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Title: Beyond integration: modeling every pixel to obtain better structure factors from stills

Abstract

Most crystallographic data processing methods use pixel integration. In serial femtosecond crystallography (SFX), the intricate interaction between the reciprocal lattice point and the Ewald sphere is integrated out by averaging symmetrically equivalent observations recorded across a large number (104-106) of exposures. Although sufficient for generating biological insights, this approach converges slowly, and using it to accurately measure anomalous differences has proved difficult. This report presents a novel approach for increasing the accuracy of structure factors obtained from SFX data. A physical model describing all observed pixels is defined to a degree of complexity such that it can decouple the various contributions to the pixel intensities. Model dependencies include lattice orientation, unit-cell dimensions, mosaic structure, incident photon spectra and structure factor amplitudes. Maximum likelihood estimation is used to optimize all model parameters. The application of prior knowledge that structure factor amplitudes are positive quantities is included in the form of a reparameterization. The method is tested using a synthesized SFX dataset of ytterbium(III) lysozyme, where each X-ray laser pulse energy is centered at 9034 eV. This energy is 100 eV above the Yb3+L-III absorption edge, so the anomalous difference signal is stable at 10 electrons despite the inherent energy jitter ofmore » each femtosecond X-ray laser pulse. This work demonstrates that this approach allows the determination of anomalous structure factors with very high accuracy while requiring an order-of-magnitude fewer shots than conventional integration-based methods would require to achieve similar results.« less

Authors:
 [1];  [1];  [1];  [1]; ORCiD logo [1]; ORCiD logo [1];  [2];  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Synchrotron Radiation Lightsource (SSRL); Univ. of California, San Francisco, CA (United States)
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES). Chemical Sciences, Geosciences & Biosciences Division; National Institutes of Health (NIH); USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1764541
Alternate Identifier(s):
OSTI ID: 1779684
Grant/Contract Number:  
AC02-05CH11231; GM117126; AC02-76SF00515; GM124149; GM124169; GM103393; AI150476; GM110501; GM126289; 17-SC-20-SC
Resource Type:
Accepted Manuscript
Journal Name:
IUCrJ
Additional Journal Information:
Journal Volume: 7; Journal Issue: 6; Journal ID: ISSN 2052-2525
Publisher:
International Union of Crystallography
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; serial crystallography; free-electron lasers; SFX; stills; data processing

Citation Formats

Mendez, Derek, Bolotovsky, Robert, Bhowmick, Asmit, Brewster, Aaron S., Kern, Jan, Yano, Junko, Holton, James M., and Sauter, Nicholas K. Beyond integration: modeling every pixel to obtain better structure factors from stills. United States: N. p., 2020. Web. doi:10.1107/s2052252520013007.
Mendez, Derek, Bolotovsky, Robert, Bhowmick, Asmit, Brewster, Aaron S., Kern, Jan, Yano, Junko, Holton, James M., & Sauter, Nicholas K. Beyond integration: modeling every pixel to obtain better structure factors from stills. United States. https://doi.org/10.1107/s2052252520013007
Mendez, Derek, Bolotovsky, Robert, Bhowmick, Asmit, Brewster, Aaron S., Kern, Jan, Yano, Junko, Holton, James M., and Sauter, Nicholas K. Sat . "Beyond integration: modeling every pixel to obtain better structure factors from stills". United States. https://doi.org/10.1107/s2052252520013007. https://www.osti.gov/servlets/purl/1764541.
@article{osti_1764541,
title = {Beyond integration: modeling every pixel to obtain better structure factors from stills},
author = {Mendez, Derek and Bolotovsky, Robert and Bhowmick, Asmit and Brewster, Aaron S. and Kern, Jan and Yano, Junko and Holton, James M. and Sauter, Nicholas K.},
abstractNote = {Most crystallographic data processing methods use pixel integration. In serial femtosecond crystallography (SFX), the intricate interaction between the reciprocal lattice point and the Ewald sphere is integrated out by averaging symmetrically equivalent observations recorded across a large number (104-106) of exposures. Although sufficient for generating biological insights, this approach converges slowly, and using it to accurately measure anomalous differences has proved difficult. This report presents a novel approach for increasing the accuracy of structure factors obtained from SFX data. A physical model describing all observed pixels is defined to a degree of complexity such that it can decouple the various contributions to the pixel intensities. Model dependencies include lattice orientation, unit-cell dimensions, mosaic structure, incident photon spectra and structure factor amplitudes. Maximum likelihood estimation is used to optimize all model parameters. The application of prior knowledge that structure factor amplitudes are positive quantities is included in the form of a reparameterization. The method is tested using a synthesized SFX dataset of ytterbium(III) lysozyme, where each X-ray laser pulse energy is centered at 9034 eV. This energy is 100 eV above the Yb3+L-III absorption edge, so the anomalous difference signal is stable at 10 electrons despite the inherent energy jitter of each femtosecond X-ray laser pulse. This work demonstrates that this approach allows the determination of anomalous structure factors with very high accuracy while requiring an order-of-magnitude fewer shots than conventional integration-based methods would require to achieve similar results.},
doi = {10.1107/s2052252520013007},
journal = {IUCrJ},
number = 6,
volume = 7,
place = {United States},
year = {Sat Oct 24 00:00:00 EDT 2020},
month = {Sat Oct 24 00:00:00 EDT 2020}
}

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