Dynamic X-ray diffraction sampling for protein crystal positioning

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

Research output: Contribution to journalArticlepeer-review

Abstract

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. Using in situ two-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.

Original languageEnglish (US)
Pages (from-to)188-195
Number of pages8
JournalJournal of Synchrotron Radiation
Volume24
Issue number1
DOIs
StatePublished - Jan 1 2017
Externally publishedYes

Bibliographical note

Funding Information:
NMS, SZ, JAN, AUC, MJS, CD and GJS gratefully acknowledge support from the NIH grant Nos. R01GM-103910 and R01GM-103410. DG, DHY and CB gratefully acknowledge support from AFOSR/MURI grant No. FA9550-12-1-0458 and AFRL/RX Contract Number FA8650-10-D-5201-0038. GM/CA@APS has been funded in whole or in part with Federal funds from the National Cancer Institute (ACB- 12002) and the National Institute of General Medical Sciences (AGM-12006). This research used resources of the Advanced Photon Source, a US Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DEAC02-06CH11357.

Publisher Copyright:
© 2017 International Union of Crystallography.

Keywords

  • dynamic sampling
  • nonlinear optical microscopy
  • second-harmonic generation
  • supervised learning approach
  • two-photon-excited fluorescence
  • X-ray diffraction

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