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Fluctuation X-ray scattering (FXS) is an emerging experimental technique in which X-ray solution scattering data are collected from particles in solution using ultrashort X-ray exposures generated by a free-electron laser (FEL). FXS experiments overcome the low data-to-parameter ratios associated with traditional solution scattering measurements by providing several orders of magnitude more information in the final processed data. Here we demonstrate the practical feasibility of FEL-based FXS on a biological multiple-particle system and describe data-processing techniques required to extract robust FXS data and significantly reduce the required number of snapshots needed by introducing an iterative noise-filtering technique. We showcase a successful ab initio electron density reconstruction from such an experiment, studying the Paramecium bursaria Chlorella virus (PBCV-1).

Most of the dioxygen on earth is generated by the oxidation of water by photosystem II (PS II) using light from the sun. This light-driven, four-photon reaction is catalyzed by the Mn ₄CaO ₅ cluster located at the lumenal side of PS II. Various X-ray studies have been carried out at cryogenic temperatures to understand the intermediate steps involved in the water oxidation mechanism. However, the necessity for collecting data at room temperature, especially for studying the transient steps during the O–O bond formation, requires the development of new methodologies. In this paper we report room temperature X-ray diffraction data of PS II microcrystals obtained using ultrashort (< 50 fs) 9 keV X-ray pulses from a hard X-ray free electron laser, namely the Linac Coherent Light Source. The results presented here demonstrate that the ”probe before destroy” approach using an X-ray free electron laser works even for the highly-sensitive Mn ₄CaO ₅ cluster in PS II at room temperature. We show that these data are comparable to those obtained in synchrotron radiation studies as seen by the similarities in the overall structure of the helices, the protein subunits and the location of the various cofactors. This work is, therefore, an important step toward future studies for resolving the structure of the Mn ₄CaO ₅ cluster without any damage at room temperature, and of the reaction intermediates of PS II during O–O bond formation.

We propose the combination of k-means clustering with Gaussian Process (GP) regression in the analysis and exploration of 4D angle-resolved photoemission spectroscopy (ARPES) data. Using cluster labels as the driving metric on which the GP is trained, this method allows us to reconstruct the experimental phase diagram from as low as 12% of the original dataset size. In addition to the phase diagram, the GP is able to reconstruct spectra in energy-momentum space from this minimal set of data points. These findings suggest that this methodology can be used to improve the efficiency of ARPES data collection strategies for unknown samples. The practical feasibility of implementing this technology at a synchrotron beamline and the overall efficiency implications of this method are discussed with a view on enabling the collection of more samples or rapid identification of regions of interest.

X-ray scattering images collected on timescales shorter than rotation diffusion times using a (partially) coherent beam result in a significant increase in information content in the scattered data. These measurements, named fluctuation X-ray scattering (FXS), are typically performed on an X-ray free-electron laser (XFEL) and can provide fundamental insights into the structure of biological molecules, engineered nanoparticles or energy-related mesoscopic materials beyond what can be obtained with standard X-ray scattering techniques. In order to understand, use and validate experimental FXS data, the availability of basic data characteristics and operational properties is essential, but has been absent up to this point. In this communication, an intuitive view of the nature of FXS data and their properties is provided, the effect of FXS data on the derived structural models is highlighted, and generalizations of the Guinier and Porod laws that can ultimately be used to plan experiments and assess the quality of experimental data are presented.

The dioxygen we breathe is formed by light-induced oxidation of water in photosystem II. O 2 formation takes place at a catalytic manganese cluster within milliseconds after the photosystem II reaction centre is excited by three single-turnover flashes. Here we present combined X-ray emission spectra and diffraction data of 2-flash (2F) and 3-flash (3F) photosystem II samples, and of a transient 3F’ state (250 μs after the third flash), collected under functional conditions using an X-ray free electron laser. The spectra show that the initial O–O bond formation, coupled to Mn reduction, does not yet occur within 250 μs after the third flash. Diffraction data of all states studied exhibit an anomalous scattering signal from Mn but show no significant structural changes at the present resolution of 4.5 Å. This study represents the initial frames in a molecular movie of the structural changes during the catalytic reaction in photosystem II. Photosystem II is the biosynthetic machinery that allows the conversion of water to oxygen using light. Here, the authors combine X-ray emission and diffraction data to probe the structural changes that take place during photosystem II catalysis.

The bacterial metalloregulator IscR possesses the unusual ability to direct differential gene expression via specific recognition of two distinct operator motifs in an Fe-S–dependent manner. New work shows that Fe-S binding displaces a residue required for sequence discrimination at the DNA binding interface, revealing a conditional, ligand-mediated mechanism regulating sequence-specific recognition. IscR from Escherichia coli is an unusual metalloregulator in that both apo and iron sulfur (Fe-S)-IscR regulate transcription and exhibit different DNA binding specificities. Here, we report structural and biochemical studies of IscR suggesting that remodeling of the protein-DNA interface upon Fe-S ligation broadens the DNA binding specificity of IscR from binding the type 2 motif only to both type 1 and type 2 motifs. Analysis of an apo-IscR variant with relaxed target-site discrimination identified a key residue in wild-type apo-IscR that, we propose, makes unfavorable interactions with a type 1 motif. Upon Fe-S binding, these interactions are apparently removed, thereby allowing holo-IscR to bind both type 1 and type 2 motifs. These data suggest a unique mechanism of ligand-mediated DNA site recognition, whereby metallocluster ligation relocates a protein-specificity determinant to expand DNA target-site selection, allowing a broader transcriptomic response by holo-IscR.

The execution and analysis of complex experiments are challenged by the vast dimensionality of the underlying parameter spaces. Although an increase in data-acquisition rates should allow broader querying of the parameter space, the complexity of experiments and the subtle dependence of the model function on input parameters remains daunting owing to the sheer number of variables. New strategies for autonomous data acquisition are being developed, with one promising direction being the use of Gaussian process regression (GPR). GPR is a quick, non-parametric and robust approximation and uncertainty quantification method that can be applied directly to autonomous data acquisition. We review GPR-driven autonomous experimentation and illustrate its functionality using real-world examples from large experimental facilities in the USA and France. We introduce the basics of a GPR-driven autonomous loop with a focus on Gaussian processes, and then shift the focus to the infrastructure that needs to be built around GPR to create a closed loop. Finally, the case studies we discuss show that Gaussian-process-based autonomous data acquisition is a widely applicable method that can facilitate the optimal use of instruments and facilities by enabling the efficient acquisition of high-value datasets.Gaussian process regression (GPR) is a powerful, non-parametric and robust technique for uncertainty quantification and function approximation that can be applied to optimal and autonomous data acquisition. This Review introduces the basics of GPR and discusses several use cases from different fields.

Tripeptidyl peptidase II is an eukaryotic serine protease that forms huge, spindle-shaped homopolymeric complexes, whose building block is an enzymatically inactive dimer. Now a combination of cryo-EM and crystal structure analysis of Drosophila TPPII allows a view on dimer organization and polymer architecture assembly, as well as insight into the mechanism of activation. Tripeptidyl peptidase II (TPP II) is the largest known eukaryotic protease (6 MDa). It is believed to act downstream of the 26S proteasome, cleaving tripeptides from the N termini of longer peptides, and it is implicated in numerous cellular processes. Here we report the structure of Drosophila TPP II determined by a hybrid approach. We solved the structure of the dimer by X-ray crystallography and docked it into the three-dimensional map of the holocomplex, which we obtained by single-particle cryo–electron microscopy. The resulting structure reveals the compartmentalization of the active sites inside a system of chambers and suggests the existence of a molecular ruler determining the size of the cleavage products. Furthermore, the structure suggests a model for activation of TPP II involving the relocation of a flexible loop and a repositioning of the active-site serine, coupling it to holocomplex assembly and active-site sequestration.

A computational approach and software tool, cctbx.xfel, enables the determination of accurate macromolecular structure factors using a relatively small number of serial femtosecond crystallography diffraction snapshots. X-ray free-electron laser (XFEL) sources enable the use of crystallography to solve three-dimensional macromolecular structures under native conditions and without radiation damage. Results to date, however, have been limited by the challenge of deriving accurate Bragg intensities from a heterogeneous population of microcrystals, while at the same time modeling the X-ray spectrum and detector geometry. Here we present a computational approach designed to extract meaningful high-resolution signals from fewer diffraction measurements.

Fluctuation X-ray scattering (FXS) is an emerging experimental technique in which solution scattering data are collected using X-ray exposures below rotational diffusion times, resulting in angularly anisotropic X-ray snapshots that provide several orders of magnitude more information than traditional solution scattering data. Such experiments can be performed using the ultrashort X-ray pulses provided by a free-electron laser source, allowing one to collect a large number of diffraction patterns in a relatively short time. Here, we describe a test data set for FXS, obtained at the Linac Coherent Light Source, consisting of close to 100 000 multi-particle diffraction patterns originating from approximately 50 to 200 Paramecium Bursaria Chlorella virus particles per snapshot. In addition to the raw data, a selection of high-quality pre-processed diffraction patterns and a reference SAXS profile are provided.