Three-Dimensional Electron Microscopy of Macromolecular Assemblies: Visualization of Biological Molecules in Their Native State

✍ Scribed by Joachim Frank

• Publisher: Oxford University Press, USA
• Year: 2006
• Tongue: English
• Leaves: 427
• Edition: 2
• Category: Library

✦ Synopsis

This concise and easy to read book is essentialy a crash course in single particle reconstruction by electron microscopy. It isn't exactly a how-to manual, more an overview of how the whole process works. Thus, it is useful not only to someone who wants to learn how to do this, but also to those who might be interested in deciding if this technique would be useful to them. And actually, the whole topic is sufficiently cool that I would recommend the book even to people who know they will never use this technique, just because its fun to read about it. The book is clearly written and doesn't assume alot of prior knowledge. A basic undergrad education in math would be enough to handle the equations.

✦ Table of Contents

Cover Page......Page 1
Title Page......Page 4
ISBN 0195182189......Page 5
Preface......Page 8
Contents (with page links)......Page 10
1.1 General Remarks......Page 18
1.2 Three-Dimensional Electron Microscopy......Page 19
2 Single-Particle Versus Crystallographic Analysis......Page 22
3 Crystallography without Crystals......Page 24
4 Toward a Unified Approach to Structural Analysis of Macromolecules......Page 26
5 Single-Particle Reconstruction, Macromolecular Machines, and Structural Proteomics......Page 27
6 The Electron Microscope and the Computer......Page 29
1 Principle of the Transmission Electron Microscope......Page 32
2.1 Introduction......Page 36
2.2 Negative Staining......Page 37
2.3 Glucose Embedment......Page 44
2.5 Ice-Embedded Specimens......Page 45
2.6 Hybrid Techniques: Cryo-Negative Staining......Page 48
2.8 Support Grids......Page 50
3.1 Introduction......Page 51
3.2 The Weak-Phase Object Approximation......Page 52
3.3 The Contrast Transfer Theory......Page 56
3.4 Amplitude Contrast......Page 64
3.5 Formulation of Bright-Field Image Formation Using Complex Atomic Scattering Amplitudes......Page 66
3.6 Optical and Computational Diffraction Analysis—The Power Spectrum......Page 67
3.7 Determination of the Contrast Transfer Function......Page 70
3.8 Instrumental Correction of the Contrast Transfer Function......Page 74
3.9 Computational Correction of the Contrast Transfer Function......Page 75
3.10 Locally Varying CTF and Image Quality......Page 79
4.1 Low-Dose Electron Microscopy......Page 81
4.2 Spot Scanning......Page 83
4.3 Energy Filtration......Page 84
4.4 Direct Image Readout and Automated Data Collection......Page 85
CHAPTER 3 Two-Dimensional Averaging Techniques......Page 88
1.1 The Different Sources and Types of Noise......Page 89
1.2 Principle of Averaging: Historical Notes......Page 91
1.3 Equivalence between Averaging and Quasi-Optical Fourier Filtration......Page 92
1.5 The Role of Two-Dimensional Averaging in the Three-Dimensional Analysis of Single Molecules......Page 95
1.6 Origins of Orientational Preferences......Page 96
2.1 Hardware for Digitization......Page 100
2.2 The Sampling Theorem......Page 101
2.3 Interactive Particle Selection......Page 103
2.4 Automated Particle Selection......Page 104
3.1 Quantitative Definitions of Alignment......Page 108
3.2 Homogeneous Versus Heterogeneous Image Sets......Page 109
3.3 Translational and Rotational Cross-Correlation......Page 111
3.4 Reference-Based Alignment Techniques......Page 117
3.5 Reference-Free Alignment Techniques......Page 126
4.1 The Statistics of Averaging......Page 132
4.2 The Variance Map and the Analysis of Statistical Significance......Page 134
4.3 Signal-to-Noise Ratio......Page 138
5.1 The Concept of Resolution......Page 141
5.2 Resolution Criteria......Page 143
5.3 Resolution and Cross-Resolution......Page 154
5.4 Resolution-Limiting Factors......Page 155
5.5 Statistical Requirements following the Physics of Scattering......Page 156
5.6 Noise Filtering......Page 157
6 Validation of the Average Image......Page 159
1 Introduction......Page 162
1.1 Heterogeneity of Image Sets......Page 163
1.2 Images as a Set of Multivariate Data......Page 164
1.3 The Principle of Making Patterns Emerge from Data......Page 165
1.4 Multivariate Data Analysis: Principal Component Analysis Versus Correspondence Analysis......Page 166
2 Theory of Correspondence Analysis......Page 170
2.1 Analysis of Image Vectors in R[sup(J)]......Page 171
2.2 Analysis of Pixel Vectors in R[sup(N)]......Page 172
2.3 Factorial Coordinates and Factor Maps......Page 173
2.4 Reconstitution......Page 174
2.6 Significance Test......Page 178
3.2 Definition of the Image Region to Be Analyzed......Page 179
3.3 Eigenvalue Histogram and Factor Map......Page 183
3.4 Case Study: Ribosome Images......Page 186
3.5 Use of Explanatory Tools......Page 189
4.1 Background......Page 193
4.2 Overview over Different Approaches and Goals of Classification......Page 194
4.3 K-Means Clustering......Page 195
4.4 Hierarchical Ascendant Classification......Page 197
4.5 Hybrid Clustering Techniques......Page 199
4.6 Inventories......Page 201
4.8 Nonlinear Mapping......Page 202
4.9 Self-Organized Maps......Page 203
4.10 Supervised Classification: Use of Templates......Page 205
4.11 Inference from Two to Three Dimensions......Page 206
1 Introduction......Page 210
2.1 The Projection Theorem and Radon’s Theorem......Page 211
2.2 Object Boundedness, Shape Transform, and Resolution......Page 213
2.3 Definition of Eulerian Angles, and Special Projection Geometries: Single-Axis and Conical Tilting......Page 215
3.1 Introduction......Page 218
3.2 Cylindrically Averaged Reconstruction......Page 219
3.3 Compatibility of Projections......Page 222
3.4 Relating Projections to One Another Using Common Lines......Page 223
3.5 The Random-Conical Data Collection Method......Page 227
3.6 Comparison of Common Lines Versus Random-Conical Methods......Page 229
4.1 Preliminaries......Page 230
4.2 Weighted Back-Projection......Page 231
4.3 Fourier Reconstruction Methods......Page 236
4.4 Iterative Algebraic Reconstruction Methods......Page 238
5.2 Optical Diffraction Screening......Page 239
5.3 Interactive Tilted/Untilted Particle Selection......Page 242
5.4 Optical Density Scaling......Page 243
5.5 Processing of Untitled-Particle Images......Page 244
5.6 Processing of Tilted-Particle Images......Page 245
5.7 Carrying Out the Reconstruction......Page 248
7.1 Introduction......Page 249
7.2 Three-Dimensional Projection Matching......Page 253
7.3 Numerical Aspects......Page 257
7.4 Three-Dimensional Radon Transform Method......Page 259
7.5 The Size of Angular Deviations......Page 260
7.6 Model Dependence of the Reconstruction......Page 263
8.1 Theoretical Resolution of the 3D Reconstruction......Page 264
8.2 Practically Achieved Resolution......Page 265
8.3 Cross-Validation Using Excision of Fourier Data from the 3D Reference......Page 270
9.2 Contrast Transfer Function Correction......Page 272
9.3 Fourier Amplitude Correction......Page 276
10.1 Introduction......Page 278
10.2 Theory of Projection onto Convex Sets......Page 279
10.3 Projection onto Convex Sets in Practice......Page 281
11.2 Separating Ligand-Bound from Ligand-Free Complexes......Page 283
11.3 Separating Populations with Different Conformations......Page 284
12.1 The Rationale for Merging......Page 287
12.2 Negatively Stained Specimens: Complications due to Preparation-Induced Deformations......Page 288
12.3 Alignment of Volumes......Page 289
12.4 Merging of Reconstructions through Merging of Projection Sets into a Common Coordinate Frame......Page 292
12.5 Classification of 3D Volumes......Page 293
1 Introduction......Page 294
2.1 Introduction......Page 296
2.2 Three-Dimensional Variance Estimation from Projections......Page 297
2.3 Use of the 3D Variance Estimate to Ascertain the Statistical Significance......Page 301
3.2 Reconstructions from the Same Data Set with Different Algorithms......Page 303
3.3 Consistency with X-Ray Structures......Page 304
3.4 Concluding Remarks......Page 308
4 Visualization and Rendering......Page 310
4.1 Surface Rendering......Page 311
4.2 Definition of Boundaries......Page 313
4.3 Volume Rendering......Page 314
5 Segmentation of Volumes......Page 315
5.2 Segmentation Based on Density Alone......Page 316
5.3 Knowledge-Based Segmentation, and Identification of Regions......Page 320
6 Methods for Docking and Fitting......Page 325
6.1 Manual Fitting......Page 326
6.2 Quantitative Fitting......Page 328
7 Classification of Volumes......Page 333
Appendix 1 Some Important Definitions and Theorems......Page 336
Appendix 2 Profiles, Point-Spread Functions, and Effects of Commonly Used Low-Pass Filters......Page 344
Appendix 3 Bibliography of Methods......Page 348
Appendix 4 Bibliography of Structures......Page 354
Appendix 5 Special Journal Issues on Image Processing Techniques......Page 360
References......Page 362
A......Page 416
C......Page 417
E......Page 419
H......Page 420
M......Page 421
P......Page 422
R......Page 423
S......Page 425
V......Page 426
Z......Page 427