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

Abstract

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.

Fig. 1

Overall layout of the robotic grid loading system. The SCARA robot is responsible for loading individual EM grids from a 96-well grid tray into the EM sample holder. The Cartesian robot is responsible for picking up this sample holder and inserting it through the goniometer on the JEOL 1230 electron microscope. Axes of movement for both robots are shown. The EM computer runs Leginon and coordinates sample loading and imaging by communicating with a database server. The Robot computer queries the database and, when requested, initiates movement of the robot to insert or remove the sample.

Fig. 2

Loading EM grids. (A) A SCARA robot has been implemented for handling individual EM grids. (B) The SCARA robot is fitted with a vacuum probe to pick up grids using three nozzles positioned around the rim of the grid. (C) Grids are stored in an anodized aluminium tray with 96 wells laid out with standard SBS dimensions. Grids are transferred to this tray manually after negative staining.

Fig. 3

Modifications to the tip and the handle of the standard EM holder. (A) The holder is shown resting in a custom mount that serves to define its location and orientation relative to the SCARA and Cartesian robots. The original plastic holder was replaced with an aluminum handle, which was milled to be concentric with the rod. The bottom of the handle was also drilled with a hole that engages a pin on the mount (not seen) in order to maintain a defined position with respect to the robots. (B) A new tip with a spring-loaded clamp was designed for use with the SCARA robot. This exploded diagram shows how a spring pushes a piston against the eccentric hinge of the clamp. (C) An L-shaped finger mounted next to the vacuum probe raises the clamp. (D) The vacuum probe deposits the grid into the holder. (E) The L-shaped finger then lowers the clamp.

Fig. 4

A Cartesian robot is used to move the sample holder to the microscope and insert it through the goniometer. This robot provides three orthogonal axes for linear motion and a three-fingered gripper is mounted on a rotation stage. (A) Robot prior to picking up the sample holder. (B) Robot inserting the holder into the microscope goniometer (white arrowhead on the left).

Fig. 5

Elements of computer control connected to an Ethernet network. A Windows XP computer runs the Leginon application as well as DigitalMicrograph and communicates directly with the JEOL 1230 microscope via an RS232 serial interface. A Linux computer runs the iRobot application, which communicates with each robot via a dedicated controller. Both iRobot and Leginon communicate with second Linux computer hosting a MySQL database, which stores all the microscope calibrations and the imaging conditions as well as the images resulting from the screen.

Fig. 6

Strategy for imaging an EM grid with Leginon. As described by Cheng et al. [19], Leginon starts by recording a montage at low magnification covering a large area of the EM grid. For our application, we specified a montage containing 3x3 grid-scale images. The magnification of grid scale imaging was adjusted to include ~20 grid squares at 400 mesh. After recording the montage, Leginon evaluates individual grid squares and selects several for imaging at the square scale. We specified selection of one grid square per grid-scale image for a total of 9 per EM grid. A raster is defined at the square-scale and areas are evaluated for imaging at the hole-scale. Six examples of images at the hole scale are shown, depicting various different outcomes: 2D crystal (A), tubular crystals (B), proteoliposome (C) edge of the grid bar (D), empty grid (E) and broken carbon film (F). Scale bars correspond to 200nm in (A) and 1μm in (B-F).

Fig. 7

Incorporation of images into a Laboratory Information Management System. An image viewer has been added to the Sesame LIMS and images from screens have been imported into its database. This allows for integration of all information relevant to the crystallization screen, e.g., target protein sequence, conditions for expression and purification, crystallization trials, and crystallization score.