a Super Lectin with Dual Specificity and Proinflammatory Activity.
PLoS Pathog 7(9): e1002238. doi:10.1371/journal.ppat.1002238
SAXS
ab initio model
EM
reconstruction
Lectins:
Bacterial
adhesion
proteins to
host cells
Projections
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2D classes
Combination of EM and SAXS/SANS
Example 2:
Martin Alcorlo et al.
Unique structure of iC3b resolved at a resolution of 24 Å by 3D-electron microscopy
PNAS 2011 vol. 108 no. 32 13236-13240
Negative stain EM:
2D class averages of different C3
convertase activation states
TED: thioester containing domain
MG: macroglobulin ring
SAXS:
global shapes of the same
C3 convertase activation states
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C3 is a complement factor which is cleaved to generate the activated fragment (C3b).
Proteolysis of C3B leads to formation of iC3b which is targeting pathogens for clearance by phagocytosis.
Single Particle Reconstructions - Summary
Requirements for Object:
• Objects must exist in multiple identical copies (but heterogeneity
can be taken into account!)
• Limited number of conformations (ideally 1)
• Mass for unstained specimens should be >200 kDa
Typical Objects:
• Large Proteins and Complexes
How much do we need? (50-100 mg)
Mode of Data-Collection:
• Many low dose micrographs, movie-mode
Achievable Resolution:
• 3 Å possible (depends on sample quality)
• Resolution is isotropic (if no preferential views)
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Schaffitzel Team:
Boris Eliseev
Karine Huard
Qijang Jiang
Manikandan Karrupasamy
Etienne Raimondeau
Taiana Maia de Oliveira
Lahari Yeramala
Sarah Zorman
Former Members:
Christoph Bieniossek
Mathieu Botte
Aurélien Deniaud
Leandro F. Estrozi
Kèvin Knoops
Ottilie von Löffelholz
Jelger Lycklama à Nijeholt
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Collaborators:
Contact:
Guiseppe Zaccai (ILL)
Nathan Zaccai (Bristol)
Ian Collinson (Bristol)
[email protected]
[email protected]