Decision-making in serial crystallography: a simple test to quickly determine whether sufficient data have been collected

In standard rotational data collection for macromolecular crystallography, data are normally collected from a single crystal, and the resulting data processing delivers metrics for data completeness and signal to noise that are well established. However, in serial crystallography it can be difficult to assess quickly whether enough data have been recorded to deliver a well scaled and complete dataset with sufficient signal to noise to address the scientific question being asked. Completeness alone is not an appropriate metric, as a nominally complete dataset can be obtained with a much smaller number of images, and thus multiplicity, than is needed to produce a final dataset with well estimated merged intensity values. Insufficient data result in alarmingly reasonable processing statistics and plausible electron-density maps that contain almost no experimental signal, instead being dominated by the phases from the phasing model. We have therefore established a simple electron-density-based test to determine whether enough data have been collected, and implemented this in the autoprocessing pipeline at the T-REXX endstation on beamline P14 at PETRA III. Importantly, the results of this perturbed model real-space difference density (PMRDD) test help to guide decisions as to whether more data should be collected or whether the experimenter can move onto a new time-point or sample.

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Publication Details

Journal
Acta Crystallographica Section D Structural Biology
Published
2026-02-13
DOI
https://doi.org/10.1107/s2059798326001324
Primary Topic
Enzyme Structure and Function
Type
article
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article

Decision-making in serial crystallography: a simple test to quickly determine whether sufficient data have been collected

David von Stetten, Arwen R. Pearson
Acta Crystallographica Section D Structural Biology
Enzyme Structure and Function
article

Decision-making in serial crystallography: a simple test to quickly determine whether sufficient data have been collected

David von Stetten, Arwen R. Pearson
article en

Abstract

In standard rotational data collection for macromolecular crystallography, data are normally collected from a single crystal, and the resulting data processing delivers metrics for data completeness and signal to noise that are well established. However, in serial crystallography it can be difficult to assess quickly whether enough data have been recorded to deliver a well scaled and complete dataset with sufficient signal to noise to address the scientific question being asked. Completeness alone is not an appropriate metric, as a nominally complete dataset can be obtained with a much smaller number of images, and thus multiplicity, than is needed to produce a final dataset with well estimated merged intensity values. Insufficient data result in alarmingly reasonable processing statistics and plausible electron-density maps that contain almost no experimental signal, instead being dominated by the phases from the phasing model. We have therefore established a simple electron-density-based test to determine whether enough data have been collected, and implemented this in the autoprocessing pipeline at the T-REXX endstation on beamline P14 at PETRA III. Importantly, the results of this perturbed model real-space difference density (PMRDD) test help to guide decisions as to whether more data should be collected or whether the experimenter can move onto a new time-point or sample.

Acta Crystallographica Section D Structural BiologyVol. 82(3)
Universität Hamburg (DE), European Molecular Biology Laboratory (DE), Max Planck Institute for the Structure and Dynamics of Matter (DE), European Molecular Biology Laboratory (DE)
Peace, Justice and strong institutions
Openalex Percentile: Top 41%
Enzyme Structure and Function
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Decision-making in serial crystallography: a simple test to quickly determine whether sufficient data have been collected — David von Stetten, Arwen R. Pearson · Acta Crystallographica Section D Structural Biology (2026) | TGRS Research Map | TGRS