A redox switch allows binding of Fe(II) and Fe(III) ions in the cyanobacterial iron-binding protein FutA from Prochlorococcus.

The marine cyanobacterium Prochlorococcus is a main contributor to global photosynthesis, whilst being limited by iron availability. Cyanobacterial genomes generally encode two different types of FutA iron-binding proteins: periplasmic FutA2 ABC transporter subunits bind Fe(III), while cytosolic FutA1 binds Fe(II). Owing to their small size and their economized genome Prochlorococcus ecotypes typically possess a single futA gene. How the encoded FutA protein might bind different Fe oxidation states was previously unknown. Here, we use structural biology techniques at room temperature to probe the dynamic behavior of FutA. Neutron diffraction confirmed four negatively charged tyrosinates, that together with a neutral water molecule coordinate iron in trigonal bipyramidal geometry. Positioning of the positively charged Arg103 side chain in the second coordination shell yields an overall charge-neutral Fe(III) binding state in structures determined by neutron diffraction and serial femtosecond crystallography. Conventional rotation X-ray crystallography using a home source revealed X-ray-induced photoreduction of the iron center with observation of the Fe(II) binding state; here, an additional positioning of the Arg203 side chain in the second coordination shell maintained an overall charge neutral Fe(II) binding site. Dose series using serial synchrotron crystallography and an XFEL X-ray pump-probe approach capture the transition between Fe(III) and Fe(II) states, revealing how Arg203 operates as a switch to accommodate the different iron oxidation states. This switching ability of the Prochlorococcus FutA protein may reflect ecological adaptation by genome streamlining and loss of specialized FutA proteins.

Computational models of amorphous ice for accurate simulation of cryo-EM images of biological samples.

Simulations of cryo-electron microscopy (cryo-EM) images of biological samples can be used to produce test datasets to support the development of instrumentation, methods, and software, as well as to assess data acquisition and analysis strategies. To be useful, these simulations need to be based on physically realistic models which include large volumes of amorphous ice. The gold standard model for EM image simulation is a physical atom-based ice model produced using molecular dynamics simulations. Although practical for small sample volumes; for simulation of cryo-EM data from large sample volumes, this can be too computationally expensive. We have evaluated a Gaussian Random Field (GRF) ice model which is shown to be more computationally efficient for large sample volumes. The simulated EM images are compared with the gold standard atom-based ice model approach and shown to be directly comparable. Comparison with experimentally acquired data shows the Gaussian random field ice model produces realistic simulations. The software required has been implemented in the Parakeet software package and the underlying atomic models are available online for use by the wider community.

Atomic structure of a nudivirus occlusion body protein determined from a 70-year-old crystal sample.

Infectious protein crystals are an essential part of the viral lifecycle for double-stranded DNA Baculoviridae and double-stranded RNA cypoviruses. These viral protein crystals, termed occlusion bodies or polyhedra, are dense protein assemblies that form a crystalline array, encasing newly formed virions. Here, using X-ray crystallography we determine the structure of a polyhedrin from Nudiviridae. This double-stranded DNA virus family is a sister-group to the baculoviruses, whose members were thought to lack occlusion bodies. The 70-year-old sample contains a well-ordered lattice formed by a predominantly α-helical building block that assembles into a dense, highly interconnected protein crystal. The lattice is maintained by extensive hydrophobic and electrostatic interactions, disulfide bonds, and domain switching. The resulting lattice is resistant to most environmental stresses. Comparison of this structure to baculovirus or cypovirus polyhedra shows a distinct protein structure, crystal space group, and unit cell dimensions, however, all polyhedra utilise common principles of occlusion body assembly.

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.

Investigation of the milling characteristics of different focused-ion-beam sources assessed by three-dimensional electron diffraction from crystal lamellae.

Three-dimensional electron diffraction (3DED) from nanocrystals of biological macromolecules requires the use of very small crystals. These are typically less than 300 nm-thick in the direction of the electron beam due to the strong interaction between electrons and matter. In recent years, focused-ion-beam (FIB) milling has been used in the preparation of thin samples for 3DED. These instruments typically use a gallium liquid metal ion source. Inductively coupled plasma (ICP) sources in principle offer faster milling rates. Little work has been done to quantify the damage these sources cause to delicate biological samples at cryogenic temperatures. Here, an analysis of the effect that milling with plasma FIB (pFIB) instrumentation has on lysozyme crystals is presented. This work evaluates both argon and xenon plasmas and compares them with crystals milled with a gallium source. A milling protocol was employed that utilizes an overtilt to produce wedge-shaped lamellae with a shallow thickness gradient which yielded very thin crystalline samples. 3DED data were then acquired and standard data-processing statistics were employed to assess the quality of the diffraction data. An upper bound to the depth of the pFIB-milling damage layer of between 42.5 and 50 nm is reported, corresponding to half the thickness of the thinnest lamellae that resulted in usable diffraction data. A lower bound of between 32.5 and 40 nm is also reported, based on a literature survey of the minimum amount of diffracting material required for 3DED.

Trapping and structural characterisation of a covalent intermediate in vitamin B6 biosynthesis catalysed by the Pdx1 PLP synthase.

The Pdx1 enzyme catalyses condensation of two carbohydrates and ammonia to form pyridoxal 5-phosphate (PLP) via an imine relay mechanism of carbonyl intermediates. The I333 intermediate characterised here using structural, UV-vis absorption spectroscopy and mass spectrometry analyses rationalises stereoselective deprotonation and subsequent substrate assisted phosphate elimination, central to PLP biosynthesis.

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.

Parakeet: a digital twin software pipeline to assess the impact of experimental parameters on tomographic reconstructions for cryo-electron tomography.

In cryo-electron tomography (cryo-ET) of biological samples, the quality of tomographic reconstructions can vary depending on the transmission electron microscope (TEM) instrument and data acquisition parameters. In this paper, we present Parakeet, a 'digital twin' software pipeline for the assessment of the impact of various TEM experiment parameters on the quality of three-dimensional tomographic reconstructions. The Parakeet digital twin is a digital model that can be used to optimize the performance and utilization of a physical instrument to enable in silico optimization of sample geometries, data acquisition schemes and instrument parameters. The digital twin performs virtual sample generation, TEM image simulation, and tilt series reconstruction and analysis within a convenient software framework. As well as being able to produce physically realistic simulated cryo-ET datasets to aid the development of tomographic reconstruction and subtomogram averaging programs, Parakeet aims to enable convenient assessment of the effects of different microscope parameters and data acquisition parameters on reconstruction quality. To illustrate the use of the software, we present the example of a quantitative analysis of missing wedge artefacts on simulated planar and cylindrical biological samples and discuss how data collection parameters can be modified for cylindrical samples where a full 180° tilt range might be measured.

A Sample Preparation Pipeline for Microcrystals at the VMXm Beamline.

The mounting of microcrystals (<10 µm) for single crystal cryo-crystallography presents a non-trivial challenge. Improvements in data quality have been seen for microcrystals with the development of beamline optics, beam stability and variable beam size focusing from submicron to microns, such as at the VMXm beamline at Diamond Light Source1. Further improvements in data quality will be gained through improvements in sample environment and sample preparation. Microcrystals inherently generate weaker diffraction, therefore improving the signal-to-noise is key to collecting quality X-ray diffraction data and will predominantly come from reductions in background noise. Major sources of X-ray background noise in a diffraction experiment are from their interaction with the air path before and after the sample, excess crystallization solution surrounding the sample, the presence of crystalline ice and scatter from any other beamline instrumentation or X-ray windows. The VMXm beamline comprises instrumentation and a sample preparation protocol to reduce all these sources of noise. Firstly, an in-vacuum sample environment at VMXm removes the air path between X-ray source and sample. Next, sample preparation protocols for macromolecular crystallography at VMXm utilize a number of processes and tools adapted from cryoTEM. These include copper grids with holey carbon support films, automated blotting and plunge cooling robotics making use of liquid ethane. These tools enable the preparation of hundreds of microcrystals on a single cryoTEM grid with minimal surrounding liquid on a low-noise support. They also minimize the formation of crystalline ice from any remaining liquid surrounding the crystals. We present the process for preparing and assessing the quality of soluble protein microcrystals using visible light and scanning electron microscopy before mounting the samples on the VMXm beamline for X-ray diffraction experiments. We will also provide examples of good quality samples as well as those which require further optimization and strategies to do so.

An on-demand, drop-on-drop method for studying enzyme catalysis by serial crystallography.

Serial femtosecond crystallography has opened up many new opportunities in structural biology. In recent years, several approaches employing light-inducible systems have emerged to enable time-resolved experiments that reveal protein dynamics at high atomic and temporal resolutions. However, very few enzymes are light-dependent, whereas macromolecules requiring ligand diffusion into an active site are ubiquitous. In this work we present a drop-on-drop sample delivery system that enables the study of enzyme-catalyzed reactions in microcrystal slurries. The system delivers ligand solutions in bursts of multiple picoliter-sized drops on top of a larger crystal-containing drop inducing turbulent mixing and transports the mixture to the X-ray interaction region with temporal resolution. We demonstrate mixing using fluorescent dyes, numerical simulations and time-resolved serial femtosecond crystallography, which show rapid ligand diffusion through microdroplets. The drop-on-drop method has the potential to be widely applicable to serial crystallography studies, particularly of enzyme reactions with small molecule substrates.

A Workflow for Protein Structure Determination From Thin Crystal Lamella by Micro-Electron Diffraction.

MicroED has recently emerged as a powerful method for the analysis of biological structures at atomic resolution. This technique has been largely limited to protein nanocrystals which grow either as needles or plates measuring only a few hundred nanometers in thickness. Furthermore, traditional microED data processing uses established X-ray crystallography software that is not optimized for handling compound effects that are unique to electron diffraction data. Here, we present an integrated workflow for microED, from sample preparation by cryo-focused ion beam milling, through data collection with a standard Ceta-D detector, to data processing using the DIALS software suite, thus enabling routine atomic structure determination of protein crystals of any size and shape using microED. We demonstrate the effectiveness of the workflow by determining the structure of proteinase K to 2.0 Å resolution and show the advantage of using protein crystal lamellae over nanocrystals.

High-throughput in situ experimental phasing.

In this article, a new approach to experimental phasing for macromolecular crystallography (MX) at synchrotrons is introduced and described for the first time. It makes use of automated robotics applied to a multi-crystal framework in which human intervention is reduced to a minimum. Hundreds of samples are automatically soaked in heavy-atom solutions, using a Labcyte Inc. Echo 550 Liquid Handler, in a highly controlled and optimized fashion in order to generate derivatized and isomorphous crystals. Partial data sets obtained on MX beamlines using an in situ setup for data collection are processed with the aim of producing good-quality anomalous signal leading to successful experimental phasing.

Scanning electron microscopy as a method for sample visualization in protein X-ray crystallography.

Developing methods to determine high-resolution structures from micrometre- or even submicrometre-sized protein crystals has become increasingly important in recent years. This applies to both large protein complexes and membrane proteins, where protein production and the subsequent growth of large homogeneous crystals is often challenging, and to samples which yield only micro- or nanocrystals such as amyloid or viral polyhedrin proteins. The versatile macromolecular crystallography microfocus (VMXm) beamline at Diamond Light Source specializes in X-ray diffraction measurements from micro- and nanocrystals. Because of the possibility of measuring data from crystalline samples that approach the resolution limit of visible-light microscopy, the beamline design includes a scanning electron microscope (SEM) to visualize, locate and accurately centre crystals for X-ray diffraction experiments. To ensure that scanning electron microscopy is an appropriate method for sample visualization, tests were carried out to assess the effect of SEM radiation on diffraction quality. Cytoplasmic polyhedrosis virus polyhedrin protein crystals cryocooled on electron-microscopy grids were exposed to SEM radiation before X-ray diffraction data were collected. After processing the data with DIALS, no statistically significant difference in data quality was found between datasets collected from crystals exposed and not exposed to SEM radiation. This study supports the use of an SEM as a tool for the visualization of protein crystals and as an integrated visualization tool on the VMXm beamline.

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.

The predictive power of data-processing statistics.

This study describes a method to estimate the likelihood of success in determining a macromolecular structure by X-ray crystallography and experimental single-wavelength anomalous dispersion (SAD) or multiple-wavelength anomalous dispersion (MAD) phasing based on initial data-processing statistics and sample crystal properties. Such a predictive tool can rapidly assess the usefulness of data and guide the collection of an optimal data set. The increase in data rates from modern macromolecular crystallography beamlines, together with a demand from users for real-time feedback, has led to pressure on computational resources and a need for smarter data handling. Statistical and machine-learning methods have been applied to construct a classifier that displays 95% accuracy for training and testing data sets compiled from 440 solved structures. Applying this classifier to new data achieved 79% accuracy. These scores already provide clear guidance as to the effective use of computing resources and offer a starting point for a personalized data-collection assistant.

Measuring energy-dependent photoelectron escape in microcrystals.

With the increasing trend of using microcrystals and intense microbeams at synchrotron X-ray beamlines, radiation damage becomes a more pressing problem. Theoretical calculations show that the photoelectrons that primarily cause damage can escape microcrystals. This effect would become more pronounced with decreasing crystal size as well as at higher energies. To prove this effect, data from cryocooled lysozyme crystals of dimensions 5 × 3 × 3 and 20 × 8 × 8 µm mounted on cryo-transmission electron microscopy (cryo-TEM) grids were collected at 13.5 and 20.1 keV using a PILATUS CdTe 2M detector, which has a similar quantum efficiency at both energies. Accurate absorbed doses were calculated through the direct measurement of individual crystal sizes using scanning electron microscopy after the experiment and characterization of the X-ray microbeam. The crystal lifetime was then quantified based on the D 1/2 metric. In this first systematic study, a longer crystal lifetime for smaller crystals was observed and crystal lifetime increased at higher X-ray energies, supporting the theoretical predictions of photoelectron escape. The use of detector technologies specifically optimized for data collection at energies above 20 keV allows the theoretically predicted photoelectron escape to be quantified and exploited, guiding future beamline-design choices.

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.

Machining protein microcrystals for structure determination by electron diffraction.

We demonstrate that ion-beam milling of frozen, hydrated protein crystals to thin lamella preserves the crystal lattice to near-atomic resolution. This provides a vehicle for protein structure determination, bridging the crystal size gap between the nanometer scale of conventional electron diffraction and micron scale of synchrotron microfocus beamlines. The demonstration that atomic information can be retained suggests that milling could provide such detail on sections cut from vitrified cells.

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.

Where is crystallography going?

Macromolecular crystallography (MX) has been a motor for biology for over half a century and this continues apace. A series of revolutions, including the production of recombinant proteins and cryo-crystallography, have meant that MX has repeatedly reinvented itself to dramatically increase its reach. Over the last 30 years synchrotron radiation has nucleated a succession of advances, ranging from detectors to optics and automation. These advances, in turn, open up opportunities. For instance, a further order of magnitude could perhaps be gained in signal to noise for general synchrotron experiments. In addition, X-ray free-electron lasers offer to capture fragments of reciprocal space without radiation damage, and open up the subpicosecond regime of protein dynamics and activity. But electrons have recently stolen the limelight: so is X-ray crystallography in rude health, or will imaging methods, especially single-particle electron microscopy, render it obsolete for the most interesting biology, whilst electron diffraction enables structure determination from even the smallest crystals? We will lay out some information to help you decide.