Status of the neutron time-of-flight single-crystal diffraction data-processing software <i>STARGazer</i>

Yano, Naomine; Yamada, Taro; Hosoya, Takamitsu; Ohhara, Takashi; Tanaka, Ichiro; Nakabayashi, Nobuo; Kusaka, Katsuhiro

doi:10.1107/s2059798318012081

Cited by 15 publications

(17 citation statements)

References 43 publications

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“…A full data set composed of a total of 29 frames of time-of-flight (TOF) data from different crystal orientations was then collected, each with a 10 h exposure at 300 kW, where the crystal was held static for each of the frames. Data reduction was carried out using STARGazer (Ohhara et al, 2009;Yano et al, 2018). The crystals constituted of the anaerobically purified enzyme were designated the 'reduced form', in which the Ni-R/Ni-C state of the binuclear complex had previously been identified based on the X-ray crystal structure (Ogata et al, 2015).…”

Section: Neutron Diffraction Experimentsmentioning

confidence: 99%

Towards cryogenic neutron crystallography on the reduced form of [NiFe]-hydrogenase

Hiromoto

Nishikawa

Inoue

et al. 2020

Acta Cryst Sect D Struct Biol

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A membrane-bound hydrogenase from Desulfovibrio vulgaris Miyazaki F is a metalloenzyme that contains a binuclear Ni–Fe complex in its active site and mainly catalyzes the oxidation of molecular hydrogen to generate a proton gradient in the bacterium. The active-site Ni–Fe complex of the aerobically purified enzyme shows its inactive oxidized form, which can be reactivated through reduction by hydrogen. Here, in order to understand how the oxidized form is reactivated by hydrogen and further to directly evaluate the bridging of a hydride ligand in the reduced form of the Ni–Fe complex, a neutron structure determination was undertaken on single crystals grown in a hydrogen atmosphere. Cryogenic crystallography is being introduced into the neutron diffraction research field as it enables the trapping of short-lived intermediates and the collection of diffraction data to higher resolution. To optimize the cooling of large crystals under anaerobic conditions, the effects on crystal quality were evaluated by X-rays using two typical methods, the use of a cold nitrogen-gas stream and plunge-cooling into liquid nitrogen, and the former was found to be more effective in cooling the crystals uniformly than the latter. Neutron diffraction data for the reactivated enzyme were collected at the Japan Photon Accelerator Research Complex under cryogenic conditions, where the crystal diffracted to a resolution of 2.0 Å. A neutron diffraction experiment on the reduced form was carried out at Oak Ridge National Laboratory under cryogenic conditions and showed diffraction peaks to a resolution of 2.4 Å.

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Section: Neutron Diffraction Experimentsmentioning

confidence: 99%

Towards cryogenic neutron crystallography on the reduced form of [NiFe]-hydrogenase

Hiromoto

Nishikawa

Inoue

et al. 2020

Acta Cryst Sect D Struct Biol

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“…The height of the diagonally cut cylinder, which is the width of the TOF profile, also depends on the 2 angle and the neutron wavelength for each Bragg reflection (it will be larger with a smaller 2 angle and a longer neutron wavelength). Using the conventional integration components, namely summation integration and profile fitting (Yano et al, 2016), in the STARGazer data-processing software (Ohhara et al, 2009;Yano et al, 2018), the integration region was defined as having a simple box or elliptical cylinder shape (Fig. 2a).…”

Section: Data Reduction Of Neutron Diffraction Data: Application Of Amentioning

confidence: 99%

“…The optimum height of the integration region with a diagonally cut cylinder shape can then be determined as one value for all reflections in each detector. A component for the summation integration method with the new definition of the aforementioned integration region was implemented in the STARGazer data-processing software (Ohhara et al, 2009;Yano et al, 2018) developed for TOF diffraction data from iBIX, based on the program ISAW (Argonne National Laboratory, USA), and applied to the reduction of the TOF diffraction data set from the Y116S TTR variant measured using iBIX to evaluate the new method.…”

Section: Data Reduction Of Neutron Diffraction Data: Application Of Amentioning

confidence: 99%

Neutron diffraction experiment with the Y116S variant of transthyretin using iBIX at J-PARC: application of a new integration method

Kusaka

Yokoyama

Yamada

et al. 2020

Acta Cryst Sect D Struct Biol

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Transthyretin (TTR) is one of more than 30 amyloidogenic proteins, and the amyloid fibrils found in patients afflicted with ATTR amyloidosis are composed of this protein. Wild-type TTR amyloids accumulate in the heart in senile systemic amyloidosis (SSA). ATTR amyloidosis occurs at a much younger age than SSA, and the affected individuals carry a TTR mutant. The naturally occurring amyloidogenic Y116S TTR variant forms more amyloid fibrils than wild-type TTR. Thus, the Y116S mutation reduces the stability of the TTR structure. A neutron diffraction experiment on Y116S TTR was performed to elucidate the mechanism of the changes in structural stability between Y116S variant and wild-type TTR through structural comparison. Large crystals of the Y116S variant were grown under optimal crystallization conditions, and a single 2.4 mm3 crystal was ultimately obtained. This crystal was subjected to time-of-flight (TOF) neutron diffraction using the IBARAKI biological crystal diffractometer (iBIX) at the Japan Proton Accelerator Research Complex, Tokai, Japan (J-PARC). A full data set for neutron structure analysis was obtained in 14 days at an operational accelerator power of 500 kW. A new integration method was developed and showed improved data statistics; the new method was applied to the reduction of the TOF diffraction data from the Y116S variant. Data reduction was completed and the integrated intensities of the Bragg reflections were obtained at 1.9 Å resolution for structure refinement. Moreover, X-ray diffraction data at 1.4 Å resolution were obtained for joint neutron–X-ray refinement.

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“…While some neutron crystallography beamlines have been able to adapt these packages for their use (Langan & Greene, 2004;Blakeley et al, 2010;Meilleur et al, 2013), the most recent generation of timeof-flight (TOF) neutron diffractometers (Coates et al, 2015;Chapon et al, 2011;Tanaka et al, 2010;Langan et al, 2008) rely on in-house packages. Namely, SXD2001 (Gutmann, 2005), Mantid (Arnold et al, 2014) and STARGazer (Yano et al, 2018) are used. While these packages have enabled routine analysis for these beamlines, they have not achieved the level of maturity of their X-ray counterparts.…”

Section: Introductionmentioning

confidence: 99%

BraggNet: integrating Bragg peaks using neural networks

et al. 2019

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Neutron crystallography offers enormous potential to complement structures from X-ray crystallography by clarifying the positions of low-Z elements, namely hydrogen. Macromolecular neutron crystallography, however, remains limited, in part owing to the challenge of integrating peak shapes from pulsed-source experiments. To advance existing software, this article demonstrates the use of machine learning to refine peak locations, predict peak shapes and yield more accurate integrated intensities when applied to whole data sets from a protein crystal. The artificial neural network, based on the U-Net architecture commonly used for image segmentation, is trained using about 100 000 simulated training peaks derived from strong peaks. After 100 training epochs (a round of training over the whole data set broken into smaller batches), training converges and achieves a Dice coefficient of around 65%, in contrast to just 15% for negative control data sets. Integrating whole peak sets using the neural network yields improved intensity statistics compared with other integration methods, including k-nearest neighbours. These results demonstrate, for the first time, that neural networks can learn peak shapes and be used to integrate Bragg peaks. It is expected that integration using neural networks can be further developed to increase the quality of neutron, electron and X-ray crystallography data. research papers J. Appl. Cryst. (2019). 52, 854-863 Brendan Sullivan et al. BraggNet: integrating Bragg peaks using neural networks 855

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Status of the neutron time-of-flight single-crystal diffraction data-processing software STARGazer

Cited by 15 publications

References 43 publications

Towards cryogenic neutron crystallography on the reduced form of [NiFe]-hydrogenase

Towards cryogenic neutron crystallography on the reduced form of [NiFe]-hydrogenase

Neutron diffraction experiment with the Y116S variant of transthyretin using iBIX at J-PARC: application of a new integration method

BraggNet: integrating Bragg peaks using neural networks

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