Automatic Acquisition and Image Analysis of 2D Crystals

Sparse and incomplete factorial matrices to screen membrane protein 2D crystallization

Electron crystallography is well suited for studying the structure of membrane proteins in their native lipid bilayer environment. This technique relies on electron cryomicroscopy of two-dimensional (2D) crystals, grown generally by reconstitution of purified membrane proteins into proteoliposomes under conditions favoring the formation of well-ordered lattices. Growing these crystals presents one of the major hurdles in the application of this technique. To identify conditions favoring crystallization a wide range of factors that can lead to a vast matrix of possible reagent combinations must be screened. However, in 2D crystallization these factors have traditionally been surveyed in a relatively limited fashion. To address this problem we carried out a detailed analysis of published 2D crystallization conditions for 12 β-barrel and 138 α-helical membrane proteins. From this analysis we identified the most successful conditions and applied them in the design of new sparse and incomplete factorial matrices to screen membrane protein 2D crystallization. Using these matrices we have run 19 crystallization screens for 16 different membrane proteins totaling over 1300 individual crystallization conditions. Six membrane proteins have yielded diffracting 2D crystals suitable for structure determination, indicating that these new matrices show promise to accelerate the success rate of membrane protein 2D crystallization.

Automated grid handling and image acquisition for two-dimensional crystal screening

Routine large-scale two-dimensional (2D) crystallization trials are good candidates for automation. For imaging the large number of grids prepared from 2D crystallization trials, a two-pass imaging protocol using Leginon and a grid handling robot is described. A manual target selection bridges the two imaging passes. The two passes can be combined into one if objects of interests at different stages of trials can be reliably found using automated methods.

Membrane protein structure determination by electron crystallography

During the past year, electron crystallography of membrane proteins has provided structural insights into the mechanism of several different transporters and into their interactions with lipid molecules within the bilayer. From a technical perspective there have been important advances in high-throughput screening of crystallization trials and in automated imaging of membrane crystals with the electron microscope. There have also been key developments in software, and in molecular replacement and phase extension methods designed to facilitate the process of structure determination.

Automation in single-particle electron microscopy connecting the pieces

Throughout the history of single-particle electron microscopy (EM), automated technologies have seen varying degrees of emphasis and development, usually depending upon the contemporary demands of the field. We are currently faced with increasingly sophisticated devices for specimen preparation, vast increases in the size of collected data sets, comprehensive algorithms for image processing, sophisticated tools for quality assessment, and an influx of interested scientists from outside the field who might lack the skills of experienced microscopists. This situation places automated techniques in high demand. In this chapter, we provide a generic definition of and discuss some of the most important advances in automated approaches to specimen preparation, grid handling, robotic screening, microscope calibrations, data acquisition, image processing, and computational infrastructure. Each section describes the general problem and then provides examples of how that problem has been addressed through automation, highlighting available processing packages, and sometimes describing the particular approach at the National Resource for Automated Molecular Microscopy (NRAMM). We contrast the more familiar manual procedures with automated approaches, emphasizing breakthroughs as well as current limitations. Finally, we speculate on future directions and improvements in automated technologies. Our overall goal is to present automation as more than simply a tool to save time. Rather, we aim to illustrate that automation is a comprehensive and versatile strategy that can deliver biological information on an unprecedented scale beyond the scope available with classical manual approaches.

Present and future of membrane protein structure determination by electron crystallography

Membrane proteins are critical to cell physiology, playing roles in signaling, trafficking, transport, adhesion, and recognition. Despite their relative abundance in the proteome and their prevalence as targets of therapeutic drugs, structural information about membrane proteins is in short supply. This chapter describes the use of electron crystallography as a tool for determining membrane protein structures. Electron crystallography offers distinct advantages relative to the alternatives of X-ray crystallography and NMR spectroscopy. Namely, membrane proteins are placed in their native membranous environment, which is likely to favor a native conformation and allow changes in conformation in response to physiological ligands. Nevertheless, there are significant logistical challenges in finding appropriate conditions for inducing membrane proteins to form two-dimensional arrays within the membrane and in using electron cryo-microscopy to collect the data required for structure determination. A number of developments are described for high-throughput screening of crystallization trials and for automated imaging of crystals with the electron microscope. These tools are critical for exploring the necessary range of factors governing the crystallization process. There have also been recent software developments to facilitate the process of structure determination. However, further innovations in the algorithms used for processing images and electron diffraction are necessary to improve throughput and to make electron crystallography truly viable as a method for determining atomic structures of membrane proteins.