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The Lysinibacillus sphaericus proteins Tpp49Aa1 and Cry48Aa1 can together act as a toxin toward the mosquito Culex quinquefasciatus and have potential use in biocontrol. Given that proteins with sequence homology to the individual proteins can have activity alone against other insect species, the structure of Tpp49Aa1 was solved in order to understand this protein more fully and inform the design of improved biopesticides. Tpp49Aa1 is naturally expressed as a crystalline inclusion within the host bacterium, and MHz serial femtosecond crystallography using the novel nanofocus option at an X-ray free electron laser allowed rapid and high-quality data collection to determine the structure of Tpp49Aa1 at 1.62 Å resolution. This revealed the packing of Tpp49Aa1 within these natural nanocrystals as a homodimer with a large intermolecular interface. Complementary experiments conducted at varied pH also enabled investigation of the early structural events leading up to the dissolution of natural Tpp49Aa1 crystals-a crucial step in its mechanism of action. To better understand the cooperation between the two proteins, assays were performed on a range of different mosquito cell lines using both individual proteins and mixtures of the two. Finally, bioassays demonstrated Tpp49Aa1/Cry48Aa1 susceptibility of Anopheles stephensi, Aedes albopictus, and Culex tarsalis larvae-substantially increasing the potential use of this binary toxin in mosquito control.
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Bacillaceae , Bacillus , Culex , Plaguicidas , Animales , Bacillaceae/química , Bacillaceae/metabolismo , Control de Mosquitos , Larva/metabolismoRESUMEN
The liquid-to-solid phase transition is a complex process that is difficult to investigate experimentally with sufficient spatial and temporal resolution. A key aspect of the transition is the formation of a critical seed of the crystalline phase in a supercooled liquid, that is, a liquid in a metastable state below the melting temperature. This stochastic process is commonly described within the framework of classical nucleation theory, but accurate tests of the theory in atomic and molecular liquids are challenging. Here, we employ femtosecond x-ray diffraction from microscopic liquid jets to study crystal nucleation in supercooled liquids of the rare gases argon and krypton. Our results provide stringent limits to the validity of classical nucleation theory in atomic liquids, and offer the long-sought possibility of testing nonclassical extensions of the theory.
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New synthetic hybrid materials and their increasing complexity have placed growing demands on crystal growth for single-crystal X-ray diffraction analysis. Unfortunately, not all chemical systems are conducive to the isolation of single crystals for traditional characterization. Here, small-molecule serial femtosecond crystallography (smSFX) at atomic resolution (0.833 Å) is employed to characterize microcrystalline silver n-alkanethiolates with various alkyl chain lengths at X-ray free electron laser facilities, resolving long-standing controversies regarding the atomic connectivity and odd-even effects of layer stacking. smSFX provides high-quality crystal structures directly from the powder of the true unknowns, a capability that is particularly useful for systems having notoriously small or defective crystals. We present crystal structures of silver n-butanethiolate (C4), silver n-hexanethiolate (C6), and silver n-nonanethiolate (C9). We show that an odd-even effect originates from the orientation of the terminal methyl group and its role in packing efficiency. We also propose a secondary odd-even effect involving multiple mosaic blocks in the crystals containing even-numbered chains, identified by selected-area electron diffraction measurements. We conclude with a discussion of the merits of the synthetic preparation for the preparation of microdiffraction specimens and compare the long-range order in these crystals to that of self-assembled monolayers.
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Femtosecond transient soft X-ray absorption spectroscopy (XAS) is a very promising technique that can be employed at X-ray free-electron lasers (FELs) to investigate out-of-equilibrium dynamics for material and energy research. Here, a dedicated setup for soft X-rays available at the Spectroscopy and Coherent Scattering (SCS) instrument at the European X-ray Free-Electron Laser (European XFEL) is presented. It consists of a beam-splitting off-axis zone plate (BOZ) used in transmission to create three copies of the incoming beam, which are used to measure the transmitted intensity through the excited and unexcited sample, as well as to monitor the incoming intensity. Since these three intensity signals are detected shot by shot and simultaneously, this setup allows normalized shot-by-shot analysis of the transmission. For photon detection, an imaging detector capable of recording up to 800 images at 4.5â MHz frame rate during the FEL burst is employed, and allows a photon-shot-noise-limited sensitivity to be approached. The setup and its capabilities are reviewed as well as the online and offline analysis tools provided to users.
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We apply ultrashort X-ray laser pulses to track optically excited structural dynamics of [Ir2(dimen)4]2+ molecules in solution. In our exploratory study we determine angular correlations in the scattered X-rays, which comprise a complex fingerprint of the ultrafast dynamics. Model-assisted analysis of the experimental correlation data allows us to elucidate various aspects of the photoinduced changes in the excited molecular ensembles. We unambiguously identify that in our experiment the photoinduced transition dipole moments in [Ir2(dimen)4]2+ molecules are oriented perpendicular to the Ir-Ir bond. The analysis also shows that the ground state conformer of [Ir2(dimen)4]2+ with a larger Ir-Ir distance is mostly responsible for the formation of the excited state. We also reveal that the ensemble of solute molecules can be characterized with a substantial structural heterogeneity due to solvent influence. The proposed X-ray correlation approach offers an alternative path for studies of ultrafast structural dynamics of molecular ensembles in the liquid and gas phases.
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Bimetallic catalysts can undergo segregation or redistribution of the metals driven by oxidizing and reducing environments. Bragg coherent diffraction imaging (BCDI) was used to relate displacement fields to compositional distributions in crystalline Pt-Rh alloy nanoparticles. Three-dimensional images of internal composition showed that the radial distribution of compositions reverses partially between the surface shell and the core when gas flow changes between O_{2} and H_{2}. Our observation suggests that the elemental segregation of nanoparticle catalysts should be highly active during heterogeneous catalysis and can be a controlling factor in synthesis of electrocatalysts. In addition, our study exemplifies applications of BCDI for in situ 3D imaging of internal equilibrium compositions in other bimetallic alloy nanoparticles.
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The main protease (Mpro) of SARS-CoV-2 is critical for viral function and a key drug target. Mpro is only active when reduced; turnover ceases upon oxidation but is restored by re-reduction. This suggests the system has evolved to survive periods in an oxidative environment, but the mechanism of this protection has not been confirmed. Here, we report a crystal structure of oxidized Mpro showing a disulfide bond between the active site cysteine, C145, and a distal cysteine, C117. Previous work proposed this disulfide provides the mechanism of protection from irreversible oxidation. Mpro forms an obligate homodimer, and the C117-C145 structure shows disruption of interactions bridging the dimer interface, implying a correlation between oxidation and dimerization. We confirm dimer stability is weakened in solution upon oxidation. Finally, we observe the protein's crystallization behavior is linked to its redox state. Oxidized Mpro spontaneously forms a distinct, more loosely packed lattice. Seeding with crystals of this lattice yields a structure with an oxidation pattern incorporating one cysteine-lysine-cysteine (SONOS) and two lysine-cysteine (NOS) bridges. These structures further our understanding of the oxidative regulation of Mpro and the crystallization conditions necessary to study this structurally.
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Dominio Catalítico , Proteasas 3C de Coronavirus , Cisteína , Disulfuros , Oxidación-Reducción , SARS-CoV-2 , Disulfuros/química , Disulfuros/metabolismo , SARS-CoV-2/metabolismo , SARS-CoV-2/química , Proteasas 3C de Coronavirus/metabolismo , Proteasas 3C de Coronavirus/química , Cisteína/química , Cisteína/metabolismo , Cristalografía por Rayos X , Humanos , Modelos Moleculares , Multimerización de Proteína , COVID-19/virologíaRESUMEN
The idea of using ultrashort X-ray pulses to obtain images of single proteins frozen in time has fascinated and inspired many. It was one of the arguments for building X-ray free-electron lasers. According to theory, the extremely intense pulses provide sufficient signal to dispense with using crystals as an amplifier, and the ultrashort pulse duration permits capturing the diffraction data before the sample inevitably explodes. This was first demonstrated on biological samples a decade ago on the giant mimivirus. Since then, a large collaboration has been pushing the limit of the smallest sample that can be imaged. The ability to capture snapshots on the timescale of atomic vibrations, while keeping the sample at room temperature, may allow probing the entire conformational phase space of macromolecules. Here we show the first observation of an X-ray diffraction pattern from a single protein, that of Escherichia coli GroEL which at 14 nm in diameter is the smallest biological sample ever imaged by X-rays, and demonstrate that the concept of diffraction before destruction extends to single proteins. From the pattern, it is possible to determine the approximate orientation of the protein. Our experiment demonstrates the feasibility of ultrafast imaging of single proteins, opening the way to single-molecule time-resolved studies on the femtosecond timescale.
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Spectroscopy and X-ray diffraction techniques encode ample information on investigated samples. The ability of rapidly and accurately extracting these enhances the means to steer the experiment, as well as the understanding of the underlying processes governing the experiment. It improves the efficiency of the experiment, and maximizes the scientific outcome. To address this, we introduce and validate three frameworks based on self-supervised learning which are capable of classifying 1D spectral curves using data transformations preserving the scientific content and only a small amount of data labeled by domain experts. In particular, in this work we focus on the identification of phase transitions in samples investigated by x-ray powder diffraction. We demonstrate that the three frameworks, based either on relational reasoning, contrastive learning, or a combination of the two, are capable of accurately identifying phase transitions. Furthermore, we discuss in detail the selection of data augmentation techniques, crucial to ensure that scientifically meaningful information is retained.
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Difracción de Rayos X , Transición de FaseRESUMEN
Regular arrangement of nanocrystalline domains can introduce interference effects which alter considerably the powder diffraction pattern. Role of nanocrystal alignment (local texture) and mutual positioning are different, with the latter much more effective in controlling the interference effect. While it is demonstrated that these effects are unlikely to be observed on a conventional laboratory instrument, coherence conditions available at modern synchrotron radiation beamlines might support further investigations of interference in systems made of very fine nanocrystals.
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Modelos Químicos , Modelos Moleculares , Nanoestructuras/química , Nanoestructuras/ultraestructura , Simulación por Computador , Tamaño de la Partícula , Dispersión de Radiación , Rayos XRESUMEN
X-ray crystallography has witnessed a massive development over the past decade, driven by large increases in the intensity and brightness of X-ray sources and enabled by employing high-frame-rate X-ray detectors. The analysis of large data sets is done via automatic algorithms that are vulnerable to imperfections in the detector and noise inherent with the detection process. By improving the model of the behaviour of the detector, data can be analysed more reliably and data storage costs can be significantly reduced. One major requirement is a software mask that identifies defective pixels in diffraction frames. This paper introduces a methodology and program based upon concepts of machine learning, called robust mask maker (RMM), for the generation of bad-pixel masks for large-area X-ray pixel detectors based on modern robust statistics. It is proposed to discriminate normally behaving pixels from abnormal pixels by analysing routine measurements made with and without X-ray illumination. Analysis software typically uses a Bragg peak finder to detect Bragg peaks and an indexing method to detect crystal lattices among those peaks. Without proper masking of the bad pixels, peak finding methods often confuse the abnormal values of bad pixels in a pattern with true Bragg peaks and flag such patterns as useful regardless, leading to storage of enormous uninformative data sets. Also, it is computationally very expensive for indexing methods to search for crystal lattices among false peaks and the solution may be biased. This paper shows how RMM vastly improves peak finders and prevents them from labelling bad pixels as Bragg peaks, by demonstrating its effectiveness on several serial crystallography data sets.
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[This corrects the article DOI: 10.1107/S2052252520012798.].
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SARS-CoV-2 papain-like protease (PLpro) covers multiple functions. Beside the cysteine-protease activity, facilitating cleavage of the viral polypeptide chain, PLpro has the additional and vital function of removing ubiquitin and ISG15 (Interferon-stimulated gene 15) from host-cell proteins to support coronaviruses in evading the host's innate immune responses. We identified three phenolic compounds bound to PLpro, preventing essential molecular interactions to ISG15 by screening a natural compound library. The compounds identified by X-ray screening and complexed to PLpro demonstrate clear inhibition of PLpro in a deISGylation activity assay. Two compounds exhibit distinct antiviral activity in Vero cell line assays and one inhibited a cytopathic effect in non-cytotoxic concentration ranges. In the context of increasing PLpro mutations in the evolving new variants of SARS-CoV-2, the natural compounds we identified may also reinstate the antiviral immune response processes of the host that are down-regulated in COVID-19 infections.
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Antivirales , Tratamiento Farmacológico de COVID-19 , Sitio Alostérico , Antivirales/farmacología , Proteasas Similares a la Papaína de Coronavirus , Humanos , Papaína/metabolismo , Péptido Hidrolasas/metabolismo , SARS-CoV-2RESUMEN
The imaging of active nanoparticles represents a milestone in decoding heterogeneous catalysts' dynamics. We report the facet-resolved, surface strain state of a single PtRh alloy nanoparticle on SrTiO3 determined by coherent x-ray diffraction imaging under catalytic reaction conditions. Density functional theory calculations allow us to correlate the facet surface strain state to its reaction environmentdependent chemical composition. We find that the initially Pt-terminated nanoparticle surface gets Rh-enriched under CO oxidation reaction conditions. The local composition is facet orientation dependent, and the Rh enrichment is nonreversible under subsequent CO reduction. Tracking facet-resolved strain and composition under operando conditions is crucial for a rational design of more efficient heterogeneous catalysts with tailored activity, selectivity, and lifetime.
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A peak-finding algorithm for serial crystallography (SX) data analysis based on the principle of 'robust statistics' has been developed. Methods which are statistically robust are generally more insensitive to any departures from model assumptions and are particularly effective when analysing mixtures of probability distributions. For example, these methods enable the discretization of data into a group comprising inliers (i.e. the background noise) and another group comprising outliers (i.e. Bragg peaks). Our robust statistics algorithm has two key advantages, which are demonstrated through testing using multiple SX data sets. First, it is relatively insensitive to the exact value of the input parameters and hence requires minimal optimization. This is critical for the algorithm to be able to run unsupervised, allowing for automated selection or 'vetoing' of SX diffraction data. Secondly, the processing of individual diffraction patterns can be easily parallelized. This means that it can analyse data from multiple detector modules simultaneously, making it ideally suited to real-time data processing. These characteristics mean that the robust peak finder (RPF) algorithm will be particularly beneficial for the new class of MHz X-ray free-electron laser sources, which generate large amounts of data in a short period of time.
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Second-order intensity interferometry was employed to study the spatial and temporal properties of the European X-ray Free-Electron Laser (EuXFEL). Measurements were performed at the soft x-ray Self-Amplified Spontaneous Emission (SASE3) undulator beamline at a photon energy of 1.2 keV in the Self-Amplified Spontaneous Emission (SASE) mode. Two high-power regimes of the SASE3 undulator settings, i.e., linear and quadratic undulator tapering at saturation, were studied in detail and compared with the linear gain regime. The statistical analysis showed an exceptionally high degree of spatial coherence up to 90% for the linear undulator tapering. Analysis of the measured data in spectral and spatial domains provided an average pulse duration of about 10 fs in our measurements. The obtained results will be valuable for the experiments requiring and exploiting short pulse duration and utilizing high coherence properties of the EuXFEL.
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The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous human suffering. To date, no effective drug is available to directly treat the disease. In a search for a drug against COVID-19, we have performed a high-throughput x-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (Mpro), which is essential for viral replication. In contrast to commonly applied x-ray fragment screening experiments with molecules of low complexity, our screen tested already-approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds that bind to Mpro In subsequent cell-based viral reduction assays, one peptidomimetic and six nonpeptidic compounds showed antiviral activity at nontoxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2.
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Sitio Alostérico , Antivirales/química , Dominio Catalítico , Proteasas 3C de Coronavirus/antagonistas & inhibidores , Proteasas 3C de Coronavirus/química , Desarrollo de Medicamentos , Inhibidores de Proteasas/química , SARS-CoV-2/enzimología , Animales , Antivirales/farmacología , Chlorocebus aethiops , Cristalografía por Rayos X , Evaluación Preclínica de Medicamentos , Inhibidores de Proteasas/farmacología , SARS-CoV-2/efectos de los fármacos , Células Vero , Replicación Viral/efectos de los fármacosRESUMEN
Here, we illustrate what happens inside the catalytic cleft of an enzyme when substrate or ligand binds on single-millisecond timescales. The initial phase of the enzymatic cycle is observed with near-atomic resolution using the most advanced X-ray source currently available: the European XFEL (EuXFEL). The high repetition rate of the EuXFEL combined with our mix-and-inject technology enables the initial phase of ceftriaxone binding to the Mycobacterium tuberculosis ß-lactamase to be followed using time-resolved crystallography in real time. It is shown how a diffusion coefficient in enzyme crystals can be derived directly from the X-ray data, enabling the determination of ligand and enzyme-ligand concentrations at any position in the crystal volume as a function of time. In addition, the structure of the irreversible inhibitor sulbactam bound to the enzyme at a 66â ms time delay after mixing is described. This demonstrates that the EuXFEL can be used as an important tool for biomedically relevant research.
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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.
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An improved analysis for single-particle imaging (SPI) experiments, using the limited data, is presented here. Results are based on a study of bacteriophage PR772 performed at the Atomic, Molecular and Optical Science instrument at the Linac Coherent Light Source as part of the SPI initiative. Existing methods were modified to cope with the shortcomings of the experimental data: inaccessibility of information from half of the detector and a small fraction of single hits. The general SPI analysis workflow was upgraded with the expectation-maximization based classification of diffraction patterns and mode decomposition on the final virus-structure determination step. The presented processing pipeline allowed us to determine the 3D structure of bacteriophage PR772 without symmetry constraints with a spatial resolution of 6.9â nm. The obtained resolution was limited by the scattering intensity during the experiment and the relatively small number of single hits.