Tables for
Volume F
Crystallography of biological macromolecules
Edited by M. G. Rossmann and E. Arnold

International Tables for Crystallography (2006). Vol. F, ch. 8.2, pp. 168-170   | 1 | 2 |

Section 8.2.3. Practical considerations in the Laue technique

K. Moffata*

aDepartment of Biochemistry and Molecular Biology, The Center for Advanced Radiation Sources, and The Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA
Correspondence e-mail:

8.2.3. Practical considerations in the Laue technique

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The experimental aspects of a Laue experiment – the source and optics, the shutters and other beamline components, detectors, analysis software, and the successful design of the Laue experiments themselves – have been presented by Helliwell et al. (1989)[link], Ren & Moffat (1994,[link] 1995a[link],b[link]), Bourgeois et al. (1996)[link], Ren et al. (1996)[link], Clifton et al. (1997)[link], Moffat (1997)[link], Yang et al. (1998)[link], and Ren et al. (1999)[link]. Certain key parameters are under the experimenter's control, such as the nature of the source (bending magnet, wiggler or undulator), the wavelength range incident on the crystal (as modified by components of the beamline such as a mirror and attenuators), the choice of detector (active area, number of pixels and the size of each, dependence of detector parameters on wavelength, inherent background, and the accuracy and speed of readout), the experimental data-collection strategy (exposure time or times, number of angular settings of the crystal to be employed and the angular interval between them) and the data-reduction strategy (properties of the algorithms employed and of the software analysis package). A successful Laue experiment demands consideration of these parameters jointly and in advance, as described in these references. The goal is accurate structure amplitudes, not just speedily obtained, beautiful diffraction images.

For example, an undulator source yields a spectrum in which the incident intensity varies sharply with wavelength. Such a source should only be employed if the software can model this variation suitably in the derivation of the wavelength normalization curve. This is indeed so (at least for the LaueView software package) even in the most extreme case, that of the so-called single-line undulator source in which [\lambda_{\max}] and [\lambda_{\min}] may differ by only 10%, say by 0.1 Å at 1.0 Å (V. Šrajer et al. and D. Bourgeois et al., in preparation).

As a second example, a Laue diffraction pattern is particularly sensitive to crystal disorder, which leads to substantial `streaking' of the Laue spots that is predominantly radial in direction in each diffraction image and may be dependent both on direction in reciprocal space (anisotropic disorder) and on time (if, in a time-resolved experiment, disorder is induced by the process of reaction initiation or by structural evolution as the reaction proceeds). The software therefore has to be able to model accurately elongated closely spaced or partially overlapping spots, whose profile varies markedly with position on each detector image and with time (Ren & Moffat, 1995a[link]). If the software has difficulty with this task, then either a more ordered crystal must be selected, thus diminishing the size of each spot and the extent of spatial overlaps, or a narrower wavelength range must be used, thus reducing the total number of spots per image and their average spatial density (Cruickshank et al., 1991[link]); or the crystal-to-detector distance must be increased, thus increasing the average spot-to-spot distance and potentially increasing the signal-to-noise ratio. There are, however, trade-offs. More ordered crystals may not be readily available, a narrower wavelength range means that more images are required for a complete data set and the detector must continue to intercept all of the high-angle diffraction data (which consist largely of single spots stimulated by longer wavelengths).

As a third example, consider radiation damage. This can be purely thermal, arising from heating due to X-ray absorption. The rate of temperature rise may easily reach several hundred kelvin per second from a focused pink bending-magnet beam at second-generation sources such as the National Synchrotron Light Source (NSLS) (Chen, 1994[link]; Moffat, 1997[link]) or several thousand kelvin per second from a focused wiggler source at third-generation sources such as the ESRF. Fast shutters are required to provide an individual exposure of one millisecond or less in the latter case, and hence to limit the temperature rise to a readily survivable value of several kelvin (Bourgeois et al., 1996[link]; Moffat, 1997[link]). Primary radiation damage (arising directly from X-ray absorption and hence from energy deposition) cannot be eliminated, but it may be modified by selection of the wavelength range and by lowering [\lambda_{\max}]. Secondary radiation damage, arising from the chemical and structural damage generated by highly reactive, rapidly diffusing free radicals, hydrated electrons and other chemical species, can be greatly minimized by the use of very short exposures which allow little time for damaging reactions to occur, and by working at cryogenic temperatures where diffusion is greatly reduced (see e.g. Garman & Schneider, 1997[link]). However, the last strategy may not be an option in a time-resolved Laue experiment, where the desired structural transitions may be literally frozen out at cryogenic temperatures.

Extraction of structure amplitudes from a Laue image or data set proceeds through five stages, reviewed in detail by Clifton et al. (1997)[link] and Ren et al. (1999)[link], and outlined in Fig.[link] First comes the purely geometrical process of indexing, in which each spot is associated with the appropriate hkl value and the unit-cell parameters, crystal orientation matrix, [\lambda_{\min}], geometric parameters of the detector and X-ray camera, [\lambda_{\max}] and [d^{*}_{\max}] are refined, also yielding λ, the wavelength stimulating that spot. In the second stage, each spot is integrated using appropriate profile-fitting algorithms. Thirdly, the wavelength normalization curve is derived, usually by comparison of the recorded intensities of the same (single) spots or symmetry-related spots at several crystal orientations, applied to each image, and the images in each data set scaled together. In the fourth stage, the intensities of spots identified in the first stage as multiple are resolved (or deconvoluted) into the intensity of each individual component or harmonic. The total intensity of a multiple Laue spot is the weighted sum of the intensities of each component, and the weights are known from the wavelength assigned to each component (Stage 1) and the wavelength normalization curve (Stage 3). In the fifth stage, the single and multiple data are merged and reduced to structure amplitudes. Ren et al. (1999)[link] have emphasized that, in contrast to the simplified description presented in Section 8.2.2[link], the effective wavelength range [\lambda_{\max} - \lambda_{\min}] depends on resolution, and each Laue spot is stimulated by a range of wavelengths which can be quite large at low resolution. Although typical Laue software packages such as the Daresbury Laue Software Suite (Helliwell et al., 1989[link]; Campbell, 1995[link]), LEAP (Wakatsuki, 1993)[link] and LaueView (Ren & Moffat, 1995a[link],b[link]) are largely automated, a surprising degree of manual intervention may still be required in the first (indexing) stage, and in later stages where the order of parameter refinement and various rejection criteria may be adjusted by the user. The overall result is that carefully conducted Laue experiments yield structure amplitudes that equal those from monochromatic data in quality (Ren et al., 1999[link]).


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Flow chart of typical Laue data processing.


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Cruickshank, D. W. J., Helliwell, J. R. & Moffat, K. (1991). Angular distribution of reflections in Laue diffraction. Acta Cryst. A47, 352–373.
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Ren, Z., Bourgeois, D., Helliwell, J. R., Moffat, K., Šrajer, V. & Stoddard, B. L. (1999). Laue crystallography: coming of age. J. Synchrotron Rad. 6, 891–917.
Ren, Z. & Moffat, K. (1994). Laue crystallography for studying rapid reactions. J. Synchrotron Rad. 1, 78–82.
Ren, Z. & Moffat, K. (1995a). Quantitative analysis of synchrotron Laue diffraction patterns in macromolecular crystallography. J. Appl. Cryst. 28, 461–481.
Ren, Z. & Moffat, K. (1995b). Deconvolution of energy overlaps in Laue diffraction. J. Appl. Cryst. 28, 482–493.
Ren, Z., Ng, K., Borgstahl, G. E. O., Getzoff, E. D. & Moffat, K. (1996). Quantitative analysis of time-resolved Laue diffraction patterns. J. Appl. Cryst. 29, 246–260.
Wakatsuki, S. (1993). In Data collection and processing, edited by L. Sawyer, N. W. Isaacs & S. Bailey, pp. 71–79. DL/Sci/R34. Warrington: Daresbury Laboratory.
Yang, X., Ren, Z. & Moffat, K. (1998). Structure refinement against synchrotron Laue data: strategies for data collection and reduction. Acta Cryst. D54, 367–377.

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