A standard data format for 3DED/MicroED

Electron diffraction from three dimensional crystals, as a technique for solving molecular structures, is rapidly increasing in popularity. The development of methodology and software has borrowed, to great effect, from macromolecular X-ray crystallography. However, standardization lags behind the development of the technique, and practitioners are forced to work with inadequate data formats that are unable to capture a full description of their experiments. This creates obstacles that are increasingly difficult to overcome as experiments become ever faster and the need for data autoprocessing becomes more pressing. We present a data format standard based on best practice from macromolecular crystallography and demonstrate how the adoption of this standard enabled autoprocessing of datasets collected with a high-throughput detector system.

Experimental phasing opportunities for macromolecular crystallography at very long wavelengths

Despite recent advances in cryo-electron microscopy and artificial intelligence-based model predictions, a significant fraction of structure determinations by macromolecular crystallography still requires experimental phasing, usually by means of single-wavelength anomalous diffraction (SAD) techniques. Most synchrotron beamlines provide highly brilliant beams of X-rays of between 0.7 and 2 Å wavelength. Use of longer wavelengths to access the absorption edges of biologically important lighter atoms such as calcium, potassium, chlorine, sulfur and phosphorus for native-SAD phasing is attractive but technically highly challenging. The long-wavelength beamline I23 at Diamond Light Source overcomes these limitations and extends the accessible wavelength range to λ = 5.9 Å. Here we report 22 macromolecular structures solved in this extended wavelength range, using anomalous scattering from a range of elements which demonstrate the routine feasibility of lighter atom phasing. We suggest that, in light of its advantages, long-wavelength crystallography is a compelling option for experimental phasing.

The CCP4 suite: integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.

xia2.multiplex: a multi-crystal data-analysis pipeline

A new program, xia2.multiplex, has been developed to facilitate symmetry analysis, scaling and merging of multi-crystal data sets.

In macromolecular crystallography, radiation damage limits the amount of data that can be collected from a single crystal. It is often necessary to merge data sets from multiple crystals; for example, small-wedge data collections from micro-crystals, in situ room-temperature data collections and data collection from membrane proteins in lipidic mesophases. Whilst the indexing and integration of individual data sets may be relatively straightforward with existing software, merging multiple data sets from small wedges presents new challenges. The identification of a consensus symmetry can be problematic, particularly in the presence of a potential indexing ambiguity. Furthermore, the presence of non-isomorphous or poor-quality data sets may reduce the overall quality of the final merged data set. To facilitate and help to optimize the scaling and merging of multiple data sets, a new program, xia2.multiplex, has been developed which takes data sets individually integrated with DIALS and performs symmetry analysis, scaling and merging of multi-crystal data sets. xia2.multiplex also performs analysis of various pathologies that typically affect multi-crystal data sets, including non-isomorphism, radiation damage and preferential orientation. After the description of a number of use cases, the benefit of xia2.multiplex is demonstrated within a wider autoprocessing framework in facilitating a multi-crystal experiment collected as part of in situ room-temperature fragment-screening experiments on the SARS-CoV-2 main protease.

DIALS as a toolkit

The DIALS software for the processing of X‐ray diffraction data is presented, with an emphasis on how the suite may be used as a toolkit for data processing. The description starts with an overview of the history and intent of the toolkit, usage as an automated system, command‐line use, and ultimately how new tools can be written using the API to perform bespoke analysis. Consideration is also made to the application of DIALS to techniques outside of macromolecular X‐ray crystallography.

Gold Standard for macromolecular crystallography diffraction data

Macromolecular crystallography (MX) is the dominant means of determining the three-dimensional structures of biological macromolecules. Over the last few decades, most MX data have been collected at synchrotron beamlines using a large number of different detectors produced by various manufacturers and taking advantage of various protocols and goniometries. These data came in their own formats: sometimes proprietary, sometimes open. The associated metadata rarely reached the degree of completeness required for data management according to Findability, Accessibility, Interoperability and Reusability (FAIR) principles. Efforts to reuse old data by other investigators or even by the original investigators some time later were often frustrated. In the culmination of an effort dating back more than two decades, a large portion of the research community concerned with high data-rate macromolecular crystallography (HDRMX) has now agreed to an updated specification of data and metadata for diffraction images produced at synchrotron light sources and X-ray free-electron lasers (XFELs). This 'Gold Standard' will facilitate the processing of data sets independent of the facility at which they were collected and enable data archiving according to FAIR principles, with a particular focus on interoperability and reusability. This agreed standard builds on the NeXus/HDF5 NXmx application definition and the International Union of Crystallo-graphy (IUCr) imgCIF/CBF dictionary, and it is compatible with major data-processing programs and pipelines. Just as with the IUCr CBF/imgCIF standard from which it arose and to which it is tied, the NeXus/HDF5 NXmx Gold Standard application definition is intended to be applicable to all detectors used for crystallography, and all hardware and software developers in the field are encouraged to adopt and contribute to the standard.

Scaling diffraction data in the DIALS software package: algorithms and new approaches for multi-crystal scaling

In processing X-ray diffraction data, the intensities obtained from integration of the diffraction images must be corrected for experimental effects in order to place all intensities on a common scale both within and between data collections. Scaling corrects for effects such as changes in sample illumination, absorption and, to some extent, global radiation damage that cause the measured intensities of symmetry-equivalent observations to differ throughout a data set. This necessarily requires a prior evaluation of the point-group symmetry of the crystal. This paper describes and evaluates the scaling algorithms implemented within the DIALS data-processing package and demonstrates the effectiveness and key features of the implementation on example macromolecular crystallographic rotation data. In particular, the scaling algorithms enable new workflows for the scaling of multi-crystal or multi-sweep data sets, providing the analysis required to support current trends towards collecting data from ever-smaller samples. In addition, the implementation of a free-set validation method is discussed, which allows the quantification of the suitability of scaling-model and algorithm choices.

How best to use photons

Strategies for collecting X-ray diffraction data have evolved alongside beamline hardware and detector developments. The traditional approaches for diffraction data collection have emphasised collecting data from noisy integrating detectors (i.e. film, image plates and CCD detectors). With fast pixel array detectors on stable beamlines, the limiting factor becomes the sample lifetime, and the question becomes one of how to expend the photons that your sample can diffract, i.e. as a smaller number of stronger measurements or a larger number of weaker data. This parameter space is explored via experiment and synthetic data treatment and advice is derived on how best to use the equipment on a modern beamline. Suggestions are also made on how to acquire data in a conservative manner if very little is known about the sample lifetime.

Structure determination and crystal chemistry of large repeat mixed-layer hexaferrites

Hexaferrites are an important class of magnetic oxides with applications in data storage and electronics. Their crystal structures are highly modular, consisting of Fe- or Ba-rich close-packed blocks that can be stacked in different sequences to form a multitude of unique structures, producing large anisotropic unit cells with lattice parameters typically >100 Å along the stacking axis. This has limited atomic-resolution structure solutions to relatively simple examples such as Ba2Zn2Fe12O22, whilst longer stacking sequences have been modelled only in terms of block sequences, with no refinement of individual atomic coordinates or occupancies. This paper describes the growth of a series of complex hexaferrite crystals, their atomic-level structure solution by high-resolution synchrotron X-ray diffraction, electron diffraction and imaging methods, and their physical characterization by magnetometry. The structures include a new hexaferrite stacking sequence, with the longest lattice parameter of any hexaferrite with a fully determined structure.

Improving signal strength in serial crystallography with DIALS geometry refinement

The DIALS diffraction-modeling software package has been applied to serial crystallography data. Diffraction modeling is an exercise in determining the experimental parameters, such as incident beam wavelength, crystal unit cell and orientation, and detector geometry, that are most consistent with the observed positions of Bragg spots. These parameters can be refined by nonlinear least-squares fitting. In previous work, it has been challenging to refine both the positions of the sensors (metrology) on multipanel imaging detectors such as the CSPAD and the orientations of all of the crystals studied. Since the optimal models for metrology and crystal orientation are interdependent, alternate cycles of panel refinement and crystal refinement have been required. To simplify the process, a sparse linear algebra technique for solving the normal equations was implemented, allowing the detector panels to be refined simultaneously against the diffraction from thousands of crystals with excellent computational performance. Separately, it is shown how to refine the metrology of a second CSPAD detector, positioned at a distance of 2.5 m from the crystal, used for recording low-angle reflections. With the ability to jointly refine the detector position against the ensemble of all crystals used for structure determination, it is shown that ensemble refinement greatly reduces the apparent nonisomorphism that is often observed in the unit-cell distributions from still-shot serial crystallography. In addition, it is shown that batching the images by timestamp and re-refining the detector position can realistically model small, time-dependent variations in detector position relative to the sample, and thereby improve the integrated structure-factor intensity signal and heavy-atom anomalous peak heights.

Determination of Patterson group symmetry from sparse multi-crystal data sets in the presence of an indexing ambiguity

Combining X-ray diffraction data from multiple samples requires determination of the symmetry and resolution of any indexing ambiguity. For the partial data sets typical of in situ room-temperature experiments, determination of the correct symmetry is often not straightforward. The potential for indexing ambiguity in polar space groups is also an issue, although methods to resolve this are available if the true symmetry is known. Here, a method is presented to simultaneously resolve the determination of the Patterson symmetry and the indexing ambiguity for partial data sets.

DIALS: implementation and evaluation of a new integration package

The DIALS project is a collaboration between Diamond Light Source, Lawrence Berkeley National Laboratory and CCP4 to develop a new software suite for the analysis of crystallographic X-ray diffraction data, initially encompassing spot finding, indexing, refinement and integration. The design, core algorithms and structure of the software are introduced, alongside results from the analysis of data from biological and chemical crystallography experiments.

Background modelling of diffraction data in the presence of ice rings

An algorithm for modelling the background for each Bragg reflection in a series of X-ray diffraction images containing Debye-Scherrer diffraction from ice in the sample is presented. The method involves the use of a global background model which is generated from the complete X-ray diffraction data set. Fitting of this model to the background pixels is then performed for each reflection independently. The algorithm uses a static background model that does not vary over the course of the scan. The greatest improvement can be expected for data where ice rings are present throughout the data set and the local background shape at the size of a spot on the detector does not exhibit large time-dependent variation. However, the algorithm has been applied to data sets whose background showed large pixel variations (variance/mean > 2) and has been shown to improve the results of processing for these data sets. It is shown that the use of a simple flat-background model as in traditional integration programs causes systematic bias in the background determination at ice-ring resolutions, resulting in an overestimation of reflection intensities at the peaks of the ice rings and an underestimation of reflection intensities either side of the ice ring. The new global background-model algorithm presented here corrects for this bias, resulting in a noticeable improvement in R factors following refinement.

Preliminary evaluation of cytosine-phosphate-guanine oligodeoxynucleotides bound to gelatine nanoparticles as immunotherapy for canine atopic dermatitis

Cytosine-phosphate-guanine oligodeoxynucleotides (CpG ODN) are a promising new immunotherapeutic treatment option for canine atopic dermatitis (AD). The aim of this uncontrolled pilot study was to evaluate clinical and immunological effects of gelatine nanoparticle (GNP)-bound CpG ODN (CpG GNP) on atopic dogs. Eighteen dogs with AD were treated for 8 weeks (group 1, n=8) or 18 weeks (group 2, n=10). Before inclusion and after 2 weeks, 4 weeks, 6 weeks (group 1+2), 8 weeks, 12 weeks and 16 weeks (group 2) 75 µg CpG ODN/dog (bound to 1.5 mg GNP) were injected subcutaneously. Pruritus was evaluated daily by the owner. Lesions were evaluated and serum concentrations and mRNA expressions of interferon-γ, tumour necrosis factor-α, transforming growth factor-β, interleukin (IL) 10 and IL-4 (only mRNA expression) were determined at inclusion and after 8 weeks (group 1+2) and 18 weeks (group 2). Lesions and pruritus improved significantly from baseline to week 8. Mean improvements from baseline to week 18 were 23 per cent and 44 per cent for lesions and pruritus, respectively, an improvement of ≥50 per cent was seen in six out of nine and three out of six dogs, respectively. IL-4 mRNA expression decreased significantly. The results of this study show a clinical improvement of canine AD with CpG GNP comparable to allergen immunotherapy. Controlled studies are needed to confirm these findings.

Guanine Can Direct Binding Specificity of Ru-dipyridophenazine (dppz) Complexes to DNA through Steric Effects

X-ray crystal structures of three Λ-[Ru(L)2 dppz]2+ complexes (dppz=dipyridophenazine; L=1,10-phenanthroline (phen), 2,2'-bipyridine (bpy)) bound to d((5BrC)GGC/GCCG) showed the compounds intercalated at a 5'-CG-3' step. The compounds bind through canted intercalation, with the binding angle determined by the guanine NH2 group, in contrast to symmetrical intercalation previously observed at 5'-TA-3' sites. This result suggests that canted intercalation is preferred at 5'-CG-3' sites even though the site itself is symmetrical, and we hypothesise that symmetrical intercalation in a 5'-CG-3' step could give rise to a longer luminescence lifetime than canted intercalation.

Robust background modelling in DIALS

A method for estimating the background under each reflection during integration that is robust in the presence of pixel outliers is presented. The method uses a generalized linear model approach that is more appropriate for use with Poisson distributed data than traditional approaches to pixel outlier handling in integration programs. The algorithm is most applicable to data with a very low background level where assumptions of a normal distribution are no longer valid as an approximation to the Poisson distribution. It is shown that traditional methods can result in the systematic underestimation of background values. This then results in the reflection intensities being overestimated and gives rise to a change in the overall distribution of reflection intensities in a dataset such that too few weak reflections appear to be recorded. Statistical tests performed during data reduction may mistakenly attribute this to merohedral twinning in the crystal. Application of the robust generalized linear model algorithm is shown to correct for this bias.

Delta chirality ruthenium 'light-switch' complexes can bind in the minor groove of DNA with five different binding modes

[Ru(phen)₂(dppz)]²⁺ has been studied since the 1990s due to its 'light-switch' properties. It can be used as a luminescent DNA probe, with emission switched on through DNA binding. The luminescence observed is dependent on the solvent accessibility of the pyrazine nitrogen atoms, and therefore is sensitive to changes in both binding site of the cation and chromophore orientation. The compound is also chiral, and there are distinct differences between the enantiomers in terms of the emission behaviour when bound to a variety of DNA sequences. Whilst a number of binary DNA-complex X-ray crystal structures are available, most include the Λ enantiomer and there is very little structural information about binding of the Δ enantiomer. Here, we present the first X-ray crystal structure of a Δ enantiomer bound to well-matched DNA, in the absence of the other, Λ enantiomer. We show how the binding site observed here can be related to a more general pattern of motifs in the crystallographic literature and propose that the Δ enantiomer can bind with five different binding modes, offering a new hypothesis for the interpretation of solution data.

Diffraction-geometry refinement in the DIALS framework

A comprehensive description of the methods used within the DIALS framework for diffraction-geometry refinement using predicted reflection centroids is given. Examples of the advanced features of the software are provided.

Rapid data collection and modern computing resources provide the opportunity to revisit the task of optimizing the model of diffraction geometry prior to integration. A comprehensive description is given of new software that builds upon established methods by performing a single global refinement procedure, utilizing a smoothly varying model of the crystal lattice where appropriate. This global refinement technique extends to multiple data sets, providing useful constraints to handle the problem of correlated parameters, particularly for small wedges of data. Examples of advanced uses of the software are given and the design is explained in detail, with particular emphasis on the flexibility and extensibility it entails.

A simple methodology for characterization of germanium coaxial detectors by using Monte Carlo simulation and evolutionary algorithms

The determination in a sample of the activity concentration of a specific radionuclide by gamma spectrometry needs to know the full energy peak efficiency (FEPE) for the energy of interest. The difficulties related to the experimental calibration make it advisable to have alternative methods for FEPE determination, such as the simulation of the transport of photons in the crystal by the Monte Carlo method, which requires an accurate knowledge of the characteristics and geometry of the detector. The characterization process is mainly carried out by Canberra Industries Inc. using proprietary techniques and methodologies developed by that company. It is a costly procedure (due to shipping and to the cost of the process itself) and for some research laboratories an alternative in situ procedure can be very useful. The main goal of this paper is to find an alternative to this costly characterization process, by establishing a method for optimizing the parameters of characterizing the detector, through a computational procedure which could be reproduced at a standard research lab. This method consists in the determination of the detector geometric parameters by using Monte Carlo simulation in parallel with an optimization process, based on evolutionary algorithms, starting from a set of reference FEPEs determined experimentally or computationally. The proposed method has proven to be effective and simple to implement. It provides a set of characterization parameters which it has been successfully validated for different source-detector geometries, and also for a wide range of environmental samples and certified materials.

Nanoparticulate CpG immunotherapy in RAO-affected horses: phase I and IIa study

Background

Recurrent airway obstruction (RAO), an asthma‐like disease, is 1 of the most common allergic diseases in horses in the northern hemisphere. Hypersensitivity reactions to environmental antigens cause an allergic inflammatory response in the equine airways. Cytosine‐phosphate‐guanosine‐oligodeoxynucleotides (CpG‐ODN) are known to direct the immune system toward a Th1‐pathway, and away from the pro‐allergic Th2‐line (Th2/Th1‐shift). Gelatin nanoparticles (GNPs) are biocompatible and biodegradable immunological inert drug delivery systems that protect CpG‐ODN against nuclease degeneration. Preliminary studies on the inhalation of GNP‐bound CpG‐ODN in RAO‐affected horses have shown promising results.

Objectives

The aim of this study was to evaluate the clinical and immunological effects of GNP‐bound CpG‐ODN in a double‐blinded, placebo‐controlled, prospective, randomized clinical trial and to verify a sustained effect post‐treatment.

Animals and Methods

Twenty‐four RAO‐affected horses received 1 inhalation every 2 days for 5 consecutive administrations. Horses were examined for clinical, endoscopic, cytological, and blood biochemical variables before the inhalation regimen (I), immediately afterwards (II), and 4 weeks post‐treatment (III).

Results

At time points I and II, administration of treatment rather than placebo corresponded to a statistically significant decrease in respiratory effort, nasal discharge, tracheal secretion, and viscosity, AaDO₂ and neutrophil percentage, and an increase in arterial oxygen pressure.

Conclusion and Clinical Importance

Administration of a GNP‐bound CpG‐ODN formulation caused a potent and persistent effect on allergic and inflammatory‐induced clinical variables in RAO‐affected horses. This treatment, therefore, provides an innovative, promising, and well‐tolerated strategy beyond conventional symptomatic long‐term therapy and could serve as a model for asthma treatment in humans.