Diffraction study of protein crystals grown in cryoloops and micromounts

A Short Review on Cryoprotectants for 3D Protein Structure Analysis

The three-dimensional structure of protein is determined by analyzing diffraction data collected using X-ray beams. However, X-ray beam can damage protein crystals during data collection, lowering the quality of the crystal data. A way to prevent such damage is by treating protein crystals with cryoprotectants. The cryoprotectant stabilizes the protein crystal and prevents lowering the quality of the diffraction data. Many kinds of cryoprotectants are commercially available, and various treatment methods have also been reported. However, incorrect selection or treatment of such cryoprotectants may lead to deterioration of crystal diffraction data when using X-ray beams.

Parsimony in Protein Conformational Change

Protein conformational change is analyzed by finding the minimalist backbone torsion angle rotations that superpose crystal structures within experimental error. Of several approaches for enforcing parsimony during flexible least-squares superposition, an ℓ(1)-norm restraint provided greatest consistency with independent indications of flexibility from nuclear magnetic resonance relaxation dispersion and chemical shift perturbation in arginine kinase and four previously studied systems. Crystallographic cross-validation shows that the dihedral parameterization describes conformational change more accurately than rigid-group approaches. The rotations that superpose the principal elements of structure constitute a small fraction of the raw (φ, ψ) differences that also reflect local conformation and experimental error. Substantial long-range displacements can be mediated by modest dihedral rotations, accommodated even within α helices and β sheets without disruption of hydrogen bonding at the hinges. Consistency between ligand-associated and intrinsic motions (in the unliganded state) implies that induced changes tend to follow low-barrier paths between conformational sub-states that are in intrinsic dynamic equilibrium.

Optimization of crystallization conditions for biological macromolecules

For the successful X-ray structure determination of macromolecules, it is first necessary to identify, usually by matrix screening, conditions that yield some sort of crystals. Initial crystals are frequently microcrystals or clusters, and often have unfavorable morphologies or yield poor diffraction intensities. It is therefore generally necessary to improve upon these initial conditions in order to obtain better crystals of sufficient quality for X-ray data collection. Even when the initial samples are suitable, often marginally, refinement of conditions is recommended in order to obtain the highest quality crystals that can be grown. The quality of an X-ray structure determination is directly correlated with the size and the perfection of the crystalline samples; thus, refinement of conditions should always be a primary component of crystal growth. The improvement process is referred to as optimization, and it entails sequential, incremental changes in the chemical parameters that influence crystallization, such as pH, ionic strength and precipitant concentration, as well as physical parameters such as temperature, sample volume and overall methodology. It also includes the application of some unique procedures and approaches, and the addition of novel components such as detergents, ligands or other small molecules that may enhance nucleation or crystal development. Here, an attempt is made to provide guidance on how optimization might best be applied to crystal-growth problems, and what parameters and factors might most profitably be explored to accelerate and achieve success.

Approaches to automated protein crystal harvesting

The harvesting of protein crystals is almost always a necessary step in the determination of a protein structure using X-ray crystallographic techniques. However, protein crystals are usually fragile and susceptible to damage during the harvesting process. For this reason, protein crystal harvesting is the single step that remains entirely dependent on skilled human intervention. Automation has been implemented in the majority of other stages of the structure-determination pipeline, including cloning, expression, purification, crystallization and data collection. The gap in automation between crystallization and data collection results in a bottleneck in throughput and presents unfortunate opportunities for crystal damage. Several automated protein crystal harvesting systems have been developed, including systems utilizing microcapillaries, microtools, microgrippers, acoustic droplet ejection and optical traps. However, these systems have yet to be commonly deployed in the majority of crystallography laboratories owing to a variety of technical and cost-related issues. Automation of protein crystal harvesting remains essential for harnessing the full benefits of fourth-generation synchrotrons, free-electron lasers and microfocus beamlines. Furthermore, automation of protein crystal harvesting offers several benefits when compared with traditional manual approaches, including the ability to harvest microcrystals, improved flash-cooling procedures and increased throughput.

Graphene as a protein crystal mounting material to reduce background scatter

The overall signal-to-noise ratio per unit dose for X-ray diffraction data from protein crystals can be improved by reducing the mass and density of all material surrounding the crystals. This article demonstrates a path towards the practical ultimate in background reduction by use of atomically thin graphene sheets as a crystal mounting platform for protein crystals. The results show the potential for graphene in protein crystallography and other cases where X-ray scatter from the mounting material must be reduced and specimen dehydration prevented, such as in coherent X-ray diffraction imaging of microscopic objects.

Integrated nonlinear optical imaging microscope for on-axis crystal detection and centering at a synchrotron beamline

Nonlinear optical (NLO) instrumentation has been integrated with synchrotron X-ray diffraction (XRD) for combined single-platform analysis, initially targeting applications for automated crystal centering. Second-harmonic-generation microscopy and two-photon-excited ultraviolet fluorescence microscopy were evaluated for crystal detection and assessed by X-ray raster scanning. Two optical designs were constructed and characterized; one positioned downstream of the sample and one integrated into the upstream optical path of the diffractometer. Both instruments enabled protein crystal identification with integration times between 80 and 150 µs per pixel, representing a ∼10(3)-10(4)-fold reduction in the per-pixel exposure time relative to X-ray raster scanning. Quantitative centering and analysis of phenylalanine hydroxylase from Chromobacterium violaceum cPAH, Trichinella spiralis deubiquitinating enzyme TsUCH37, human κ-opioid receptor complex kOR-T4L produced in lipidic cubic phase (LCP), intimin prepared in LCP, and α-cellulose samples were performed by collecting multiple NLO images. The crystalline samples were characterized by single-crystal diffraction patterns, while α-cellulose was characterized by fiber diffraction. Good agreement was observed between the sample positions identified by NLO and XRD raster measurements for all samples studied.

The use of workflows in the design and implementation of complex experiments in macromolecular crystallography

The automation of beam delivery, sample handling and data analysis, together with increasing photon flux, diminishing focal spot size and the appearance of fast-readout detectors on synchrotron beamlines, have changed the way that many macromolecular crystallography experiments are planned and executed. Screening for the best diffracting crystal, or even the best diffracting part of a selected crystal, has been enabled by the development of microfocus beams, precise goniometers and fast-readout detectors that all require rapid feedback from the initial processing of images in order to be effective. All of these advances require the coupling of data feedback to the experimental control system and depend on immediate online data-analysis results during the experiment. To facilitate this, a Data Analysis WorkBench (DAWB) for the flexible creation of complex automated protocols has been developed. Here, example workflows designed and implemented using DAWB are presented for enhanced multi-step crystal characterizations, experiments involving crystal reorientation with kappa goniometers, crystal-burning experiments for empirically determining the radiation sensitivity of a crystal system and the application of mesh scans to find the best location of a crystal to obtain the highest diffraction quality. Beamline users interact with the prepared workflows through a specific brick within the beamline-control GUI MXCuBE.

Direct cryocooling of naked crystals: are cryoprotection agents always necessary?

Over the last 20 years cryocrystallography has revolutionized the field of macromolecular crystallography, greatly reducing radiation damage and allowing the collection of complete data sets at synchrotron sources. However, in order to cool crystals to 100 K cryoprotective agents must usually be added to prevent the formation of crystalline ice, which disrupts the macromolecular crystal lattice and often results in a degradation of diffraction quality. This process can involve the extensive testing of solution compositions and soaking protocols to find suitable conditions that maintain diffraction quality. In this study, it is demonstrated that when some crystals of macromolecules are mounted in the complete absence of surrounding liquid no crystalline ice is formed and the diffraction resolution, merging R factors and mosaic spread values are comparable to those of crystals cryocooled in the presence of a cryoprotectant. This potentially removes one of the most onerous manual steps in the structure-solution pipeline and could alleviate some of the foreseen difficulties in the automation of crystal mounting.