Automated data collection and real-time data analysis suite for serial synchrotron crystallography

Basu, Shibom; Kaminski, Jakub Wojciech; Panepucci, Ezequiel; Huang, Chia‐Ying; Warshamanage, Rangana; Wang, Meitian; Wojdyla, Justyna Aleksandra

doi:10.1107/s1600577518016570

Cited by 38 publications

(44 citation statements)

References 52 publications

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“…Multiple small wedges (each of 40-45 ) were required to be merged and scaled together to give a complete data set, which in turn was used for structure determination. Thereby, isomorphous and statistically equivalent data sets were selected and merged using the automated workflow sxdm (SSX data merging), which is described in detail elsewhere (Basu et al, 2019). The sxdm package provides automatic scaling and merging of subsets, allowing the identification of the sets of subsets that result in the final merged data with the best quality.…”

Section: Data Collection and Processingmentioning

confidence: 99%

“…One of their main advantages is that diffraction data can (again) be collected from samples at room temperature (RT), versus the standard diffraction data collection at cryogenic temperatures. In parallel, much effort has been devoted to ease the challenges of data collection at synchrotron sources, from sample mounting and centering to crystal screening (Bowler et al, 2015) and data processing (Aller et al, 2015;Hirata et al, 2019;Yu et al, 2019;Sparta et al, 2016;Basu et al, 2019;Monaco et al, 2013). However, sample handling remains a major issue.…”

Section: Introductionmentioning

confidence: 99%

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Attaining atomic resolution from in situ data collection at room temperature using counter-diffusion-based low-cost microchips

Gavira

Rodríguez-Ruiz

Martínez‐Rodríguez

et al. 2020

Acta Cryst Sect D Struct Biol

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Sample handling and manipulation for cryoprotection currently remain critical factors in X-ray structural determination. While several microchips for macromolecular crystallization have been proposed during the last two decades to partially overcome crystal-manipulation issues, increased background noise originating from the scattering of chip-fabrication materials has so far limited the attainable resolution of diffraction data. Here, the conception and use of low-cost, X-ray-transparent microchips for in situ crystallization and direct data collection, and structure determination at atomic resolution close to 1.0 Å, is presented. The chips are fabricated by a combination of either OSTEMER and Kapton or OSTEMER and Mylar materials for the implementation of counter-diffusion crystallization experiments. Both materials produce a sufficiently low scattering background to permit atomic resolution diffraction data collection at room temperature and the generation of 3D structural models of the tested model proteins lysozyme, thaumatin and glucose isomerase. Although the high symmetry of the three model protein crystals produced almost complete data sets at high resolution, the potential of in-line data merging and scaling of the multiple crystals grown along the microfluidic channels is also presented and discussed.

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Section: Data Collection and Processingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Attaining atomic resolution from in situ data collection at room temperature using counter-diffusion-based low-cost microchips

Gavira

Rodríguez-Ruiz

Martínez‐Rodríguez

et al. 2020

Acta Cryst Sect D Struct Biol

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“…After cryo‐freezing of the IMISX plate, mini‐datasets were collected for each crystal using the conventional rotation imaging method. Data were integrated and merged online using an automatic processing and merging pipeline at SLS beamline PXII‐X10SA . Using this procedure, we were able to derive a high‐quality 2.7 Å resolution dataset for CCR2A‐ΔN.C (−) from 77 mini‐datasets from crystals contained within one LCP bolus using less than 3 h of data collection time (PDB http://www.rcsb.org/pdb/search/structidSearch.do?structureId=6GPX).…”

Section: Application Of Imisx To Ccr2amentioning

confidence: 99%

“…After cryo-freezing of the IMISX plate, mini-datasets were collected for each crystal using the conventional rotation imaging method. Data were integrated and merged online using an automatic processing and merging pipeline at SLS beamline PXII-X10SA [27,28]. Using this procedure, we were able to derive a high-quality 2.7…”

Section: Application Of Imisx To Ccr2amentioning

confidence: 99%

In situ crystallography as an emerging method for structure solution of membrane proteins: the case of CCR2A

Cheng¹,

Huang

Hennig³

et al. 2019

The FEBS Journal

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The in meso in situ serial X‐ray crystallization method (Huang et al., (2015) Acta Crystallogr D Biol Crystallogr 71, 1238) combines lipid cubic phase crystallization, direct freezing of the crystallization droplet without handling of the crystals, and data collection in situ. Recently, this method was used to overcome the mechanical fragility of crystals which enabled the X‐ray structure determination of chemokine receptor 2A (Apel et al., (2019) Structure 27, 427) at 2.7 Å resolution. The CCR2 structure provides the structural basis for ligand selectivity of CCR2 against chemokine receptor 5 and provides insights into the residence time of MK‐0812 analogs based on molecular dynamics simulations. These findings offer new opportunities for drug discovery targeting chemokine receptors.

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“…Automated pipelines such as MeshAndCollect (Zander et al, 2015) and ccCluster (Santoni et al, 2017) with both unit-cell-based and intensity-based HCA selection have recently been established. Basu et al (2019) provide another automated SSX software suite with selection of data based on unit-cell parameters, asymptotic I/ (ISa) (Diederichs, 2010;Diederichs & Wang, 2017) or pairwise correlation coefficients. Another approach utilizes a genetic algorithm (Zander et al, 2016;Foos et al, 2019) that generates random combinations of data sets into subsets.…”

Section: Introductionmentioning

confidence: 99%

Making a difference in multi-data-set crystallography: simple and deterministic data-scaling/selection methods

Aßmann

Wang

Diederichs

2020

Acta Crystallogr D Struct Biol

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Phasing by single-wavelength anomalous diffraction (SAD) from multiple crystallographic data sets can be particularly demanding because of the weak anomalous signal and possible non-isomorphism. The identification and exclusion of non-isomorphous data sets by suitable indicators is therefore indispensable. Here, simple and robust data-selection methods are described. A multi-dimensional scaling procedure is first used to identify data sets with large non-isomorphism relative to clusters of other data sets. Within each cluster that it identifies, further selection is based on the weighted ΔCC1/2, a quantity representing the influence of a set of reflections on the overall CC1/2 of the merged data. The anomalous signal is further improved by optimizing the scaling protocol. The success of iterating the selection and scaling steps was verified by substructure determination and subsequent structure solution. Three serial synchrotron crystallography (SSX) SAD test cases with hundreds of partial data sets and one test case with 62 complete data sets were analyzed. Structure solution was dramatically simplified with this procedure, and enabled solution of the structures after a few selection/scaling iterations. To explore the limits, the procedure was tested with much fewer data than originally required and could still solve the structure in several cases. In addition, an SSX data challenge, minimizing the number of (simulated) data sets necessary to solve the structure, was significantly underbid.

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Automated data collection and real-time data analysis suite for serial synchrotron crystallography

Cited by 38 publications

References 52 publications

Attaining atomic resolution from in situ data collection at room temperature using counter-diffusion-based low-cost microchips

Attaining atomic resolution from in situ data collection at room temperature using counter-diffusion-based low-cost microchips

In situ crystallography as an emerging method for structure solution of membrane proteins: the case of CCR2A

Making a difference in multi-data-set crystallography: simple and deterministic data-scaling/selection methods

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