Hybrid approach for structural modeling of biological systems from X-ray free electron laser diffraction patterns

2016 ◽  
Vol 194 (3) ◽  
pp. 325-336 ◽  
Author(s):  
Atsushi Tokuhisa ◽  
Slavica Jonic ◽  
Florence Tama ◽  
Osamu Miyashita
IUCrJ ◽  
2021 ◽  
Vol 8 (6) ◽  
Author(s):  
Miklós Tegze ◽  
Gábor Bortel

In single-particle imaging (SPI) experiments, diffraction patterns of identical particles are recorded. The particles are injected into the X-ray free-electron laser (XFEL) beam in random orientations. The crucial step of the data processing of SPI is finding the orientations of the recorded diffraction patterns in reciprocal space and reconstructing the 3D intensity distribution. Here, two orientation methods are compared: the expansion maximization compression (EMC) algorithm and the correlation maximization (CM) algorithm. To investigate the efficiency, reliability and accuracy of the methods at various XFEL pulse fluences, simulated diffraction patterns of biological molecules are used.


Author(s):  
Monarin Uervirojnangkoorn ◽  
Oliver B Zeldin ◽  
Artem Y Lyubimov ◽  
Johan Hattne ◽  
Aaron S Brewster ◽  
...  

2014 ◽  
Vol 21 (3) ◽  
pp. 600-612 ◽  
Author(s):  
Yuki Sekiguchi ◽  
Tomotaka Oroguchi ◽  
Yuki Takayama ◽  
Masayoshi Nakasako

Coherent X-ray diffraction imaging is a promising technique for visualizing the structures of non-crystalline particles with dimensions of micrometers to sub-micrometers. Recently, X-ray free-electron laser sources have enabled efficient experiments in the `diffraction before destruction' scheme. Diffraction experiments have been conducted at SPring-8 Angstrom Compact free-electron LAser (SACLA) using the custom-made diffraction apparatus KOTOBUKI-1 and two multiport CCD detectors. In the experiments, ten thousands of single-shot diffraction patterns can be collected within several hours. Then, diffraction patterns with significant levels of intensity suitable for structural analysis must be found, direct-beam positions in diffraction patterns determined, diffraction patterns from the two CCD detectors merged, and phase-retrieval calculations for structural analyses performed. A software suite namedSITENNOhas been developed to semi-automatically apply the four-step processing to a huge number of diffraction data. Here, details of the algorithm used in the suite are described and the performance for approximately 9000 diffraction patterns collected from cuboid-shaped copper oxide particles reported. Using theSITENNOsuite, it is possible to conduct experiments with data processing immediately after the data collection, and to characterize the size distribution and internal structures of the non-crystalline particles.


2016 ◽  
Vol 23 (4) ◽  
pp. 975-989 ◽  
Author(s):  
Amane Kobayashi ◽  
Yuki Sekiguchi ◽  
Tomotaka Oroguchi ◽  
Koji Okajima ◽  
Asahi Fukuda ◽  
...  

Coherent X-ray diffraction imaging (CXDI) allows internal structures of biological cells and cellular organelles to be analyzed. CXDI experiments have been conducted at 66 K for frozen-hydrated biological specimens at the SPring-8 Angstrom Compact Free-Electron Laser facility (SACLA). In these cryogenic CXDI experiments using X-ray free-electron laser (XFEL) pulses, specimen particles dispersed on thin membranes of specimen disks are transferred into the vacuum chamber of a diffraction apparatus. Because focused single XFEL pulses destroy specimen particles at the atomic level, diffraction patterns are collected through raster scanning the specimen disks to provide fresh specimen particles in the irradiation area. The efficiency of diffraction data collection in cryogenic experiments depends on the quality of the prepared specimens. Here, detailed procedures for preparing frozen-hydrated biological specimens, particularly thin membranes and devices developed in our laboratory, are reported. In addition, the quality of the frozen-hydrated specimens are evaluated by analyzing the characteristics of the collected diffraction patterns. Based on the experimental results, the internal structures of the frozen-hydrated specimens and the future development for efficient diffraction data collection are discussed.


2014 ◽  
Vol 30 (S1) ◽  
pp. S25-S30 ◽  
Author(s):  
Kenneth R. Beyerlein ◽  
Christian Jooss ◽  
Anton Barty ◽  
Richard Bean ◽  
Sébastien Boutet ◽  
...  

We report on the analysis of virtual powder-diffraction patterns from serial femtosecond crystallography (SFX) data collected at an X-ray free-electron laser. Different approaches to binning and normalizing these patterns are discussed with respect to the microstructural characteristics which each highlights. Analysis of SFX data from a powder of Pr0.5Ca0.5MnO3 in this way finds evidence of other trace phases in its microstructure which was not detectable in a standard powder-diffraction measurement. Furthermore, a comparison between two virtual powder pattern integration strategies is shown to yield different diffraction peak broadening, indicating sensitivity to different types of microstrain. This paper is a first step in developing new data analysis methods for microstructure characterization from serial crystallography data.


2014 ◽  
Vol 369 (1647) ◽  
pp. 20130498 ◽  
Author(s):  
Rick P. Millane ◽  
Joe P. J. Chen

X-ray free-electron laser diffraction patterns from protein nanocrystals provide information on the diffracted amplitudes between the Bragg reflections, offering the possibility of direct phase retrieval without the use of ancillary experimental data. Proposals for implementing direct phase retrieval are reviewed. These approaches are limited by the signal-to-noise levels in the data and the presence of different and incomplete unit cells in the nanocrystals. The effects of low signal to noise can be ameliorated by appropriate selection of the intensity data samples that are used. The effects of incomplete unit cells may be small in some cases, and a unique solution is likely if there are four or fewer molecular orientations in the unit cell.


Nano Letters ◽  
2021 ◽  
Author(s):  
Sungwon Kim ◽  
Youngsam Kim ◽  
Jaeseung Kim ◽  
Sungwook Choi ◽  
Kyuseok Yun ◽  
...  

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