Operator-assisted harvesting of protein crystals using a universal micromanipulation robot

Abstract

High-throughput crystallography has reached a level of automation where complete computer-assisted robotic crystallization pipelines are capable of cocktail preparation, crystallization plate setup, and inspection and interpretation of results. While mounting of crystal pins, data collection and structure solution are highly automated, crystal harvesting and cryocooling remain formidable challenges towards full automation. To address the final frontier in achieving fully automated high-throughput crystallography, the prototype of an anthropomorphic six-axis universal micromanipulation robot (UMR) has been designed and tested; this UMR is capable of operator-assisted harvesting and cryoquenching of protein crystals as small as 10 microm from a variety of 96-well plates. The UMR is equipped with a versatile tool exchanger providing full operational flexibility. Trypsin crystals harvested and cryoquenched using the UMR have yielded a 1.5 A structure demonstrating the feasibility of robotic protein crystal harvesting.

Figure 1

The UMR prototype. The core of the system is a Stäubli RX 60 anthropomorphic six-axis robot, equipped with a versatile pneumatically operated tool exchanger, giving the robotic arm access to a wide range of harvesting loops, microtools and liquid exchange capability.

Figure 2

Detailed view of the tool exchanger and tool storage (left panel), and the plate manipulator tool attached to the tool exchanger (right panel).

Figure 3

Tool exchanger with harvesting wand carrying a magnetic base Hampton Research CrystalCap pin with Kapton cryo-loop (left panel). A harvested 30 µm lysozyme crystal dyed with methylene blue in the MiTeGen harvesting loop is shown in the right panel.

Figure 4

Automated cryoquenching of a crystal in liquid nitrogen. The sample magazine used during the tests was a simplified version of the ‘cryo-pucks’ currently in use at a number of synchrotron light sources. Because of the system’s inherent flexibility, the UMR can be configured for compatibility with any type of storage magazine currently in use.

Figure 5

Real-space correlation coefficients against a bias-minimized SNW map (black) and B factors (blue) for the final model of trypsin 2j9n, demonstrating the quality of the trypsin model obtained from the robotically harvested crystals. Inserts shows SNW omit electron density of the benzamidine inhibitor (left) and the phased anomalous difference map of the disulfide bond Cys40—Cys56. Density figures were generated using Xfit (McRee, 1999 ▶) and Raster3 d (Merritt & Bacon, 1997 ▶).

Figure 6

Packing of trypsin molecules with intercalating peptide. Two symmetry-related molecules are shown in purple and yellow; the peptide linking the three molecules is shown in red. In addition, residues of BPTI (green; PDB code 3btd; Helland et al., 1999 ▶) and a synthetic peptide inhibitor (blue; PDB code 1ox1) are superimposed on the central trypsin (grey), showing that the intercalating density occupies a different location from the peptide substrates. Figure prepared with ICM Pro Version 3.7 (Abagyan et al., 1994 ▶).

Figure 7

Enlarged section of the interface region between three trypsin molecules (same orientation as Fig. 6 ▶). The trace of the peptide (red) shows that it is located so that its positively charged side chains such as arginine and lysine would generally interact with negative patches on the trypsin surface (red) while interactions of the peptide backbone involve basic residues (blue) of the neighboring molecule’s residues. Figure prepared using ICM Pro Version 3.7 (Abagyan et al., 1994 ▶).