Lecture 8 Video 6

Protein structure

❄️ Cryo-Electron Microscopy (Cryo-EM) — Full Workflow Summary

Cryo-EM is one of the most powerful modern structural biology methods. It allows scientists to determine 3D structures of proteins and complexes — often at near-atomic resolution — without crystallization.

This lecture walks step-by-step through:

  • Sample preparation
  • Grid freezing (vitrification)
  • Data collection in the microscope
  • Image processing and 3D reconstruction
  • Comparison to other EM methods

Let’s go through everything in a logical and fun way.


🧪 Step 1 — The Most Important Rule: Make a Perfect Sample

Before anything else, you must have:

Highly purified proteinHomogeneous sample (no aggregation)Fresh preparation

Structural biology rule number one:

The quality of the structure is limited by the quality of the sample.

Typical purification workflow:

  • Ion-exchange chromatography → elution peak
  • SDS-PAGE → purity increases step-by-step
  • Final polishing: Size-exclusion chromatography just before freezing

This is done because:

  • Proteins can aggregate or degrade if left on ice
  • Sensitive samples (like membrane proteins) must be extremely fresh

🧫 Step 2 — Applying Sample to the EM Grid

You apply ~3 µL of protein solution onto an EM grid.

What is an EM grid?

  • Diameter: ~3.05 mm
  • Metal mesh with square holes
  • Mesh density: 200–400 lines per inch
  • Square openings: ~65–130 µm
  • On top sits a carbon or gold foil with tiny holes (~1–2 µm)

These holes are crucial — they will contain the thin ice film holding the proteins.


💧 Step 3 — Blotting & Vitrification (Flash Freezing)

This happens in a plunge freezer chamber:

Conditions:

  • ~100% humidity
  • ~4–5 °C
  • Prevents evaporation during preparation

Process:

  1. Make grid surface hydrophilic
  2. Apply sample
  3. Blot away 99.99% of liquid
  4. Immediately plunge into liquid ethane (~−184 °C)

Why liquid ethane?

  • Very high heat capacity → ultra-fast cooling
  • Prevents formation of crystalline ice
  • Produces vitreous (glass-like) ice

Result:

  • Thin ice film (~30 nm)
  • Proteins are randomly oriented and trapped in native buffer conditions

Then grids are stored in:

👉 Liquid nitrogen (~−196 °C)


🔬 Step 4 — Imaging in the Cryo-Electron Microscope

Example instrument:

  • Titan Krios
  • 300 kV transmission electron microscope
  • Operated at cryogenic temperatures

Modern microscopes use:

🎥 Movie mode data collection

Instead of one long exposure:

  • Multiple frames are collected
  • Motion correction is applied
  • This removes beam-induced drift

Without this:

❌ Images would be blurred With correction:

✅ Sharp individual particle images → high resolution possible

Typical total electron dose:

  • ~60 electrons / Ų

Low dose is necessary to:

👉 Avoid radiation damage

But it also causes:

⚠️ Very low contrast images — a key Cryo-EM challenge.


🧩 Step 5 — Particle Picking

Each micrograph contains:

  • Hundreds to thousands of particles

Scientists:

  • Identify x-y coordinates of each particle
  • Cut out small image boxes
  • Build large datasets (100,000 → 1,000,000 particles)

Each particle image is:

👉 A 2D projection of the 3D protein

Because proteins are randomly oriented in the ice.


📊 Step 6 — 2D Classification & Averaging

Particles are grouped based on:

  • Similar projection views

Within each class:

  • Images are averaged

Why?

  • Signal is consistent
  • Noise is random

Therefore:

✨ Signal-to-noise dramatically improves

This also helps remove:

🗑️ Junk particles 🦠 Contaminants ⚙️ Damaged proteins

This cleaning step is essential.


🧠 Step 7 — Determining Angular Relationships (Fourier Space Magic)

Key principle:

  • Fourier transform of a 2D projection = slice through the 3D Fourier transform

All projections share common lines in Fourier space.

Using this:

  • Angular relationships between views can be determined
  • 3D Fourier space is gradually filled
  • Inverse Fourier transform reconstructs the 3D object

This is one of the most elegant mathematical ideas in structural biology.


🧊 Step 8 — 3D Reconstruction (Electrostatic Potential Map)

Final result:

👉 A 3D electrostatic potential map

Important distinction:

MethodMap type
X-ray crystallographyElectron density
Cryo-EMElectrostatic potential

Electrons interact with:

  • Atomic nuclei electrostatic potential

X-rays interact with:

  • Electron clouds

But visually:

👉 Maps look very similar

So:

  • Atomic models can be built into Cryo-EM maps just like X-ray maps.

🔁 Step 9 — Iterative Refinement Cycle

Processing is iterative:

  1. Initial 3D model built
  2. Generate projections
  3. Align particles again
  4. Remove bad classes
  5. Reconstruct new map

This continues until:

👉 Resolution cannot improve further

Then:

  • Resolution is estimated (e.g., correlation coefficients)
  • Final map + atomic model are deposited in databases.

⚖️ Negative Stain vs Cryo-EM (Two Single-Particle Methods)

🧪 Negative Stain EM

Uses:

  • Heavy metal salts (e.g., uranyl acetate)

Advantages:

✅ Very high contrast ✅ Cheap ✅ Fast ✅ Good for small proteins (<40 kDa) ✅ Great for checking sample quality

Disadvantages:

❌ Low resolution (~20–40 Å) ❌ Drying artifacts possible

Good for:

👉 Initial screening and heterogeneity assessment.


❄️ Cryo-EM

Advantages:

✅ Native hydrated environment ✅ No fixatives ✅ Can reach atomic resolution ✅ Best structural method for large complexes

Disadvantages:

⚠️ Very low contrast ⚠️ Technically demanding ⚠️ Requires expensive instrumentation


⭐ Big Conceptual Takeaways

  • Cryo-EM reconstructs 3D structures from many 2D projections
  • Sample quality determines structural success
  • Rapid vitrification preserves native state
  • Iterative classification and refinement improve resolution
  • Fourier space alignment is key to angular determination
  • Modern detectors + movie mode enabled the Cryo-EM revolution

Quiz

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