Protein Crystallization Strategies for Structural Genomics

1.    Structural Genomics in the United States: The NIGMS Protein Structure Initiative     1
Charles G. Edmonds and John C. Norvell    
2.    A Guide to Automation and Data Handling in Protein Crystallization     9
Bernhard Rupp
       2.1.    Introduction     11
       2.2.    High-Throughput Protein Structure Determination     13
                 2.2.1.    Why High Throughput?     13
                 2.2.2.    Definition of High Throughput     13
                 2.2.3.    High Throughput versus Low Throughput     14
                 2.2.4.    Estimation of Throughput     14
                 2.2.5.    The Data Explosion     17
                2.2.6.     Information Technology Infrastructure      18
                2.2.7.     Data Mining and Machine Learning      19 
       2.3.    Overview of Protein Crystallization     21
                 2.3.1.    Basics of Protein Crystallization     21
                 2.3.2.    Experimental Crystallization Setup Techniques     23
                 2.3.3.    Experimental Design Considerations     25
                 2.3.4.    Crystallization Screening as a Sampling Problem     26
                 2.3.5.    Robotics and Flexible Design Strategies     26
       2.4.    Implementation of Robotic Technology—General Considerations     28
                 2.4.1.    Efficiency versus Throughput     29
                 2.4.2.    Patent and Licensing Issues     30
                 2.4.3.    Service and Maintenance      31
       2.5.    Implementation of Robotics in the Academic Laboratory     31
                 2.5.1.    Objectives and Cost     32
                 2.5.2.    Bottlenecks     33
                 2.5.3.    Kits versus Custom Cocktails      34
                 2.5.4.    Limitations to Full Automation      35
                 2.5.5.    Two Basic Automation Scenarios      35
       2.6.    Instrumentation     36
                 2.6.1.    Liquid Handling Stations     36
                 2.6.2.    Plate-Setup Robotics     38
                 2.6.3.    Sealing      41
                 2.6.4.    Visualization      41
                 2.6.5.    Plate Handling and Storage      42
                 2.6.6.    Fully Integrated Systems      45
                 2.6.7.    Cryoprotection      45
                 2.6.8.    Robotic Sample Mounting      46
       2.7.    Conclusions     49
3.    Automated Liquid Handling Systems for Submicroliter Crystallization     57
Terese Bergfors
       3.1.    Introduction     59
                 3.1.1.    The Development Path of Crystallization Robotics      59
                 3.1.2.    The Shift Towards Nanoliter Crystallization      60
                 3.1.3.    Advantages of Crystallization on the Nanoliter Level      61
                 3.1.4.    Future Robot Technology for Crystallization      62 
       3.2.    Choosing a Robot     63
                 3.2.1.    Background of This Chapter     63
                 3.2.2.    What are the Automation Requirements?     63
                 3.2.3.    Multiuser or Service Laboratory?     63
                 3.2.4.    Reservoir Filling and Cocktail Production     64
                 3.2.5.    Types of Dispensing     65
                 3.2.6.    Accuracy and Precision     67
                 3.2.7.    Speed and Related Issues of Chilling and Evaporation Control     68
                 3.2.8.    Size     69
                 3.2.9.    Price     70
                 3.2.10.  Product Descriptions      70
       Appendix 3.1. Product Ddescriptions of the Crystallization Robots Listed in Table 3.1     73
4.    Soft-Polymer Microfluidic Applications to Protein Crystallization     87
James M. Berger
       4.1.    Introduction     89
       4.2.    Classic Crystal Growth Methods     91
       4.3.    Microfluidic Platforms for Crystallization     94
       4.4.    Capabilities Unique to Microfluidic Devices     97
       4.5.    Microfluidic Phase-Space Mapping     100
       4.6.    Horizon Methods     100
       4.7.    Conclusion     103
5.    Counter-Diffusion Capillary Crystallization for High-Throughput Applications     111
Juan M. Garcia-Ruiz and Joseph D. Ng
       5.1.    Why Counter-Diffusion Crystallization?     113
       5.2.    Principle of Counter-Diffusion Crystallization     114
       5.3.    Preparation and Setup     115
                 5.3.1.    Single Capillar     116
                 5.3.2.    Multiple Array Configurations     116
       5.4.    Getting the Protein Crystal to the X-ray Beam as Soon as Possible     118
                 5.4.1.    Taking a Walk Down Crystal Lane     120
                 5.4.2.    Mounting and Aligning Crystals in Capillary     121
                 5.4.3.    Preliminary X-Ray Analysis     121
                 5.4.4.    Data Collection and Electron Density Calculation Image Processing     122
       5.5. Important Points      124
6.    Scale-Down Approaches for Measuring Protein-Protein Interactions     127
Joseph C. Fanguy, Charles S. Henry, Steven C. Holman, Joseph J. Valente, and
W. William Wilson
       6.1.    Introduction     129
       6.2.    Scale Down of Static Light Scattering     133
                 6.2.1.    Configuration Description     133
                 6.2.2.    Flow Injection Components     136
                 6.2.3.    Data Acquisition System      137
                 6.2.4.    Samples for Demonstration Purposes      137
                 6.2.5.    Results for Demonstration Proteins      138
       6.3.    Scale Down of Self-Interaction Chromatography     143
                 6.3.1.    Evolution of Self-Interaction Chromatography (SIC)     143
                 6.3.2.    The Synergy of B and SIC     144
       6.4.    B and Solubility     146
       6.5.    Potential for Miniaturization     147
       6.6.    Conclusions     149
7.    Gearing Optimization Techniques Towards High-Throughput     153
Naomi E. Chayen
       7.1.    Introduction     155
       7.2.    Development of Optimization Procedures     156
                 7.2.1.    Crystallization in Gels     157
                 7.2.2.    “Containerless” Crystallization       159
                 7.2.3.    Control of Evaporation Kinetics      160
                 7.2.4.    Optimization by Decoupling Nucleation and Growth      161
                 7.2.5.    Slowing Down Vapor Diffusion with an Oil Barrier      162 
       7.3.    Summary     163
       Appendix 7.1.  Experimental Procedures     166
                 A7.1.1.  Preparation of Gels     166
                 A7.1.2. Control of Evaporation     166
                 A7.1.3. Decoupling of Nucleation and Growth     167
8.    Miniaturization and Automation for High-Throughput Membrane Protein Crystallization
       in Lipidic Mesophases     169
Vadim Cherezov and Martin Caffrey
        8.1.    Introduction     171
        8.2.    The In-Meso Crystallogenesis Robot Suite     174
                  8.2.1.    Crystallization Robot     174
                  8.2.2.    Screen Solution Preparation     174
                  8.2.3.    Crystallization Plates     175
                  8.2.4.    Imaging Station     176
        8.3.    Crystallization Trials     176
                  8.3.1.    In-Meso Crystallization     176
                  8.3.2.    Screening     177
        8.4.    Robot-Performance Characterization     178
        8.5.    Crystallization Plates     179
        8.6.    Crystallization Robot     181
                  8.6.1.    Dispensing the Lipidic Cubic Phase     181
                  8.6.2.    Dispensing the Precipitant Solution     184
                  8.6.3.    Dehydration during Setup     185
        8.7.    Imaging Station     187
                  8.7.1.    Performance Characteristics     187
                  8.7.2.    Image Processing     188
        8.8.    Crystallization Trials      189
        8.9.    Quo Vadis?      189
        8.10.  Conclusions      192
9.    Automated Classification of Crystallization Experiment     359
Julie Wilson
       9.1.    The Need for Automated Classification     197
       9.2.    Edge Detection     198
       9.3.    Image Cropping     203
       9.4.    Artifacts not Related to the Crystallization Experiment     203
                 9.4.1.    Bubbles and Droplets     204
                 9.4.2.    Plastic Mold Effects     204
       9.5.    Masking the Drop     205
                 9.5.1.    Circular Masks     205
                 9.5.2.    Noncircular Masks     20
       9.6.    Analysis of the Crystallization Drop     208
                 9.6.1.    Feature Extraction     209
                 9.6.2.    Object-Based Features     209
                 9.6.3.   Drop-Based Features     212
       9.7.    Classification     214
                 9.7.1.    Learning Algorithms     214
                 9.7.2.    Decision Trees     215
                 9.7.3.    Linear Discriminant Analysis     216
       9.8.    Summary     217
Index     221

Abstract

Getting from gene to structure involves many steps: cloning expression, solubilization, purification, crystallization, and only then, the determination of the structure. Once protein is pure and soluble, the key to crystallography is the availability of high-quality crystals. Producing high-quality crystals has always been the bottleneck to structure determination and with the advent of proteomics this problem is becoming increasingly acute. As a result, crystallization is gathering a new momentum as evidenced by the increasing numbers of commercial companies selling crystallization kits and tools, the increased investment of pharmaceutical companies in crystallization equipment and expertise, a high demand for practical courses in crystal growth, and the launch by the International Union of crystallography of a new Journal, Acta Crystallographica F, formed in 2005 for publishing the recent explosion of data concerning crystallization.

The past five years have seen some of the greatest achievements in the field of protein crystallization. It is now feasible to screen thousands of potential crystallization conditions by dispensing trials consisting of nanoliter volumes in a high-throughput mode. This has cut the time of setting up experiments from weeks to minutes, a scenario that was unimaginable a few years ago. Even more incredible, is the revelation that diffracting crystals can be produced from protein samples in volumes as small as 5–20 nanoliter. The subsequent phase of image capture and analysis of the crystallization drops is also progressing in great strides.

Surprisingly, in spite of the impressive advances accomplished, the crystallization problem has not been solved. High throughput has not yet resulted in high output and the current challenge is to design new and improved techniques (of screening and optimization) for the production of useful crystals. Scientists worldwide have taken on the challenge by tackling the crystallization problem from a variety of different aspects.

Research advances in recent years have opened up the scope for the development of new methods and tools to overcome the bottleneck of protein crystallization. A variety of parameters that could previously not be explored are now accessible thanks to sophisticated apparatus and the development of new science-based techniques to monitor and control the process of crystallization. However, in order to become useful to the structural genomics effort, it is vital to miniaturize and automate these techniques and adapt them to cope with the vast numbers of “leads” resulting from the high-throughput screening procedures. Such efforts are those of the immediate future and the focus of this book.