New tool gives protein crystallographers a head start

A new method developed by Professor Elspeth Garman and colleagues looks set to improve the ability of scientists to determine the structure of proteins using X-ray crystallography.

From ‘www.raddo.se’, where researchers can calculate the X-ray dose absorbed by a crystal (developed by the Garman group). The transparent cube represents the crystal which has been rotated by 90­<sup>0</sup> in an X-ray beam. The dose isosurfaces are shown, with the centre of the crystal suffering the highest (red) dose in the Gaussian profile beam

From ‘www.raddo.se’, where researchers can calculate the X-ray dose absorbed by a crystal (developed by the Garman group). The transparent cube represents the crystal which has been rotated by 90° in an X-ray beam. The dose isosurfaces are shown, with the centre of the crystal suffering the highest (red) dose in the Gaussian profile beam

Details of the work, carried out by Professor Garman and her group and colleagues in Grenoble and the States, are published in PNAS (1).

The method allows the prediction of the X-ray lifetime of protein crystals and helps the user determine the best strategies for data collection – particularly useful for membrane proteins which are notoriously difficult to work with. Application of the new approach should lead to better data for the solution of structures of difficult proteins.

Researchers using X-ray crystallography to understand protein structure are continuously faced with the problem of crystal decay. Bombarding a crystal with X-radiation leads to its degradation, resulting in deterioration of the diffraction signal.

‘When you have a crystal in a beam and rotate it for sampling,’ explains Professor Garman, ‘the middle of the crystal gets fried by the beam but the outside won’t. Ideally, you want to spread the beam more evenly over the crystal and get better data less affected by radiation damage.’

Predicting how the crystal will fare in the beam before it is actually exposed is very difficult. Software used by researchers can tell them the maximum dose in the middle but there is no metric to calculate the gradation of dose across the region in which the crystal is exposed. So it can be a challenge to work out the best way to collect good quality data.

Professor Garman, her former DPhil student Dr Oliver Zeldin, and Markus Gerstel, another graduate student in her group, recently developed the RADDOSE-3D programme to address this problem (2). The programme incorporates a metric that allows researchers to model the dose absorbed by crystals rotating in a beam of any profile. By reading in the experimental conditions they can generate dose maps for their crystals in a particular beam.

With the metric in hand, Professor Garman and colleagues set about establishing whether it would stand up to experimental scrutiny. They did this by modelling the dose maps for a single crystal exposed to different beam sizes.

Part II undergraduate student John Bremridge carried out the painstaking task of trying to produce insulin crystals of a simple cubic shape that could be modelled accurately by RADDOSE-3D. These were chosen because it was important to be able to make reliable measurements of crystal size. By optimising crystallisation conditions, he was able to pick ones that were suitable for the experiments.

The group collaborated with Dr Sandor Brockhauser at the ESRF in Grenoble where beams of different sizes are available. They found that the metric vastly improved the reliability to predict the damage progression – an indicator of dose – irrespective of beam conditions.

‘Our metric allows us to normalise out the reported difference in doses because of different beam conditions,’ Professor Garman explains. ‘So it doesn’t matter what the beam conditions are, you can still predict what’s going to happen. People across different labs and synchrotrons and using different proteins can now cross compare.’

Dose map for the experimental validation of the approach in which the crystal is offset in the beam (front) compared with the alignment approach (rear). Doses are represented as follows: low dose (light blue), medium dose (dark blue) and high dose (red) Description

Dose map for the experimental validation of the approach in which the crystal is offset in the beam (front) compared with the alignment approach (rear). Doses are represented as follows: low dose (light blue), medium dose (dark blue) and high dose (red) (Click to enlarge)

The group’s next step was to use this metric to test whether a data collection strategy which should theoretically give better data by spreading the dose more evenly over the crystal, actually does. They compared this approach - in which the centre of the crystal is displaced a little from the centre of the beam - with the commonly used approach of aligning the centre of the crystal and rotating it in the centre of beam.

The metric was used to model the diffraction quality of the two different strategies and compare them. Offsetting the crystal in the beam, which creates a donut-shaped volume of collection, offered 30% better quality data. The group went on to experimentally reproduce this improvement.

Professor Garman says that the new metric the group has developed will be useful for tackling challenging proteins. ‘If people have a difficult problem, they can model it in our software before doing the experiment. They can determine the best way to take the data by reading in the experimental beam profiles. So this is a reliable predictor on any beamline if you know the shape of the beam and the size of the crystal.’

Difficult cases are those where the crystal dies very quickly in the beam – largely membrane proteins. ‘By finding a way of summarising the dose state of the crystal in a way that gives us the same result whatever the beam conditions, we should be able to generate better data for the solution of difficult biological problems,’  says Professor Garman.

Researchers will now be able to work out how much time they have for an experiment based on the dose and can divide this time up to ensure that the data remain good. ‘It gives you a strategy for not collecting data that are poor and biologically compromised,’ adds Professor Garman.

As for distribution and application, she says that the plan is to get the software into the pipeline in a number of synchrotron locations. She is visiting Hamburg, and is liaising with scientists at Diamond and at the Lawrence Berkeley National Laboratory to get the software out. The more beamline pipelines it can be added to, the better - giving researchers the opportunity to optimise data collection before exposing their precious samples to the X-rays.

References

  1. Predicting the X-ray lifetime of protein crystals. Zeldin, O.B., Brockhauser, S., Bremridge, J., Holton, J.M. and Garman, E.F. On-line 2/12/13: http://www.pnas.org/content/early/2013/11/27/1315879110
  2. RADDOSE-3D: Time- and space-resolved modelling of dose in macromolecular crystallography. Zeldin, O.B., Gerstel, M. and Garman, E.F. (2013). J. Appl. Cryst. 46, 1225–1230 http://www.raddo.se/

 

 

 

 

 





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