What's in a drop? Correlating observations and outcomes to guide macromolecular crystallization experiments

Phase Separation and Aggregation of α-Synuclein Diverge at Different Salt Conditions

The coacervation of alpha-synuclein (αSyn) into cytotoxic oligomers and amyloid fibrils are considered pathological hallmarks of Parkinson's disease. While aggregation is central to amyloid diseases, liquid-liquid phase separation (LLPS) and its interplay with aggregation have gained increasing interest. Previous work shows that factors promoting or inhibiting aggregation have similar effects on LLPS. This study provides a detailed scanning of a wide range of parameters, including protein, salt and crowding concentrations at multiple pH values, revealing different salt dependencies of aggregation and LLPS. The influence of salt on aggregation under crowding conditions follows a non-monotonic pattern, showing increased effects at medium salt concentrations. This behavior can be elucidated through a combination of electrostatic screening and salting-out effects on the intramolecular interactions between the N-terminal and C-terminal regions of αSyn. By contrast, this study finds a monotonic salt dependence of LLPS due to intermolecular interactions. Furthermore, it observes time evolution of the two distinct assembly states, with macroscopic fibrillar-like bundles initially forming at medium salt concentration but subsequently converting into droplets after prolonged incubation. The droplet state is therefore capable of inhibiting aggregation or even dissolving aggregates through heterotypic interactions, thus preventing αSyn from its dynamically arrested state.

TAAM refinement on high-resolution experimental and simulated 3D ED/MicroED data for organic molecules

3D electron diffraction (3D ED), or microcrystal electron diffraction (MicroED), has become an alternative technique for determining the high-resolution crystal structures of compounds from sub-micron-sized crystals. Here, we considered L-alanine, α-glycine and urea, which are known to form good-quality crystals, and collected high-resolution 3D ED data on our in-house TEM instrument. In this study, we present a comparison of independent atom model (IAM) and transferable aspherical atom model (TAAM) kinematical refinement against experimental and simulated data. TAAM refinement on both experimental and simulated data clearly improves the model fitting statistics (R factors and residual electrostatic potential) compared to IAM refinement. This shows that TAAM better represents the experimental electrostatic potential of organic crystals than IAM. Furthermore, we compared the geometrical parameters and atomic displacement parameters (ADPs) resulting from the experimental refinements with the simulated refinements, with the periodic density functional theory (DFT) calculations and with published X-ray and neutron crystal structures. The TAAM refinements on the 3D ED data did not improve the accuracy of the bond lengths between the non-H atoms. The experimental 3D ED data provided more accurate H-atom positions than the IAM refinements on the X-ray diffraction data. The IAM refinements against 3D ED data had a tendency to lead to slightly longer X-H bond lengths than TAAM, but the difference was statistically insignificant. Atomic displacement parameters were too large by tens of percent for L-alanine and α-glycine. Most probably, other unmodelled effects were causing this behaviour, such as radiation damage or dynamical scattering.

Phase Separation and Aggregation of α-Synuclein Diverge at Different Salt Conditions

The coacervation and structural rearrangement of the protein alpha-synuclein (αSyn) into cytotoxic oligomers and amyloid fibrils are considered pathological hallmarks of Parkinson's disease. While aggregation is recognized as the key element of amyloid diseases, liquid-liquid phase separation (LLPS) and its interplay with aggregation have gained increasing interest. Previous work showed that factors promoting or inhibiting amyloid formation have similar effects on phase separation. Here, we provide a detailed scanning of a wide range of parameters including protein, salt and crowding concentrations at multiple pH values, revealing different salt dependencies of aggregation and phase separation. The influence of salt on aggregation under crowded conditions follows a non-monotonic pattern, showing increased effects at medium salt concentrations. This behavior can be elucidated through a combination of electrostatic screening and salting-out effects on the intramolecular interactions between the N-terminal and C-terminal regions of αSyn. By contrast, we find a monotonic salt dependence of phase separation due to the intermolecular interaction. Furthermore, we observe the time evolution of the two distinct assembly states, with macroscopic fibrillar-like bundles initially forming at medium salt concentration but subsequently converting into droplets after prolonged incubation. The droplet state is therefore capable of inhibiting aggregation or even dissolving the aggregates through a variety of heterotypic interactions, thus preventing αSyn from its dynamically arrested state.

Systematic enhancement of protein crystallization efficiency by bulk lysine-to-arginine (KR) substitution

Structural genomics consortia established that protein crystallization is the primary obstacle to structure determination using x-ray crystallography. We previously demonstrated that crystallization propensity is systematically related to primary sequence, and we subsequently performed computational analyses showing that arginine is the most overrepresented amino acid in crystal-packing interfaces in the Protein Data Bank. Given the similar physicochemical characteristics of arginine and lysine, we hypothesized that multiple lysine-to-arginine (KR) substitutions should improve crystallization. To test this hypothesis, we developed software that ranks lysine sites in a target protein based on the redundancy-corrected KR substitution frequency in homologs. This software can be run interactively on the worldwide web at https://www.pxengineering.org/. We demonstrate that three unrelated single-domain proteins can tolerate 5-11 KR substitutions with at most minor destabilization, and, for two of these three proteins, the construct with the largest number of KR substitutions exhibits significantly enhanced crystallization propensity. This approach rapidly produced a 1.9 Å crystal structure of a human protein domain refractory to crystallization with its native sequence. Structures from Bulk KR-substituted domains show the engineered arginine residues frequently make hydrogen-bonds across crystal-packing interfaces. We thus demonstrate that Bulk KR substitution represents a rational and efficient method for probabilistic engineering of protein surface properties to improve crystallization.

20 years of crystal hits: progress and promise in ultrahigh-throughput crystallization screening

Diffraction-based structural methods contribute a large fraction of the biomolecular structural models available, providing a critical understanding of macromolecular architecture. These methods require crystallization of the target molecule, which remains a primary bottleneck in crystal-based structure determination. The National High-Throughput Crystallization Center at Hauptman-Woodward Medical Research Institute has focused on overcoming obstacles to crystallization through a combination of robotics-enabled high-throughput screening and advanced imaging to increase the success of finding crystallization conditions. This paper will describe the lessons learned from over 20 years of operation of our high-throughput crystallization services. The current experimental pipelines, instrumentation, imaging capabilities and software for image viewing and crystal scoring are detailed. New developments in the field and opportunities for further improvements in biomolecular crystallization are reflected on.

Self-Assembly of Tunable Intrinsically Disordered Peptide Amphiphiles

Intrinsically disordered peptide amphiphiles (IDPAs) present a novel class of synthetic conjugates that consist of short hydrophilic polypeptides anchored to hydrocarbon chains. These hybrid polymer-lipid block constructs spontaneously self-assemble into dispersed nanoscopic aggregates or ordered mesophases in aqueous solution due to hydrophobic interactions. Yet, the possible sequence variations and their influence on the self-assembly structures are vast and have hardly been explored. Here, we measure the nanoscopic self-assembled structures of four IDPA systems that differ by their amino acid sequence. We show that permutations in the charge pattern along the sequence remarkably alter the headgroup conformation and consequently alter the pH-triggered phase transitions between spherical, cylindrical micelles and hexagonal condensed phases. We demonstrate that even a single amino acid mutation is sufficient to tune structural transitions in the condensed IDPA mesophases, while peptide conformations remain unfolded and disordered. Furthermore, alteration of the peptide sequence can render IDPAs to become susceptible to enzymatic cleavage and induce enzymatically activated phase transitions. These results hold great potential for embedding multiple functionalities into lipid nanoparticle delivery systems by incorporating IDPAs with the desired properties.

Polymorphic protein phase transitions driven by surface anisotropy

Phase transitions of proteins are strongly influenced by surface chemical modifications or mutations. Human γD-crystallin (HGD) single-mutants have been extensively studied because they are associated with the onset of juvenile cataract. However, they have also provided a rich library of molecules to examine how specific inter-protein interactions direct protein assembly, providing new insights and valuable experimental data for coarse-grained patchy-particle models. Here, we demonstrate that the addition of new inter-protein interactions by mutagenesis is additive and increases the number and variety of condensed phases formed by proteins. When double mutations incorporating two specific single point mutations are made, the properties of both single mutations are retained in addition to the formation of a new condensed phase. We find that the HGD double-mutant P23VC110M self-assembles into spherical particles with retrograde solubility, orthorhombic crystals, and needle/plate shape crystals, while retaining the ability to undergo liquid-liquid phase separation. This rich polymorphism is only partially predicted by the experimental data on the constituent single mutants. We also report a previously un-characterized amorphous protein particle, with unique properties that differ from those of protein spherulites, protein particulates previously described. The particles we observe are amorphous, reversible with temperature, tens of microns in size, and perfectly spherical. When they are grown on pristine surfaces, they appear to form by homogeneous nucleation, making them unique, and we believe a new form of protein condensate. This work highlights the challenges in predicting protein behavior, which has frustrated rational assembly and crystallization but also provides rich data to develop new coarse-grained models to explain the observed polymorphism.

Machine learning-based protein crystal detection for monitoring of crystallization processes enabled with large-scale synthetic data sets of photorealistic images

Since preparative chromatography is a sustainability challenge due to large amounts of consumables used in downstream processing of biomolecules, protein crystallization offers a promising alternative as a purification method. While the limited crystallizability of proteins often restricts a broad application of crystallization as a purification method, advances in molecular biology, as well as computational methods are pushing the applicability towards integration in biotechnological downstream processes. However, in industrial and academic settings, monitoring protein crystallization processes non-invasively by microscopic photography and automated image evaluation remains a challenging problem. Recently, the identification of single crystal objects using deep learning has been the subject of increased attention for various model systems. However, the advancement of crystal detection using deep learning for biotechnological applications is limited: robust models obtained through supervised machine learning tasks require large-scale and high-quality data sets usually obtained in large projects through extensive manual labeling, an approach that is highly error-prone for dense systems of transparent crystals. For the first time, recent trends involving the use of synthetic data sets for supervised learning are transferred, thus generating photorealistic images of virtual protein crystals in suspension (PCS) through the use of ray tracing algorithms, accompanied by specialized data augmentations modelling experimental noise. Further, it is demonstrated that state-of-the-art models trained with the large-scale synthetic PCS data set outperform similar fine-tuned models based on the average precision metric on a validation data set, followed by experimental validation using high-resolution photomicrographs from stirred tank protein crystallization processes.

Purification and structural elucidation of a cobalamin-dependent radical SAM enzyme

The cobalamin (Cbl)-dependent radical S-adenosylmethionine (SAM) enzymes use a [4Fe-4S] cluster, SAM, and Cbl to carry out remarkable catalytic feats in a large number of biosynthetic pathways. However, despite the abundance of annotated Cbl-dependent radical SAM enzymes, relatively few molecular details exist regarding how these enzymes function. Traditionally, challenges associated with purifying and reconstituting Cbl-dependent radical SAM enzymes have hindered biochemical studies aimed at elucidating the structures and mechanisms of these enzymes. Herein, we describe a bottom-up approach that was used to crystallize OxsB, learn about the overall architecture of a Cbl-dependent radical SAM enzyme, and facilitate mechanistic studies. We report lessons learned from the crystallization of different states of OxsB, including the apo-, selenomethionine (SeMet)-labeled, and fully reconstituted form of OxsB that has a [4Fe-4S] cluster, SAM, and Cbl bound. Further, we suggest that, when appropriate, this bottom-up method can be used to facilitate studies on enzymes in this class for which there are challenges associated with purifying and reconstituting the active enzyme.

Microcrystal electron diffraction in macromolecular and pharmaceutical structure determination

Microcrystal electron diffraction (MicroED) has recently shown to be a promising technique for structure determination in structural biology and pharmaceutical chemistry. Here, we discuss the unique properties of electrons and motivate its use for diffraction experiments. We review the latest developments in MicroED, and illustrate its applications in macromolecular crystallography, fragment screening and structure guided drug discovery. We discuss the perspectives of MicroED in synthetic chemistry and pharmaceutical development. We anticipate that the rapid advances MicroED showcased here will promote further development of electron crystallography and open up new opportunities for drug discovery.

Application of ultraviolet, visible, and infrared light imaging in protein-based biopharmaceutical formulation characterization and development studies

Imaging is increasingly more utilized as analytical technology in biopharmaceutical formulation research, with applications ranging from subvisible particle characterization to thermal stability screening and residual moisture analysis. This review offers a comprehensive overview of analytical imaging for scientists active in biopharmaceutical formulation research and development, where it presents the unique information provided by the ultraviolet (UV), visible (Vis), and infrared (IR) sections in the electromagnetic spectrum. The main body of this review consists of an outline of UV, Vis, and IR imaging techniques for several (bio)physical properties that are commonly determined during protein-based biopharmaceutical formulation characterization and development studies. The review concludes with a future perspective of applied imaging within the field of biopharmaceutical formulation research.

MyD88 TIR domain higher-order assembly interactions revealed by microcrystal electron diffraction and serial femtosecond crystallography

MyD88 and MAL are Toll-like receptor (TLR) adaptors that signal to induce pro-inflammatory cytokine production. We previously observed that the TIR domain of MAL (MALTIR) forms filaments in vitro and induces formation of crystalline higher-order assemblies of the MyD88 TIR domain (MyD88TIR). These crystals are too small for conventional X-ray crystallography, but are ideally suited to structure determination by microcrystal electron diffraction (MicroED) and serial femtosecond crystallography (SFX). Here, we present MicroED and SFX structures of the MyD88TIR assembly, which reveal a two-stranded higher-order assembly arrangement of TIR domains analogous to that seen previously for MALTIR. We demonstrate via mutagenesis that the MyD88TIR assembly interfaces are critical for TLR4 signaling in vivo, and we show that MAL promotes unidirectional assembly of MyD88TIR. Collectively, our studies provide structural and mechanistic insight into TLR signal transduction and allow a direct comparison of the MicroED and SFX techniques.

Reactive electrically conducting membranes for phosphorus recovery from livestock wastewater effluents

We present a novel 'proof-of-concept' electrochemically based membrane filtration process for the recovery of nitrogen and phosphorus from livestock wastewater following an anaerobic digestion step. Reactive electrically conducting membranes are shown to precipitate and separate struvite, an eco-friendly fertilizer from synthetic livestock wastewater, resulting in the production of a solid fertilizer and a high-quality water stream, fit for irrigation. The recovery process is based on electrochemical hydrolysis and control of local pH in proximity to the surface of the membrane, and therefore, does not require chemical additives for pH adjustment. The system was assessed at varying concentrations of nitrogen and phosphorus corresponding to diluted and concentrated livestock wastewater (up to 1000 mg/L of N and P). Experimental results show up to 65% removal of phosphorus and nitrogen in the first 30 min of electrochemical filtration, and the precipitates were analytically confirmed to be struvite. In addition, the recovery process was shown efficient as it resulted in limited membrane fouling and flux reduction. Fouling and precipitation results were explained by a mathematical model describing the concentration of N, P, Mg ions in the presence of an external electric field. Accordingly, precipitation takes place in proximity to the membrane's surface but not directly on it, thus, limiting surface fouling. The electrochemical filtration system does not require chemical additives for pH adjustment, and the cost associated with electrochemical membrane-based struvite recovery was calculated to be $158 per ton of dry struvite, which is about 1.4 times lower in comparison to conventional recovery approaches. Overall, the electrochemical filtration system may be a promising alternative for nutrient recovery from livestock wastewater in terms of operational costs, recovery efficiency, and fouling mitigation.

Macromolecular crystallography using microcrystal electron diffraction

Microcrystal electron diffraction (MicroED) has recently emerged as a promising method for macromolecular structure determination in structural biology. Since the first protein structure was determined in 2013, the method has been evolving rapidly. Several protein structures have been determined and various studies indicate that MicroED is capable of (i) revealing atomic structures with charges, (ii) solving new protein structures by molecular replacement, (iii) visualizing ligand-binding interactions and (iv) determining membrane-protein structures from microcrystals embedded in lipidic mesophases. However, further development and optimization is required to make MicroED experiments more accurate and more accessible to the structural biology community. Here, we provide an overview of the current status of the field, and highlight the ongoing development, to provide an indication of where the field may be going in the coming years. We anticipate that MicroED will become a robust method for macromolecular structure determination, complementing existing methods in structural biology.

MicroED in natural product and small molecule research

Covering: 2013 to 2020The electron cryo-microscopy (cryo-EM) method Microcrystal Electron Diffraction (MicroED) allows the collection of high-resolution structural data from vanishingly small crystals that appear like amorphous powders or very fine needles. Since its debut in 2013, data collection and analysis schemes have been fine-tuned, and there are currently close to 100 structures determined by MicroED. Although originally developed to study proteins, MicroED is also very powerful for smaller systems, with some recent and very promising examples from the field of natural products. Herein, we review what has been achieved so far and provide examples of natural product structures, as well as demonstrate the expected future impact of MicroED to the field of natural product and small molecule research.

The Nuclear Matrix Protein SAFB Cooperates with Major Satellite RNAs to Stabilize Heterochromatin Architecture Partially through Phase Separation

Interphase chromatin is hierarchically organized into higher-order architectures that are essential for gene functions, yet the biomolecules that regulate these 3D architectures remain poorly understood. Here, we show that scaffold attachment factor B (SAFB), a nuclear matrix (NM)-associated protein with RNA-binding functions, modulates chromatin condensation and stabilizes heterochromatin foci in mouse cells. SAFB interacts via its R/G-rich region with heterochromatin-associated repeat transcripts such as major satellite RNAs, which promote the phase separation driven by SAFB. Depletion of SAFB leads to changes in 3D genome organization, including an increase in interchromosomal interactions adjacent to pericentromeric heterochromatin and a decrease in genomic compartmentalization, which could result from the decondensation of pericentromeric heterochromatin. Collectively, we reveal the integrated roles of NM-associated proteins and repeat RNAs in the 3D organization of heterochromatin, which may shed light on the molecular mechanisms of nuclear architecture organization.

Miniaturization of the Whole Process of Protein Crystallographic Analysis by a Microfluidic Droplet Robot: From Nanoliter-Scale Purified Proteins to Diffraction-Quality Crystals

To obtain diffraction-quality crystals is one of the largest barriers to analyze the protein structure using X-ray crystallography. Here we describe a microfluidic droplet robot that enables successful miniaturization of the whole process of crystallization experiments including large-scale initial crystallization screening, crystallization optimization, and crystal harvesting. The combination of the state-of-the-art droplet-based microfluidic technique with the microbatch crystallization mode dramatically reduces the volumes of droplet crystallization reactors to tens nanoliter range, allowing large-scale initial screening of 1536 crystallization conditions and multifactor crystallization condition optimization with extremely low protein consumption, and on-chip harvesting of diffraction-quality crystals directly from the droplet reactors. We applied the droplet robot in miniaturized crystallization experiments of seven soluble proteins and two membrane proteins, and on-chip crystal harvesting of six proteins. The X-ray diffraction data sets of these crystals were collected using synchrotron radiation for analyzing the structures with similar diffraction qualities as conventional crystallization methods.

Cinder: keeping crystallographers app-y

The process of producing suitable crystals for X-ray diffraction analysis most often involves the setting up of hundreds (or thousands) of individual crystallization trials, each of which must be repeatedly examined for crystals or hints of crystallinity. Currently, the only real way to address this bottleneck is to use an automated imager to capture images of the trials. However, the images still need to be assessed for crystals or other outcomes. Ideally, there would exist some rapid and reliable machine-analysis tool to translate the images into a quantitative result. However, as yet no such tool exists in wide usage, despite this being a well recognized problem. One of the issues in creating robust automatic image-analysis software is the lack of reliable data for training machine-learning algorithms. Here, a mobile application, Cinder, has been developed which allows crystallization images to be scored quickly on a smartphone or tablet. The Cinder scores are inserted into the appropriate table in a crystallization database and are immediately available to the user through a more sophisticated web interface, allowing more detailed analyses. A sharp increase in the number of scored images was observed after Cinder was released, which in turn provides more data for training machine-learning tools.

Application of Empirical Phase Diagrams for Multidimensional Data Visualization of High-Throughput Microbatch Crystallization Experiments

Protein phase diagrams are a tool to investigate the cause and consequence of solution conditions on protein phase behavior. The effects are scored according to aggregation morphologies such as crystals or amorphous precipitates. Solution conditions affect morphologic features, such as crystal size, as well as kinetic features, such as crystal growth time. Commonly used data visualization techniques include individual line graphs or phase diagrams based on symbols. These techniques have limitations in terms of handling large data sets, comprehensiveness or completeness. To eliminate these limitations, morphologic and kinetic features obtained from crystallization images generated with high throughput microbatch experiments have been visualized with radar charts in combination with the empirical phase diagram method. Morphologic features (crystal size, shape, and number, as well as precipitate size) and kinetic features (crystal and precipitate onset and growth time) are extracted for 768 solutions with varying chicken egg white lysozyme concentration, salt type, ionic strength, and pH. Image-based aggregation morphology and kinetic features were compiled into a single and easily interpretable figure, thereby showing that the empirical phase diagram method can support high-throughput crystallization experiments in its data amount as well as its data complexity.

The nucleation of protein crystals as a race against time with on- and off-pathways

High supersaturation levels are a necessary but insufficient condition for the crystallization of purified proteins. Unlike most small molecules, proteins can take diverse aggregation pathways that make the outcome of crystallization assays quite unpredictable. Here, dynamic light scattering and optical microscopy were used to show that the nucleation of lysozyme crystals is preceded by an initial step of protein oligomerization and by the progressive formation of metastable clusters. Because these steps deplete the concentration of soluble monomers, the probability of obtaining protein crystals decreases as time progresses. Stochastic variations of the induction time are thus amplified to a point where fast crystallization can coexist with unyielding regimes in the same conditions. With an initial hydrodynamic radius of ∼100 nm, the metastable clusters also promote the formation of protein crystals through a mechanism of heterogeneous nucleation. Crystal growth (on-pathway) takes place in parallel with cluster growth (off-pathway). The Janus-faced influence of the mesoscopic clusters is beneficial when it accelerates the formation of the first precrystalline nuclei and is detrimental as it depletes the solution of protein ready to crystallize. Choosing the right balance between the two effects is critical for determining the success of protein crystallization trials. The results presented here suggest that a mild oligomerization degree promotes the formation of a small number of metastable clusters which then catalyze the nucleation of well differentiated crystals.

MPI tray: a versatile crystallization plate for membrane proteins

High-throughput crystallization of biological macromolecules is usually performed on multi-well plates, the design of which needs to address different and sometimes conflicting requirements. In this regard, handling of membrane proteins presents a particular challenge owing to the common use of detergents with associated effects on surface tension. Reported here is the design of a new crystallization plate, termed the MPI tray, which is optimized for UV and visible imaging with membrane protein samples. Following basic considerations regarding geometry and material, the surface properties of the plate were subjected to extensive analysis and modification in order to improve the performance in a robotic environment. An electrostatic surface potential was identified as the major problem affecting the automated setup of experiments, and it was found that treatment of the crystallization plate with ethanol is effective in removing this potential.

The use of haptic interfaces and web services in crystallography: an application for a 'screen to beam' interface

Haptic interfaces have become common in consumer electronics. They enable easy interaction and information entry without the use of a mouse or keyboard. The work presented here illustrates the application of a haptic interface to crystallization screening in order to provide a natural means for visualizing and selecting results. By linking this to a cloud-based database and web-based application program interface, the same application shifts the approach from 'point and click' to 'touch and share', where results can be selected, annotated and discussed collaboratively. In the crystallographic application, given a suitable crystallization plate, beamline and robotic end effector, the resulting information can be used to close the loop between screening and X-ray analysis, allowing a direct and efficient 'screen to beam' approach. The application is not limited to the area of crystallization screening; 'touch and share' can be used by any information-rich scientific analysis and geographically distributed collaboration.

Minimal physical requirements for crystal growth self-poisoning

Self-poisoning is a kinetic trap that can impair or prevent crystal growth in a wide variety of physical settings. Here we use dynamic mean-field theory and computer simulation to argue that poisoning is ubiquitous because its emergence requires only the notion that a molecule can bind in two (or more) ways to a crystal; that those ways are not energetically equivalent; and that the associated binding events occur with sufficiently unequal probability. If these conditions are met then the steady-state growth rate is in general a non-monotonic function of the thermodynamic driving force for crystal growth, which is the characteristic of poisoning. Our results also indicate that relatively small changes of system parameters could be used to induce recovery from poisoning.

Computational crystallization

Crystallization is a key step in macromolecular structure determination by crystallography. While a robust theoretical treatment of the process is available, due to the complexity of the system, the experimental process is still largely one of trial and error. In this article, efforts in the field are discussed together with a theoretical underpinning using a solubility phase diagram. Prior knowledge has been used to develop tools that computationally predict the crystallization outcome and define mutational approaches that enhance the likelihood of crystallization. For the most part these tools are based on binary outcomes (crystal or no crystal), and the full information contained in an assembly of crystallization screening experiments is lost. The potential of this additional information is illustrated by examples where new biological knowledge can be obtained and where a target can be sub-categorized to predict which class of reagents provides the crystallization driving force. Computational analysis of crystallization requires complete and correctly formatted data. While massive crystallization screening efforts are under way, the data available from many of these studies are sparse. The potential for this data and the steps needed to realize this potential are discussed.

Analysis of crystallization data in the Protein Data Bank

The Protein Data Bank (PDB) is the largest available repository of solved protein structures and contains a wealth of information on successful crystallization. Many centres have used their own experimental data to draw conclusions about proteins and the conditions in which they crystallize. Here, data from the PDB were used to reanalyse some of these results. The most successful crystallization reagents were identified, the link between solution pH and the isoelectric point of the protein was investigated and the possibility of predicting whether a protein will crystallize was explored.

The detection and subsequent volume optimization of biological nanocrystals

Identifying and then optimizing initial crystallization conditions is a prerequisite for macromolecular structure determination by crystallography. Improved technologies enable data collection on crystals that are difficult if not impossible to detect using visible imaging. The application of second-order nonlinear imaging of chiral crystals and ultraviolet two-photon excited fluorescence detection is shown to be applicable in a high-throughput manner to rapidly verify the presence of nanocrystals in crystallization screening conditions. It is noted that the nanocrystals are rarely seen without also producing microcrystals from other chemical conditions. A crystal volume optimization method is described and associated with a phase diagram for crystallization.

Using isoelectric point to determine the pH for initial protein crystallization trials

Motivation: The identification of suitable conditions for crystallization is a rate-limiting step in protein structure determination. The pH of an experiment is an important parameter and has the potential to be used in data-mining studies to help reduce the number of crystallization trials required. However, the pH is usually recorded as that of the buffer solution, which can be highly inaccurate.

Results: Here, we show that a better estimate of the true pH can be predicted by considering not only the buffer pH but also any other chemicals in the crystallization solution. We use these more accurate pH values to investigate the disputed relationship between the pI of a protein and the pH at which it crystallizes.

Availability and implementation: Data used to generate models are available as Supplementary Material.

Contact:julie.wilson@york.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

Sparse and incomplete factorial matrices to screen membrane protein 2D crystallization

Electron crystallography is well suited for studying the structure of membrane proteins in their native lipid bilayer environment. This technique relies on electron cryomicroscopy of two-dimensional (2D) crystals, grown generally by reconstitution of purified membrane proteins into proteoliposomes under conditions favoring the formation of well-ordered lattices. Growing these crystals presents one of the major hurdles in the application of this technique. To identify conditions favoring crystallization a wide range of factors that can lead to a vast matrix of possible reagent combinations must be screened. However, in 2D crystallization these factors have traditionally been surveyed in a relatively limited fashion. To address this problem we carried out a detailed analysis of published 2D crystallization conditions for 12 β-barrel and 138 α-helical membrane proteins. From this analysis we identified the most successful conditions and applied them in the design of new sparse and incomplete factorial matrices to screen membrane protein 2D crystallization. Using these matrices we have run 19 crystallization screens for 16 different membrane proteins totaling over 1300 individual crystallization conditions. Six membrane proteins have yielded diffracting 2D crystals suitable for structure determination, indicating that these new matrices show promise to accelerate the success rate of membrane protein 2D crystallization.

A high-throughput colourimetric method for the determination of pH in crystallization screens

The crystallization of proteins is dependent on the careful control of numerous parameters, one of these being pH. The pH of crystallization is generally reported as that of the buffer; however, the true pH has been found to be as many as four pH units away. Measurement of pH with a meter is time-consuming and requires the reformatting of the crystallization solution. To overcome this, a high-throughput method for pH determination of buffered solutions has been developed with results comparable to those of a pH meter.

Identifying, studying and making good use of macromolecular crystals

As technology advances, the crystal volume that can be used to collect useful X-ray diffraction data decreases. The technologies available to detect and study growing crystals beyond the optical resolution limit and methods to successfully place the crystal into the X-ray beam are discussed.

Structural biology has contributed tremendous knowledge to the understanding of life on the molecular scale. The Protein Data Bank, a depository of this structural knowledge, currently contains over 100 000 protein structures, with the majority stemming from X-ray crystallography. As the name might suggest, crystallography requires crystals. As detectors become more sensitive and X-ray sources more intense, the notion of a crystal is gradually changing from one large enough to embellish expensive jewellery to objects that have external dimensions of the order of the wavelength of visible light. Identifying these crystals is a prerequisite to their study. This paper discusses developments in identifying these crystals during crystallization screening and distinguishing them from other potential outcomes. The practical aspects of ensuring that once a crystal is identified it can then be positioned in the X-ray beam for data collection are also addressed.

Crystallization screening: the influence of history on current practice

While crystallization historically predates crystallography, it is a critical step for the crystallographic process. The rich history of crystallization and how that history influences current practices is described. The tremendous impact of crystallization screens on the field is discussed.

Comparing chemistry to outcome: the development of a chemical distance metric, coupled with clustering and hierarchal visualization applied to macromolecular crystallography

Many bioscience fields employ high-throughput methods to screen multiple biochemical conditions. The analysis of these becomes tedious without a degree of automation. Crystallization, a rate limiting step in biological X-ray crystallography, is one of these fields. Screening of multiple potential crystallization conditions (cocktails) is the most effective method of probing a proteins phase diagram and guiding crystallization but the interpretation of results can be time-consuming. To aid this empirical approach a cocktail distance coefficient was developed to quantitatively compare macromolecule crystallization conditions and outcome. These coefficients were evaluated against an existing similarity metric developed for crystallization, the C6 metric, using both virtual crystallization screens and by comparison of two related 1,536-cocktail high-throughput crystallization screens. Hierarchical clustering was employed to visualize one of these screens and the crystallization results from an exopolyphosphatase-related protein from Bacteroides fragilis, (BfR192) overlaid on this clustering. This demonstrated a strong correlation between certain chemically related clusters and crystal lead conditions. While this analysis was not used to guide the initial crystallization optimization, it led to the re-evaluation of unexplained peaks in the electron density map of the protein and to the insertion and correct placement of sodium, potassium and phosphate atoms in the structure. With these in place, the resulting structure of the putative active site demonstrated features consistent with active sites of other phosphatases which are involved in binding the phosphoryl moieties of nucleotide triphosphates. The new distance coefficient, CD_coeff, appears to be robust in this application, and coupled with hierarchical clustering and the overlay of crystallization outcome, reveals information of biological relevance. While tested with a single example the potential applications related to crystallography appear promising and the distance coefficient, clustering, and hierarchal visualization of results undoubtedly have applications in wider fields.

Applications of the second virial coefficient: protein crystallization and solubility

This article begins by highlighting some of the ground-based studies emanating from NASA's Microgravity Protein Crystal Growth (PCG) program. This is followed by a more detailed discussion of the history of and the progress made in one of the NASA-funded PCG investigations involving the use of measured second virial coefficients (B values) as a diagnostic indicator of solution conditions conducive to protein crystallization. A second application of measured B values involves the determination of solution conditions that improve or maximize the solubility of aqueous and membrane proteins. These two important applications have led to several technological improvements that simplify the experimental expertise required, enable the measurement of membrane proteins and improve the diagnostic capability and measurement throughput.

Water in the formation of biogenic minerals: peeling away the hydration layers

Minerals of biogenic origin form and crystallize from aqueous environments at ambient temperatures and pressures. The in vivo environment either intracellular or intercellular, contains many components that modulate both the activity of the ions which associate to form the mineral, as well as the activity and structure of the crowded water. Most of the studies about the mechanism of mineralization, that is, the detailed pathways by which the mineral ions proceed from solution to crystal state, have been carried out in relatively dilute solutions and clean solutions. These studies have considered both thermodynamic and kinetic controls. Most have not considered the water itself. Is the water a passive bystander, or is it intimately a participant in the mineral ion densification reaction? A wide range of experiments show that the mineralization pathways proceed through a series of densification stages with intermediates, such as a "dense liquid" phase and the prenucleation clusters that form within it. This is in contrast to the idea of a single step phase transition, but consistent with the Gibbs concept of discontinuous phase transitions from supersaturated mother liquor to crystal. Further changes in the water structure at every surface and interface during densification guides the free energy trajectory leading to the crystalline state. In vertebrates, mineralization takes place in a hydrated collagen matrix, thus water must be considered as a direct participant. Although different in detail, the crystallization of calcium phosphates, as apatite, and calcium carbonates, as calcite, are mechanistically identical from the viewpoint of water.

Towards protein-crystal centering using second-harmonic generation (SHG) microscopy

The potential of second-harmonic generation (SHG) microscopy for automated crystal centering to guide synchrotron X-ray diffraction of protein crystals was explored. These studies included (i) comparison of microcrystal positions in cryoloops as determined by SHG imaging and by X-ray diffraction rastering and (ii) X-ray structure determinations of selected proteins to investigate the potential for laser-induced damage from SHG imaging. In studies using β2 adrenergic receptor membrane-protein crystals prepared in lipidic mesophase, the crystal locations identified by SHG images obtained in transmission mode were found to correlate well with the crystal locations identified by raster scanning using an X-ray minibeam. SHG imaging was found to provide about 2 µm spatial resolution and shorter image-acquisition times. The general insensitivity of SHG images to optical scatter enabled the reliable identification of microcrystals within opaque cryocooled lipidic mesophases that were not identified by conventional bright-field imaging. The potential impact of extended exposure of protein crystals to five times a typical imaging dose from an ultrafast laser source was also assessed. Measurements of myoglobin and thaumatin crystals resulted in no statistically significant differences between structures obtained from diffraction data acquired from exposed and unexposed regions of single crystals. Practical constraints for integrating SHG imaging into an active beamline for routine automated crystal centering are discussed.

A universal indicator dye pH assay for crystallization solutions and other high-throughput applications

In protein crystallization, as well as in many other fields, it is known that the pH at which experiments are performed is often the key factor in the success or failure of the trials. With the trend towards plate-based high-throughput experimental techniques, measuring the pH values of solutions one by one becomes prohibitively time- and reagent-expensive. As part of an HT crystallization facility, a colour-based pH assay that is rapid, uses very little reagent and is suitable for 96-well or higher density plates has been developed.

On the need for an international effort to capture, share and use crystallization screening data

Development of an ontology for the description of crystallization experiments and results is proposed.

When crystallization screening is conducted many outcomes are observed but typically the only trial recorded in the literature is the condition that yielded the crystal(s) used for subsequent diffraction studies. The initial hit that was optimized and the results of all the other trials are lost. These missing results contain information that would be useful for an improved general understanding of crystallization. This paper provides a report of a crystallization data exchange (XDX) workshop organized by several international large-scale crystallization screening laboratories to discuss how this information may be captured and utilized. A group that administers a significant fraction of the world’s crystallization screening results was convened, together with chemical and structural data informaticians and computational scientists who specialize in creating and analysing large disparate data sets. The development of a crystallization ontology for the crystallization community was proposed. This paper (by the attendees of the workshop) provides the thoughts and rationale leading to this conclusion. This is brought to the attention of the wider audience of crystallographers so that they are aware of these early efforts and can contribute to the process going forward.