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

Authors :
Derek Mendez
Robert Bolotovsky
Asmit Bhowmick
Aaron S. Brewster
Jan Kern
Junko Yano
James M. Holton
Nicholas K. Sauter
Source :
IUCrJ, Vol 7, Iss 6, Pp 1151-1167 (2020)
Publication Year :
2020
Publisher :
International Union of Crystallography, 2020.

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 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.

Details

Language :
English
ISSN :
20522525
Volume :
7
Issue :
6
Database :
Directory of Open Access Journals
Journal :
IUCrJ
Publication Type :
Academic Journal
Accession number :
edsdoj.8ca363cf9c214ab7baf4380db63e291c
Document Type :
article
Full Text :
https://doi.org/10.1107/S2052252520013007