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. 2012 Aug;68(Pt 8):975-84.
doi: 10.1107/S090744491201863X. Epub 2012 Jul 17.

The use of workflows in the design and implementation of complex experiments in macromolecular crystallography

Sandor Brockhauser  1 , Olof Svensson, Matthew W Bowler, Max Nanao, Elspeth Gordon, Ricardo M F Leal, Alexander Popov, Matthew Gerring, Andrew A McCarthy, Andy Gotz
Affiliations

The use of workflows in the design and implementation of complex experiments in macromolecular crystallography

Sandor Brockhauser et al. Acta Crystallogr D Biol Crystallogr. 2012 Aug.

Abstract

The automation of beam delivery, sample handling and data analysis, together with increasing photon flux, diminishing focal spot size and the appearance of fast-readout detectors on synchrotron beamlines, have changed the way that many macromolecular crystallography experiments are planned and executed. Screening for the best diffracting crystal, or even the best diffracting part of a selected crystal, has been enabled by the development of microfocus beams, precise goniometers and fast-readout detectors that all require rapid feedback from the initial processing of images in order to be effective. All of these advances require the coupling of data feedback to the experimental control system and depend on immediate online data-analysis results during the experiment. To facilitate this, a Data Analysis WorkBench (DAWB) for the flexible creation of complex automated protocols has been developed. Here, example workflows designed and implemented using DAWB are presented for enhanced multi-step crystal characterizations, experiments involving crystal reorientation with kappa goniometers, crystal-burning experiments for empirically determining the radiation sensitivity of a crystal system and the application of mesh scans to find the best location of a crystal to obtain the highest diffraction quality. Beamline users interact with the prepared workflows through a specific brick within the beamline-control GUI MXCuBE.

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Figures

Figure 1
Figure 1
The GUI for designing workflows, as embedded in DAWB. The Palette View on the left organizes the available actors into groups such as Hardware/EDNA/UI and makes them available to drag and drop onto the main canvas. The workflow shown performs different image-manipulation tasks concurrently and stores the generated results in an hdf5 file which is then opened to visualize the results.
Figure 2
Figure 2
Diagram showing the integration of workflows at the ESRF MX beamlines. Arrows indicate information exchange between software and hardware components.
Figure 3
Figure 3
A workflow for Enhanced Characterization. By coupling subsequent and related steps into composite actors, such as those coloured blue, the higher level logical sequence of the experimental protocol is preserved and clearly presented to non-programmers.
Figure 4
Figure 4
(a) The radiation-sensitivity workflow and (b) its output plot as presented by DAWB for a cubic insulin crystal. Markers show measured values, whilst fitting curves are denoted by solid lines. Overall B factors are represented in blue, relative scales in red and the relative averaged integrated intensities are shown in green. Linear fitting curves are applied to both overall B factors and relative scales, whereas the relative averaged integrated intensities are fitted with an exponential curve. The horizontal axis shows the calculated dose (RADDOSE). The radiation-damage sensitivity coefficient (β = 0.8 Å2 MGy−1) and the slope of the relative scale fitting line (Δ = −0.027 MGy−1) are shown at the bottom of the plot.
Figure 5
Figure 5
Simulation of the crystal orientation effect on achievable minimum noise between Bijvoet mates represented as R Friedel = 〈|〈E 2+〉 − 〈E 2−〉|〉, where 〈E 2+〉 and 〈E 2−〉 are normalized average intensities of Bijvoet mates plotted as a function of resolution. Calculations were performed by the program BEST accounting for radiation-damage effects in the cases of (a) trypsin, space group P3121, and (b) thaumatin, space group P41212.
Figure 6
Figure 6
The kappa-reorientation workflow with example diffraction images captured from the same FAE crystal in different orientations. The blue image on the left is taken at step 1 in the initial random orientation. The blue image on the right is the reference image at step 2 in an aligned orientation to optimize the strategy for a complete data collection in this orientation. The red background image is taken at step 3 as the first image of the final data set.
Figure 7
Figure 7
The ratios of data collections using the MiniKappa are shown as a function of time for scheduled beamtime in 2011 on ESRF public MX beamlines. Note that ID23-2 does not have the MiniKappa mounted routinely and MiniKappa usage on ID29 is not available in the beamline operation database.
Figure 8
Figure 8
The mesh-scan workflow was executed on a precentered trypsin crystal. (a) The on-axis microscope view of the crystal. (b) The result of scanning a ±225 µm region of interest both horizontally and vertically with a 50 µm square beam using 57 µm steps is shown as displayed in DAWB. (c) Overlay of the scan results on the microscope view together with the workflow that was used to perform the experiment.
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