James Pulokas

Fully automated, sequential tilt-series acquisition with Leginon

Electron tomography has become a uniquely powerful tool for investigating the structures of individual cells, viruses, and macromolecules. Data collection is, however, time consuming and requires expensive instruments. To optimize productivity, we have incorporated one of the existing tilt-series acquisition programs, UCSF Tomo, into the well-developed automatic electron microscopy data collection package Leginon to enable fully automatic, sequential tilt-series acquisition. Here we describe how UCSF Tomo was integrated into Leginon, what users must do to set up a data collection session, how the automatic collection proceeds, how archived data about the process can be accessed and used, and how the software has been tested.

Leginon: a system for fully automated acquisition of 1000 electron micrographs a day.

We have developed a system to automatically acquire large numbers of acceptable quality images from specimens of negatively stained catalase, a biological protein which forms crystals. In this paper we will describe the details of the system architecture and analyze the performance of the system as compared to a human operator. The ultimate goal of the system if to automate the process of acquiring cryo-electron micrographs.

Precise beam-tilt alignment and collimation are required to minimize the phase error associated with coma in high-resolution cryo-EM.

Electron microscopy at a resolution of 0.4nm or better requires more careful adjustment of the illumination than is the case at a resolution of 0.8nm. The use of current-axis alignment is not always sufficient, for example, to avoid the introduction of large phase errors, at higher resolution, due to axial coma. In addition, one must also ensure that off-axis coma does not corrupt the data quality at the higher resolution. We particularly emphasize that the standard CTF correction does not account for the phase error associated with coma. We explain the cause of both axial coma and the typically most troublesome component of off-axis coma in terms of the well-known shift of the electron diffraction pattern relative to the optical axis that occurs when the illumination is not parallel to the axis. We review the experimental conditions under which coma causes unacceptably large phase errors, and we discuss steps that can be taken when setting up the conditions of illumination, so as to ensure that neither axial nor off-axis coma is a problem.

Automated electron microscopy for evaluating two-dimensional crystallization of membrane proteins.

Membrane proteins fulfill many important roles in the cell and represent the target for a large number of therapeutic drugs. Although structure determination of membrane proteins has become a major priority, it has proven to be technically challenging. Electron microscopy of two-dimensional (2D) crystals has the advantage of visualizing membrane proteins in their natural lipidic environment, but has been underutilized in recent structural genomics efforts. To improve the general applicability of electron crystallography, high-throughput methods are needed for screening large numbers of conditions for 2D crystallization, thereby increasing the chances of obtaining well ordered crystals and thus achieving atomic resolution. Previous reports describe devices for growing 2D crystals on a 96-well format. The current report describes a system for automated imaging of these screens with an electron microscope. Samples are inserted with a two-part robot: a SCARA robot for loading samples into the microscope holder, and a Cartesian robot for placing the holder into the electron microscope. A standard JEOL 1230 electron microscope was used, though a new tip was designed for the holder and a toggle switch controlling the airlock was rewired to allow robot control. A computer program for controlling the robots was integrated with the Leginon program, which provides a module for automated imaging of individual samples. The resulting images are uploaded into the Sesame laboratory information management system database where they are associated with other data relevant to the crystallization screen.

A relational database for cryoEM: experience at one year and 50 000 images.

For the past year we have been using a relational database as part of an automated data collection system for cryoEM. The database is vital for keeping track of the very large number of images collected and analyzed by the automated system and essential for quantitatively evaluating the utility of methods and algorithms used in the data collection. The database can be accessed using a variety of tools including specially developed Web-based interfaces that enable a user to annotate and categorize images using a Web-based form.

Rapid routine structure determination of macromolecular assemblies using electron microscopy: current progress and further challenges.

Although the methodology of molecular microscopy has enormous potential, it is time consuming and labor intensive. The techniques required to produce a three-dimensional (3D) electron density map of a macromolecular structure normally require manual operation of an electron microscope by a skilled operator and manual supervision of the sometimes complex software needed for analysis and calculation of 3D maps. Systems to automate the process of data acquisition from an electron microscope are being developing and these systems are being integrated with specimen handling operations and post acquisition data processing. Here, the current performance of our existing systems and the future challenges involved in substantially improving both the sustained throughput and the yield of automated data collection and analysis are reported.

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.

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.

Getting the Most out of Direct Detection Cameras for Low-Dose Transmission Electron Microscopy

Single-particle cryo electron microscopy (cryoEM) is undergoing a technical revolution due to the recent developments of direct detectors. These new recording devices detect electrons directly (i.e. without conversion into light) and feature significantly improved detective quantum efficiency (DQE) as compared to photographic films or CCDs. Moreover, their enhanced readout rates allow for the collection of data as movies composed of many frames, during the time lapse previously corresponding to a single exposure. This in turn allows for correcting for beam-induced sample movement, a factor that has until now limited the resolution attainable using cryoEM.