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Title: Dynamic X-ray diffraction sampling for protein crystal positioning

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. Furthermore, by usingin situtwo-photon-excited fluorescence microscopy measurementsmore » 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.« less

Authors:
 [1];  [2]; ORCiD logo [2];  [3];  [1];  [1];  [1];  [1];  [3];  [1];  [4];  [2];  [1]
  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
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
US Air Force Office of Scientific Research (AFOSR); National Institutes of Health (NIH)
OSTI Identifier:
1390796
Grant/Contract Number:  
AC02-06CH11357; R01GM-103910; R01GM-103410
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Synchrotron Radiation (Online)
Additional Journal Information:
Journal Name: Journal of Synchrotron Radiation (Online); Journal Volume: 24; Journal Issue: 1; Journal ID: ISSN 1600-5775
Publisher:
International Union of Crystallography
Country of Publication:
United States
Language:
English
Subject:
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

Citation Formats

Scarborough, Nicole M., Godaliyadda, G. M. Dilshan P., Ye, Dong Hye, Kissick, David J., Zhang, Shijie, Newman, Justin A., Sheedlo, Michael J., Chowdhury, Azhad U., Fischetti, Robert F., Das, Chittaranjan, Buzzard, Gregery T., Bouman, Charles A., and Simpson, Garth J. Dynamic X-ray diffraction sampling for protein crystal positioning. United States: N. p., 2017. Web. doi:10.1107/S160057751601612X.
Scarborough, Nicole M., Godaliyadda, G. M. Dilshan P., Ye, Dong Hye, Kissick, David J., Zhang, Shijie, Newman, Justin A., Sheedlo, Michael J., Chowdhury, Azhad U., Fischetti, Robert F., Das, Chittaranjan, Buzzard, Gregery T., Bouman, Charles A., & Simpson, Garth J. Dynamic X-ray diffraction sampling for protein crystal positioning. United States. doi:10.1107/S160057751601612X.
Scarborough, Nicole M., Godaliyadda, G. M. Dilshan P., Ye, Dong Hye, Kissick, David J., Zhang, Shijie, Newman, Justin A., Sheedlo, Michael J., Chowdhury, Azhad U., Fischetti, Robert F., Das, Chittaranjan, Buzzard, Gregery T., Bouman, Charles A., and Simpson, Garth J. Sun . "Dynamic X-ray diffraction sampling for protein crystal positioning". United States. doi:10.1107/S160057751601612X. https://www.osti.gov/servlets/purl/1390796.
@article{osti_1390796,
title = {Dynamic X-ray diffraction sampling for protein crystal positioning},
author = {Scarborough, Nicole M. and Godaliyadda, G. M. Dilshan P. and Ye, Dong Hye and Kissick, David J. and Zhang, Shijie and Newman, Justin A. and Sheedlo, Michael J. and Chowdhury, Azhad U. and Fischetti, Robert F. and Das, Chittaranjan and Buzzard, Gregery T. and Bouman, Charles A. and Simpson, Garth J.},
abstractNote = {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.},
doi = {10.1107/S160057751601612X},
journal = {Journal of Synchrotron Radiation (Online)},
number = 1,
volume = 24,
place = {United States},
year = {2017},
month = {1}
}

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