Dynamic X-ray diffraction sampling for protein crystal positioning

Journal Article · Sun Jan 01 00:00:00 EST 2017 · Journal of Synchrotron Radiation (Online)

DOI:https://doi.org/10.1107/S160057751601612X· OSTI ID:1390796

Scarborough, Nicole M. ^[1]; Godaliyadda, G. M. Dilshan P. ^[2]; Ye, Dong Hye  ^[2]; Kissick, David J. ^[3]; Zhang, Shijie ^[1]; Newman, Justin A. ^[1]; Sheedlo, Michael J. ^[1]; Chowdhury, Azhad U. ^[1]; Fischetti, Robert F. ^[3]; Das, Chittaranjan ^[1]; Buzzard, Gregery T. ^[4]; Bouman, Charles A. ^[2]; Simpson, Garth J. ^[1]

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1. Purdue Univ., West Lafayette, IN (United States). Dept. of Chemistry
2. Purdue Univ., West Lafayette, IN (United States). Dept. of Electrical and Computer Engineering
3. Argonne National Lab. (ANL), Argonne, IL (United States). X-ray Science Division
4. Purdue Univ., West Lafayette, IN (United States). Dept. of Mathematics

A sparse supervised learning approach for dynamic sampling (SLADS) is described for dose reduction in diffraction-based protein crystal positioning. Crystal centering is typically a prerequisite for macromolecular diffraction at synchrotron facilities, with X-ray diffraction mapping growing in popularity as a mechanism for localization. In X-ray raster scanning, diffraction is used to identify the crystal positions based on the detection of Bragg-like peaks in the scattering patterns; however, this additional X-ray exposure may result in detectable damage to the crystal prior to data collection. Dynamic sampling, in which preceding measurements inform the next most information-rich location to probe for image reconstruction, significantly reduced the X-ray dose experienced by protein crystals during positioning by diffraction raster scanning. The SLADS algorithm implemented herein is designed for single-pixel measurements and can select a new location to measure. In each step of SLADS, the algorithm selects the pixel, which, when measured, maximizes the expected reduction in distortion given previous measurements. Ground-truth diffraction data were obtained for a 5 µm-diameter beam and SLADS reconstructed the image sampling 31% of the total volume and only 9% of the interior of the crystal greatly reducing the X-ray dosage on the crystal. Furthermore, by usingin situtwo-photon-excited fluorescence microscopy measurements as a surrogate for diffraction imaging with a 1 µm-diameter beam, the SLADS algorithm enabled image reconstruction from a 7% sampling of the total volume and 12% sampling of the interior of the crystal. When implemented into the beamline at Argonne National Laboratory, without ground-truth images, an acceptable reconstruction was obtained with 3% of the image sampled and approximately 5% of the crystal. The incorporation of SLADS into X-ray diffraction acquisitions has the potential to significantly minimize the impact of X-ray exposure on the crystal by limiting the dose and area exposed for image reconstruction and crystal positioning using data collection hardware present in most macromolecular crystallography end-stations.

• Research Organization: Argonne National Lab. (ANL), Argonne, IL (United States)
• Sponsoring Organization: US Air Force Office of Scientific Research (AFOSR); National Institutes of Health (NIH)
• Grant/Contract Number: AC02-06CH11357; R01GM-103910; R01GM-103410
• OSTI ID: 1390796
• Journal Information: Journal of Synchrotron Radiation (Online), Vol. 24, Issue 1; ISSN 1600-5775
• Publisher: International Union of Crystallography
• Country of Publication: United States
• Language: English

Related Subjects

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
X-ray diffraction
dynamic sampling
nonlinear optical microscopy
second-harmonic generation
supervised learning approach
two-photon-excited fluorescence