Three-dimensional reconstruction of the giant mimivirus particle with an x-ray free-electron laser

Fluorescence intensity correlation imaging with high spatial resolution and elemental contrast using intense x-ray pulses

We theoretically investigate the fluorescence intensity correlation (FIC) of Ar clusters and Mo-doped iron oxide nanoparticles subjected to intense, femtosecond, and sub-femtosecond x-ray free-electron laser pulses for high-resolution and elemental contrast imaging. We present the FIC of K α and K α h emission in Ar clusters and discuss the impact of sample damage on retrieving high-resolution structural information and compare the obtained structural information with those from the coherent diffractive imaging (CDI) approach. We found that, while sub-femtosecond pulses will substantially benefit the CDI approach, few-femtosecond pulses may be sufficient for achieving high-resolution information with the FIC. Furthermore, we show that the fluorescence intensity correlation computed from the fluorescence of the Mo atoms in Mo-doped iron oxide nanoparticles can be used to image dopant distributions in the nonresonant regime.

Reconstruction of nanoscale particles from single-shot wide-angle free-electron-laser diffraction patterns with physics-informed neural networks

Single-shot wide-angle diffraction imaging is a widely used method to investigate the structure of noncrystallizing objects such as nanoclusters, large proteins, or even viruses. Its main advantage is that information about the three-dimensional structure of the object is already contained in a single image. This makes it useful for the reconstruction of fragile and nonreproducible particles without the need for tomographic measurements. However, currently there is no efficient numerical inversion algorithm available that is capable of determining the object's structure in real time. Neural networks, on the other hand, excel in image processing tasks suited for such purpose. Here we show how a physics-informed deep neural network can be used to reconstruct complete three-dimensional object models of uniform, convex particles on a voxel grid from single two-dimensional wide-angle scattering patterns. We demonstrate its universal reconstruction capabilities for silver nanoclusters, where the network uncovers novel geometric structures that reproduce the experimental scattering data with very high precision.

Limitations of Structural Insight into Ultrafast Melting of Solid Materials with X-ray Diffraction Imaging

In this work, we analyze the application of X-ray diffraction imaging techniques to follow ultrafast structural transitions in solid materials using the example of an X-ray pump–X-ray probe experiment with a single-crystal silicon performed at a Linac Coherent Light Source. Due to the spatially non-uniform profile of the X-ray beam, the diffractive signal recorded in this experiment included contributions from crystal parts experiencing different fluences from the peak fluence down to zero. With our theoretical model, we could identify specific processes contributing to the silicon melting in those crystal regions, i.e., the non-thermal and thermal melting whose occurrences depended on the locally absorbed X-ray doses. We then constructed the total volume-integrated signal by summing up the coherent signal contributions (amplitudes) from the various crystal regions and found that this significantly differed from the signals obtained for a few selected uniform fluence values, including the peak fluence. This shows that the diffraction imaging signal obtained for a structurally damaged material after an impact of a non-uniform X-ray pump pulse cannot be always interpreted as the material’s response to a pulse of a specific (e.g., peak) fluence as it is sometimes believed. This observation has to be taken into account in planning and interpreting future experiments investigating structural changes in materials with X-ray diffraction imaging.

Classification of diffraction patterns in single particle imaging experiments performed at x-ray free-electron lasers using a convolutional neural network

Single particle imaging (SPI) is a promising method of native structure determination, which has undergone fast progress with the development of x-ray free-electron lasers. Large amounts of data are collected during SPI experiments, driving the need for automated data analysis. The necessary data analysis pipeline has a number of steps including binary object classification (single versus non-single hits). Classification and object detection are areas where deep neural networks currently outperform other approaches. In this work, we use the fast object detector networks YOLOv2 and YOLOv3. By exploiting transfer learning, a moderate amount of data is sufficient to train the neural network. We demonstrate here that a convolutional neural network can be successfully used to classify data from SPI experiments. We compare the results of classification for the two different networks, with different depth and architecture, by applying them to the same SPI data with different data representation. The best results are obtained for diffracted intensity represented by color images on a linear scale using YOLOv2 for classification. It shows an accuracy of about 95% with precision and recall of about 50% and 60%, respectively, in comparison to manual data classification.

Single-Shot Coherent X-ray Imaging Instrument at PAL-XFEL

We developed a single-shot coherent X-ray imaging instrument at the hard X-ray beamline of the Pohang Accelerator Laboratory X-ray Free Electron Laser (PAL-XFEL). This experimental platform was established to conduct a variety of XFEL experiments, including coherent diffraction imaging (CDI), X-ray photon correlation spectroscopy (XPCS), and coherent X-ray scattering (CXS). Based on the forward-scattering geometry, this instrument utilizes a fixed-target method for sample delivery. It is well optimized for single-shot-based experiments in which one expects to observe the ultrafast phenomena of nanoparticles at picosecond temporal and nanometer spatial resolutions. In this paper, we introduce a single-shot coherent X-ray imaging instrument and report pump–probe coherent diffraction imaging (PPCDI) of Ag nanoparticles as an example of its applications.

Features and futures of X-ray free-electron lasers

Linear accelerator-based free-electron lasers (FELs) are the leading source of fully coherent X-rays with ultra-high peak powers and ultra-short pulse lengths. Current X-ray FEL facilities have proved their worth as useful tools for diverse scientific applications. In this paper, we present an overview of the features and future prospects of X-ray FELs, including the working principles and properties of X-ray FELs, the operational status of different FEL facilities worldwide, the applications supported by such facilities, and the current developments and outlook for X-ray FEL-based research.

High-Throughput 3D Ensemble Characterization of Individual Core-Shell Nanoparticles with X-ray Free Electron Laser Single-Particle Imaging

The structures as building blocks for designing functional nanomaterials have fueled the development of versatile nanoprobes to understand local structures of noncrystalline specimens. Progress in analyzing structures of individual specimens with atomic scale accuracy has been notable recently. In most cases, however, only a limited number of specimens are inspected lacking statistics to represent the systems with structural inhomogeneity. Here, by employing single-particle imaging with X-ray free electron lasers and algorithms for multiple-model 3D imaging, we succeeded in investigating several thousand specimens in a couple of hours and identified intrinsic heterogeneities with 3D structures. Quantitative analysis has unveiled 3D morphology, facet indices, and elastic strain. The 3D elastic energy distribution is further corroborated by molecular dynamics simulations to gain mechanical insight at the atomic level. This work establishes a route to high-throughput characterization of individual specimens in large ensembles, hence overcoming statistical deficiency while providing quantitative information at the nanoscale.

An encryption-decryption framework to validating single-particle imaging

We propose an encryption-decryption framework for validating diffraction intensity volumes reconstructed using single-particle imaging (SPI) with X-ray free-electron lasers (XFELs) when the ground truth volume is absent. This conceptual framework exploits each reconstructed volumes' ability to decipher latent variables (e.g. orientations) of unseen sentinel diffraction patterns. Using this framework, we quantify novel measures of orientation disconcurrence, inconsistency, and disagreement between the decryptions by two independently reconstructed volumes. We also study how these measures can be used to define data sufficiency and its relation to spatial resolution, and the practical consequences of focusing XFEL pulses to smaller foci. This conceptual framework overcomes critical ambiguities in using Fourier Shell Correlation (FSC) as a validation measure for SPI. Finally, we show how this encryption-decryption framework naturally leads to an information-theoretic reformulation of the resolving power of XFEL-SPI, which we hope will lead to principled frameworks for experiment and instrument design.

Selecting XFEL single-particle snapshots by geometric machine learning

A promising new route for structural biology is single-particle imaging with an X-ray Free-Electron Laser (XFEL). This method has the advantage that the samples do not require crystallization and can be examined at room temperature. However, high-resolution structures can only be obtained from a sufficiently large number of diffraction patterns of individual molecules, so-called single particles. Here, we present a method that allows for efficient identification of single particles in very large XFEL datasets, operates at low signal levels, and is tolerant to background. This method uses supervised Geometric Machine Learning (GML) to extract low-dimensional feature vectors from a training dataset, fuse test datasets into the feature space of training datasets, and separate the data into binary distributions of "single particles" and "non-single particles." As a proof of principle, we tested simulated and experimental datasets of the Coliphage PR772 virus. We created a training dataset and classified three types of test datasets: First, a noise-free simulated test dataset, which gave near perfect separation. Second, simulated test datasets that were modified to reflect different levels of photon counts and background noise. These modified datasets were used to quantify the predictive limits of our approach. Third, an experimental dataset collected at the Stanford Linear Accelerator Center. The single-particle identification for this experimental dataset was compared with previously published results and it was found that GML covers a wide photon-count range, outperforming other single-particle identification methods. Moreover, a major advantage of GML is its ability to retrieve single particles in the presence of structural variability.

Three-Dimensional Coherent Bragg Imaging of Rotating Nanoparticles

Bragg coherent diffraction imaging is a powerful strain imaging tool, often limited by beam-induced sample instability for small particles and high power densities. Here, we devise and validate an adapted diffraction volume assembly algorithm, capable of recovering three-dimensional datasets from particles undergoing uncontrolled and unknown rotations. We apply the method to gold nanoparticles which rotate under the influence of a focused coherent x-ray beam, retrieving their three-dimensional shapes and strain fields. The results show that the sample instability problem can be overcome, enabling the use of fourth generation synchrotron sources for Bragg coherent diffraction imaging to their full potential.

Fast reconstruction of single-shot wide-angle diffraction images through deep learning

Single-shot x-ray imaging of short-lived nanostructures such as clusters and nanoparticles near a phase transition or non-crystalizing objects such as large proteins and viruses is currently the most elegant method for characterizing their structure. Using hard x-ray radiation provides scattering images that encode two-dimensional projections, which can be combined to identify the full three-dimensional object structure from multiple identical samples. Wide-angle scattering using XUV or soft x-rays, despite yielding lower resolution, provides three-dimensional structural information in a single shot and has opened routes towards the characterization of non-reproducible objects in the gas phase. The retrieval of the structural information contained in wide-angle scattering images is highly non-trivial, and currently no efficient rigorous algorithm is known. Here we show that deep learning networks, trained with simulated scattering data, allow for fast and accurate reconstruction of shape and orientation of nanoparticles from experimental images. The gain in speed compared to conventional retrieval techniques opens the route for automated structure reconstruction algorithms capable of real-time discrimination and pre-identification of nanostructures in scattering experiments with high repetition rate—thus representing the enabling technology for fast femtosecond nanocrystallography.

An advanced workflow for single-particle imaging with the limited data at an X-ray free-electron laser

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 6.9 nm. The obtained resolution was limited by the scattering intensity during the experiment and the relatively small number of single hits.

Effect of radiation damage and illumination variability on signal-to-noise ratio in X-ray free-electron laser single-particle imaging

The deterioration of both the signal-to-noise ratio and the spatial resolution in the electron-density distribution reconstructed from diffraction intensities collected at different orientations of a sample is analysed theoretically with respect to the radiation damage to the sample and the variations in the X-ray intensities illuminating different copies of the sample. The simple analytical expressions and numerical estimates obtained for models of radiation damage and incident X-ray pulses may be helpful in planning X-ray free-electron laser (XFEL) imaging experiments and in analysis of experimental data. This approach to the analysis of partially coherent X-ray imaging configurations can potentially be used for analysis of other forms of imaging where the temporal behaviour of the sample and the incident intensity during exposure may affect the inverse problem of sample reconstruction.

Single-virus genomics and beyond

Viruses are extremely diverse and modulate important biological and ecological processes globally. However, much of viral diversity remains uncultured and yet to be discovered. Several powerful culture-independent tools, in particular metagenomics, have substantially advanced virus discovery. Among those tools is single-virus genomics, which yields sequenced reference genomes from individual sorted virus particles without the need for cultivation. This new method complements virus culturing and metagenomic approaches and its advantages include targeted investigation of specific virus groups and investigation of genomic microdiversity within viral populations. In this Review, we provide a brief history of single-virus genomics, outline how this emergent method has facilitated advances in virus ecology and discuss its current limitations and future potential. Finally, we address how this method may synergistically intersect with other single-virus and single-cell approaches.

Flash X-ray diffraction imaging in 3D: a proposed analysis pipeline

Modern Flash X-ray diffraction Imaging (FXI) acquires diffraction signals from single biomolecules at a high repetition rate from X-ray Free Electron Lasers (XFELs), easily obtaining millions of 2D diffraction patterns from a single experiment. Due to the stochastic nature of FXI experiments and the massive volumes of data, retrieving 3D electron densities from raw 2D diffraction patterns is a challenging and time-consuming task. We propose a semi-automatic data analysis pipeline for FXI experiments, which includes four steps: hit-finding and preliminary filtering, pattern classification, 3D Fourier reconstruction, and post-analysis. We also include a recently developed bootstrap methodology in the post-analysis step for uncertainty analysis and quality control. To achieve the best possible resolution, we further suggest using background subtraction, signal windowing, and convex optimization techniques when retrieving the Fourier phases in the post-analysis step. As an application example, we quantified the 3D electron structure of the PR772 virus using the proposed data analysis pipeline. The retrieved structure was above the detector edge resolution and clearly showed the pseudo-icosahedral capsid of the PR772.

Structural Heterogeneity in Single Particle Imaging Using X-ray Lasers

One of the challenges facing single particle imaging with ultrafast X-ray pulses is the structural heterogeneity of the sample to be imaged. For the method to succeed with weakly scattering samples, the diffracted images from a large number of individual proteins need to be averaged. The more the individual proteins differ in structure, the lower the achievable resolution in the final reconstructed image. We use molecular dynamics to simulate two globular proteins in vacuum, fully desolvated as well as with two different solvation layers, at various temperatures. We calculate the diffraction patterns based on the simulations and evaluate the noise in the averaged patterns arising from the structural differences and the surrounding water. Our simulations show that the presence of a minimal water coverage with an average 3 Å thickness will stabilize the protein, reducing the noise associated with structural heterogeneity, whereas additional water will generate more background noise.

Holography and Coherent Diffraction Imaging with Low-(30-250 eV) and High-(80-300 keV) Energy Electrons: History, Principles, and Recent Trends

In this paper, we present the theoretical background to electron scattering in an atomic potential and the differences between low- and high-energy electrons interacting with matter. We discuss several interferometric techniques that can be realized with low- and high-energy electrons and which can be applied to the imaging of non-crystalline samples and individual macromolecules, including in-line holography, point projection microscopy, off-axis holography, and coherent diffraction imaging. The advantages of using low- and high-energy electrons for particular experiments are examined, and experimental schemes for holography and coherent diffraction imaging are compared.

Perspectives on single particle imaging with x rays at the advent of high repetition rate x-ray free electron laser sources

X-ray free electron lasers (XFELs) now routinely produce millijoule level pulses of x-ray photons with tens of femtoseconds duration. Such x-ray intensities gave rise to the idea that weakly scattering particles-perhaps single biomolecules or viruses-could be investigated free of radiation damage. Here, we examine elements from the past decade of so-called single particle imaging with hard XFELs. We look at the progress made to date and identify some future possible directions for the field. In particular, we summarize the presently achieved resolutions as well as identifying the bottlenecks and enabling technologies to future resolution improvement, which in turn enables application to samples of scientific interest.

Coarse-Grained Diffraction Template Matching Model to Retrieve Multiconformational Models for Biomolecule Structures from Noisy Diffraction Patterns

Biomolecular imaging using X-ray free-electron lasers (XFELs) has been successfully applied to serial femtosecond crystallography. However, the application of single-particle analysis for structure determination using XFELs with 100 nm or smaller biomolecules has two practical problems: the incomplete diffraction data sets for reconstructing 3D assembled structures and the heterogeneous conformational states of samples. A new diffraction template matching method is thus presented here to retrieve a plausible 3D structural model based on single noisy target diffraction patterns, assuming candidate structures. Two concepts are introduced here: prompt candidate diffraction, generated by enhanced sampled coarse-grain (CG) candidate structures, and efficient molecular orientation searching for matching based on Bayesian optimization. A CG model-based diffraction-matching protocol is proposed that achieves a 100-fold speed increase compared to exhaustive diffraction matching using an all-atom model. The conditions that enable multiconformational analysis were also investigated by simulated diffraction data for various conformational states of chromatin and ribosomes. The proposed method can enable multiconformational analysis, with a structural resolution of at least 20 Å for 270-800 Å flexible biomolecules, in experimental single-particle structure analyses that employ XFELs.

Magnetic field-enhanced beam monitor for ionizing radiation

For the microwave cavity resonance spectroscopy based non-destructive beam monitor for ionizing radiation, an addition-which adapts the approach to conditions where only little ionization takes place due to, e.g., small ionization cross sections, low gas pressures, and low photon fluxes-is presented and demonstrated. In this experiment, a magnetic field with a strength of 57 ± 1 mT was used to extend the lifetime of the afterglow of an extreme ultraviolet-induced plasma by a factor of ∼5. Magnetic trapping is expected to be most successful in preventing the decay of ephemeral free electrons created by low-energy photons. Good agreement has been found between the experimental results and the decay rates calculated based on the ambipolar and classical collision diffusion models.

High-quality reconstruction of coherent modulation imaging using weak cascade modulators

Coherent modulation imaging (CMI) has been shown to be an effective lensless diffraction approach to imaging general extended samples with fast algorithmic convergence and high robustness to data imperfection. Being a single-shot technique, CMI holds a high potential for imaging dynamics with ultrafast pulses like the ones from free-electron lasers. In the reported work, strong modulators have been suggested for CMI to have the optimal performance, which may be an obstacle for the wide adoption of the method. Here we show that with our improved reconstruction algorithm the requirements on the modulation depth and feature size of a modulator can be relaxed. Furthermore, we demonstrate that when cascade configuration is used, the modulators can be even weaker while providing lower image errors in reconstruction than the case of a single modulator. Detailed numerical studies in both far-field and near-field experiment geometry are given via simulation. A relaxed requirement on modulators in CMI could pave the way for its wide use in biology and materials science.

Imaging plasma formation in isolated nanoparticles with ultrafast resonant scattering

We have recorded the diffraction patterns from individual xenon clusters irradiated with intense extreme ultraviolet pulses to investigate the influence of light-induced electronic changes on the scattering response. The clusters were irradiated with short wavelength pulses in the wavelength regime of different 4d inner-shell resonances of neutral and ionic xenon, resulting in distinctly different optical properties from areas in the clusters with lower or higher charge states. The data show the emergence of a transient structure with a spatial extension of tens of nanometers within the otherwise homogeneous sample. Simulations indicate that ionization and nanoplasma formation result in a light-induced outer shell in the cluster with a strongly altered refractive index. The presented resonant scattering approach enables imaging of ultrafast electron dynamics on their natural timescale.

Methods and application of coherent X-ray diffraction imaging of noncrystalline particles

Microscopic imaging techniques have been developed to visualize events occurring in biological cells. Coherent X-ray diffraction imaging is one of the techniques applicable to structural analyses of cells and organelles, which have never been crystallized. In the experiment, a single noncrystalline particle is illuminated by an X-ray beam with almost complete spatial coherence. The structure of the particle projected along the direction of the beam is, in principle, retrieved from a finely recorded diffraction pattern alone by using iterative phase-retrieval algorithms. Here, we describe fundamental theory and experimental methods of coherent X-ray diffraction imaging and the recent application in structural studies of noncrystalline specimens by using X-rays available at Super Photon Ring of 8-Gev and SPring-8 Angstrom Compact Free Electron Laser in Japan.

Characterizing crystalline defects in single nanoparticles from angular correlations of single-shot diffracted X-rays

Characterizing and controlling the uniformity of nanoparticles is crucial for their application in science and technology because crystalline defects in the nanoparticles strongly affect their unique properties. Recently, ultra-short and ultra-bright X-ray pulses provided by X-ray free-electron lasers (XFELs) opened up the possibility of structure determination of nanometre-scale matter with Å spatial resolution. However, it is often difficult to reconstruct the 3D structural information from single-shot X-ray diffraction patterns owing to the random orientation of the particles. This report proposes an analysis approach for characterizing defects in nanoparticles using wide-angle X-ray scattering (WAXS) data from free-flying single nanoparticles. The analysis method is based on the concept of correlated X-ray scattering, in which correlations of scattered X-ray are used to recover detailed structural information. WAXS experiments of xenon nanoparticles, or clusters, were conducted at an XFEL facility in Japan by using the SPring-8 Ångstrom compact free-electron laser (SACLA). Bragg spots in the recorded single-shot X-ray diffraction patterns showed clear angular correlations, which offered significant structural information on the nanoparticles. The experimental angular correlations were reproduced by numerical simulation in which kinematical theory of diffraction was combined with geometric calculations. We also explain the diffuse scattering intensity as being due to the stacking faults in the xenon clusters.

Single-particle imaging by x-ray free-electron lasers-How many snapshots are needed?

X-ray free-electron lasers (XFELs) open the possibility of obtaining diffraction information from a single biological macromolecule. This is because XFELs can generate extremely intense x-ray pulses that are so short that diffraction data can be collected before the sample is destroyed. By collecting a sufficient number of single-particle diffraction patterns, the three-dimensional electron density of a molecule can be reconstructed ab initio. The quality of the reconstruction depends largely on the number of patterns collected at the experiment. This paper provides an estimate of the number of diffraction patterns required to reconstruct the electron density at a targeted spatial resolution. This estimate is verified by simulations for realistic x-ray fluences, repetition rates, and experimental conditions available at modern XFELs. Employing the bacterial phytochrome as a model system, we demonstrate that sub-nanometer resolution is within reach.

Controlled beams of shock-frozen, isolated, biological and artificial nanoparticles

X-ray free-electron lasers promise diffractive imaging of single molecules and nanoparticles with atomic spatial resolution. This relies on the averaging of millions of diffraction patterns of identical particles, which should ideally be isolated in the gas phase and preserved in their native structure. Here, we demonstrated that polystyrene nanospheres and Cydia pomonella granulovirus can be transferred into the gas phase, isolated, and very quickly shock-frozen, i.e., cooled to 4 K within microseconds in a helium-buffer-gas cell, much faster than state-of-the-art approaches. Nanoparticle beams emerging from the cell were characterized using particle-localization microscopy with light-sheet illumination, which allowed for the full reconstruction of the particle beams, focused to < 100   μ m , as well as for the determination of particle flux and number density. The experimental results were quantitatively reproduced and rationalized through particle-trajectory simulations. We propose an optimized setup with cooling rates for particles of few-nanometers on nanosecond timescales. The produced beams of shock-frozen isolated nanoparticles provide a breakthrough in sample delivery, e.g., for diffractive imaging and microscopy or low-temperature nanoscience.

Parameter optimization for 3D-reconstruction from XFEL diffraction patterns based on Fourier slice matching

Single-particle analysis (SPA) by X-ray free electron laser (XFEL) is a novel method that can observe biomolecules and living tissue that are difficult to crystallize in a state close to nature. To reconstruct three-dimensional (3D) molecular structure from two-dimensional (2D) XFEL diffraction patterns, we have to estimate the incident beam angle to the molecule for each pattern to assemble the 3D-diffraction intensity distribution using interpolation, and retrieve the phase information. In this study, we investigated the optimal parameter sets to assemble the 3D-diffraction intensity distribution from simulated 2D-diffraction patterns of ribosome. In particular, we examined how the parameters need to be adjusted for diffraction patterns with different binning sizes and beam intensities to obtain the highest resolution of molecular structure phase retrieved from the 3D-diffraction intensity. We found that resolution of restored molecular structure is sensitive to the interpolation parameters. Using the optimal parameter set, a linear oversampling ratio of around four is found to be sufficient for correct angle estimation and phase retrieval from the diffraction patterns of SPA by XFEL.

The role of transient resonances for ultra-fast imaging of single sucrose nanoclusters

Intense x-ray free-electron laser (XFEL) pulses hold great promise for imaging function in nanoscale and biological systems with atomic resolution. So far, however, the spatial resolution obtained from single shot experiments lags averaging static experiments. Here we report on a combined computational and experimental study about ultrafast diffractive imaging of sucrose clusters which are benchmark organic samples. Our theoretical model matches the experimental data from the water window to the keV x-ray regime. The large-scale dynamic scattering calculations reveal that transient phenomena driven by non-linear x-ray interaction are decisive for ultrafast imaging applications. Our study illuminates the complex interplay of the imaging process with the rapidly changing transient electronic structures in XFEL experiments and shows how computational models allow optimization of the parameters for ultrafast imaging experiments.

X-ray free electron lasers provide high photon flux to explore single particle diffraction imaging of biological samples. Here the authors present dynamic electronic structure calculations and benchmark them to single-particle XFEL diffraction data of sucrose clusters to predict optimal single-shot imaging conditions.

Characterizing the intrinsic properties of individual XFEL pulses via single-particle diffraction

With each single X-ray pulse having its own characteristics, understanding the individual property of each X-ray free-electron laser (XFEL) pulse is essential for its applications in probing and manipulating specimens as well as in diagnosing the lasing performance. Intensive research using XFEL radiation over the last several years has introduced techniques to characterize the femtosecond XFEL pulses, but a simple characterization scheme, while not requiring ad hoc assumptions, to address multiple aspects of XFEL radiation via a single data collection process is scant. Here, it is shown that single-particle diffraction patterns collected using single XFEL pulses can provide information about the incident photon flux and coherence property simultaneously, and the X-ray beam profile is inferred. The proposed scheme is highly adaptable to most experimental configurations, and will become an essential approach to understanding single X-ray pulses.

Low-signal limit of X-ray single particle diffractive imaging

An outstanding question in X-ray single particle imaging experiments has been the feasibility of imaging sub 10-nm-sized biomolecules under realistic experimental conditions where very few photons are expected to be measured in a single snapshot and instrument background may be significant relative to particle scattering. While analyses of simulated data have shown that the determination of an average image should be feasible using Bayesian methods such as the EMC algorithm, this has yet to be demonstrated using experimental data containing realistic non-isotropic instrument background, sample variability and other experimental factors. In this work, we show that the orientation and phase retrieval steps work at photon counts diluted to the signal levels one expects from smaller molecules or with weaker pulses, using data from experimental measurements of 60-nm PR772 viruses. Even when the signal is reduced to a fraction as little as 1/256, the virus electron density determined using ab initio phasing is of almost the same quality as the high-signal data. However, we are still limited by the total number of patterns collected, which may soon be mitigated by the advent of high repetition-rate sources like the European XFEL and LCLS-II.

Light-sheet imaging for the recording of transverse absolute density distributions of gas-phase particle-beams from nanoparticle injectors

Imaging biological molecules in the gas-phase requires novel sample delivery methods, which generally have to be characterized and optimized to produce high-density particle beams. A non-destructive characterization method of the transverse particle beam profile is presented. It enables the characterization of the particle beam in parallel to the collection of, for instance, x-ray-diffraction patterns. As a rather simple experimental method, it requires the generation of a small laser-light sheet using a cylindrical telescope and a microscope. The working principle of this technique was demonstrated for the characterization of the fluid-dynamic-focusing behavior of 220 nm polystyrene beads as prototypical nanoparticles. The particle flux was determined and the velocity distribution was calibrated using Mie-scattering calculations.

Characterization of X-ray diffraction intensity function from a biological molecule for single particle imaging

An attainable structural resolution of single particle imaging is determined by the characteristics of X-ray diffraction intensity, which depend on the incident X-ray intensity density and molecule size. To estimate the attainable structural resolution even for molecules whose coordinates are unknown, this research aimed to clarify how these characteristics of X-ray diffraction intensity are determined from the structure of a molecule. The functional characteristics of X-ray diffraction intensity of a single biomolecule were theoretically and computationally evaluated. The wavenumber dependence of the average diffraction intensity on a sphere of constant wavenumber was observable by small-angle X-ray solution scattering. An excellent approximation was obtained, in which this quantity was expressed by an integral transform of the product of the external molecular shape and a universal function related to its atom packing. A standard model protein was defined by an analytical form of the first factor characterized by molecular volume and length. It estimated the numerically determined wavenumber dependence with a worst-case error of approximately a factor of five. The distribution of the diffraction intensity on a sphere of constant wavenumber was also examined. Finally, the correlation of diffraction intensities in the wavenumber space was assessed. This analysis enabled the estimation of an attainable structural resolution as a function of the incident X-ray intensity density and the volume and length of a target molecule, even in the absence of molecular coordinates.

Virus Structures by X-Ray Free-Electron Lasers

Until recently X-ray crystallography has been the standard technique for virus structure determinations. Available X-ray sources have continuously improved over the decades, leading to the realization of X-ray free-electron lasers (XFELs). They provide high-intensity femtosecond X-ray pulses, which allow for new kinds of experiments by making use of the diffraction-before-destruction principle. By overcoming classical dose constraints, they at least in principle allow researchers to perform X-ray virus structure determination for single particles at room temperature. Simultaneously, the availability of XFELs led to the development of the method of serial femtosecond crystallography, where a crystal structure is determined from the measurement of hundreds to thousands of microcrystals. In the case of virus crystallography this method does not require freezing of the crystals and allows researchers to perform experiments under non-equilibrium conditions (e.g., by laser-induced temperature jumps or rapid chemical mixing), which is currently not possible with electron microscopy.

Photo-ionization and fragmentation of Sc3N@C80 following excitation above the Sc K-edge

We have investigated the ionization and fragmentation of a metallo-endohedral fullerene, Sc₃N@C₈₀, using ultrashort (10 fs) x-ray pulses. Following selective ionization of a Sc (1s) electron (hν = 4.55 keV), an Auger cascade leads predominantly to either a vibrationally cold multiply charged parent molecule or multifragmentation of the carbon cage following a phase transition. In contrast to previous studies, no intermediate regime of C₂ evaporation from the carbon cage is observed. A time-delayed, hard x-ray pulse (hν = 5.0 keV) was used to attempt to probe the electron transfer dynamics between the encapsulated Sc species and the carbon cage. A small but significant change in the intensity of Sc-containing fragment ions and coincidence counts for a delay of 100 fs compared to 0 fs, as well as an increase in the yield of small carbon fragment ions, may be indicative of incomplete charge transfer from the carbon cage on the sub-100 fs time scale.

Deep neural networks for classifying complex features in diffraction images

Intense short-wavelength pulses from free-electron lasers and high-harmonic-generation sources enable diffractive imaging of individual nanosized objects with a single x-ray laser shot. The enormous data sets with up to several million diffraction patterns present a severe problem for data analysis because of the high dimensionality of imaging data. Feature recognition and selection is a crucial step to reduce the dimensionality. Usually, custom-made algorithms are developed at a considerable effort to approximate the particular features connected to an individual specimen, but because they face different experimental conditions, these approaches do not generalize well. On the other hand, deep neural networks are the principal instrument for today's revolution in automated image recognition, a development that has not been adapted to its full potential for data analysis in science. We recently published [Langbehn et al., Phys. Rev. Lett. 121, 255301 (2018)PRLTAO0031-900710.1103/PhysRevLett.121.255301] the application of a deep neural network as a feature extractor for wide-angle diffraction images of helium nanodroplets. Here we present the setup, our modifications, and the training process of the deep neural network for diffraction image classification and its systematic bench marking. We find that deep neural networks significantly outperform previous attempts for sorting and classifying complex diffraction patterns and are a significant improvement for the much-needed assistance during postprocessing of large amounts of experimental coherent diffraction imaging data.

Nanometre-sized droplets from a gas dynamic virtual nozzle

This paper reports on improved techniques to create and characterize nanometre-sized droplets from dilute aqueous solutions by using a gas dynamic virtual nozzle (GDVN). It describes a method to measure the size distribution of uncharged droplets, using an environmental scanning electron microscope, and provides theoretical models for the droplet sizes created. The results show that droplet sizes can be tuned by adjusting the gas and liquid flow rates in the GDVN, and at the lowest liquid flow rates, the size of the water droplets peaks at about 120 nm. This droplet size is similar to droplet sizes produced by electrospray ionization but requires neither electrolytes nor charging of the solution. The results presented here identify a new operational regime for GDVNs and show that predictable droplet sizes, comparable to those obtained by electrospray ionization, can be produced by purely mechanical means in GDVNs.

Plasma channel formation in NIR laser-irradiated carrier gas from an aerosol nanoparticle injector

Aerosol nanoparticle injectors are fundamentally important for experiments where container-free sample handling is needed to study isolated nanoparticles. The injector consists of a nebuliser, a differential pumping unit, and an aerodynamic lens to create and deliver a focused particle beam to the interaction point inside a vacuum chamber. The tightest focus of the particle beam is close to the injector tip. The density of the focusing carrier gas is high at this point. We show here how this gas interacts with a near infrared laser pulse (800 nm wavelength, 120 fs pulse duration) at intensities approaching 1016 Wcm-2. We observe acceleration of gas ions to kinetic energies of 100s eV and study their energies as a function of the carrier gas density. Our results indicate that field ionisation by the intense near-infrared laser pulse opens up a plasma channel behind the laser pulse. The observations can be understood in terms of a Coulomb explosion of the created underdense plasma channel. The results can be used to estimate gas background in experiments with the injector and they open up opportunities for a new class of studies on electron and ion dynamics in nanoparticles surrounded by a low-density gas.

X-Ray Free-Electron Lasers for the Structure and Dynamics of Macromolecules

X-ray free-electron lasers provide femtosecond-duration pulses of hard X-rays with a peak brightness approximately one billion times greater than is available at synchrotron radiation facilities. One motivation for the development of such X-ray sources was the proposal to obtain structures of macromolecules, macromolecular complexes, and virus particles, without the need for crystallization, through diffraction measurements of single noncrystalline objects. Initial explorations of this idea and of outrunning radiation damage with femtosecond pulses led to the development of serial crystallography and the ability to obtain high-resolution structures of small crystals without the need for cryogenic cooling. This technique allows the understanding of conformational dynamics and enzymatics and the resolution of intermediate states in reactions over timescales of 100 fs to minutes. The promise of more photons per atom recorded in a diffraction pattern than electrons per atom contributing to an electron micrograph may enable diffraction measurements of single molecules, although challenges remain.

Complex Membrane Remodeling during Virion Assembly of the 30,000-Year-Old Mollivirus Sibericum

Cellular membranes ensure functional compartmentalization by dynamic fusion-fission remodeling and are often targeted by viruses during entry, replication, assembly, and egress. Nucleocytoplasmic large DNA viruses (NCLDVs) can recruit host-derived open membrane precursors to form their inner viral membrane. Using complementary three-dimensional (3D)-electron microscopy techniques, including focused-ion beam scanning electron microscopy and electron tomography, we show that the giant Mollivirus sibericum utilizes the same strategy but also displays unique features. Indeed, assembly is specifically triggered by an open cisterna with a flat pole in its center and open curling ends that grow by recruitment of vesicles never reported for NCLDVs. These vesicles, abundant in the viral factory (VF), are initially closed but open once in close proximity to the open curling ends of the growing viral membrane. The flat pole appears to play a central role during the entire virus assembly process. While additional capsid layers are assembled from it, it also shapes the growing cisterna into immature crescent-like virions and is located opposite to the membrane elongation and closure sites, thereby providing virions with a polarity. In the VF, DNA-associated filaments are abundant, and DNA is packed within virions prior to particle closure. Altogether, our results highlight the complexity of the interaction between giant viruses and their host. Mollivirus assembly relies on the general strategy of vesicle recruitment, opening, and shaping by capsid layers similar to all NCLDVs studied until now. However, the specific features of its assembly suggest that the molecular mechanisms for cellular membrane remodeling and persistence are unique.IMPORTANCE Since the first giant virus Mimivirus was identified, other giant representatives are isolated regularly around the world and appear to be unique in several aspects. They belong to at least four viral families, and the ways they interact with their hosts remain poorly understood. We focused on Mollivirus sibericum, the sole representative of "Molliviridae," which was isolated from a 30,000-year-old permafrost sample and exhibits spherical virions of complex composition. In particular, we show that (i) assembly is initiated by a unique structure containing a flat pole positioned at the center of an open cisterna, (ii) core packing involves another cisterna-like element seemingly pushing core proteins into particles being assembled, and (iii) specific filamentous structures contain the viral genome before packaging. Altogether, our findings increase our understanding of how complex giant viruses interact with their host and provide the foundation for future studies to elucidate the molecular mechanisms of Mollivirus assembly.

Coherent diffractive imaging of microtubules using an X-ray laser

X-ray free electron lasers (XFELs) create new possibilities for structural studies of biological objects that extend beyond what is possible with synchrotron radiation. Serial femtosecond crystallography has allowed high-resolution structures to be determined from micro-meter sized crystals, whereas single particle coherent X-ray imaging requires development to extend the resolution beyond a few tens of nanometers. Here we describe an intermediate approach: the XFEL imaging of biological assemblies with helical symmetry. We collected X-ray scattering images from samples of microtubules injected across an XFEL beam using a liquid microjet, sorted these images into class averages, merged these data into a diffraction pattern extending to 2 nm resolution, and reconstructed these data into a projection image of the microtubule. Details such as the 4 nm tubulin monomer became visible in this reconstruction. These results illustrate the potential of single-molecule X-ray imaging of biological assembles with helical symmetry at room temperature.

The Single Particles, Clusters and Biomolecules and Serial Femtosecond Crystallography instrument of the European XFEL: initial installation

The European X-ray Free-Electron Laser (FEL) became the first operational high-repetition-rate hard X-ray FEL with first lasing in May 2017. Biological structure determination has already benefitted from the unique properties and capabilities of X-ray FELs, predominantly through the development and application of serial crystallography. The possibility of now performing such experiments at data rates more than an order of magnitude greater than previous X-ray FELs enables not only a higher rate of discovery but also new classes of experiments previously not feasible at lower data rates. One example is time-resolved experiments requiring a higher number of time steps for interpretation, or structure determination from samples with low hit rates in conventional X-ray FEL serial crystallography. Following first lasing at the European XFEL, initial commissioning and operation occurred at two scientific instruments, one of which is the Single Particles, Clusters and Biomolecules and Serial Femtosecond Crystallography (SPB/SFX) instrument. This instrument provides a photon energy range, focal spot sizes and diagnostic tools necessary for structure determination of biological specimens. The instrumentation explicitly addresses serial crystallography and the developing single particle imaging method as well as other forward-scattering and diffraction techniques. This paper describes the major science cases of SPB/SFX and its initial instrumentation - in particular its optical systems, available sample delivery methods, 2D detectors, supporting optical laser systems and key diagnostic components. The present capabilities of the instrument will be reviewed and a brief outlook of its future capabilities is also described.

Electrospray sample injection for single-particle imaging with x-ray lasers

The possibility of imaging single proteins constitutes an exciting challenge for x-ray lasers. Despite encouraging results on large particles, imaging small particles has proven to be difficult for two reasons: not quite high enough pulse intensity from currently available x-ray lasers and, as we demonstrate here, contamination of the aerosolized molecules by nonvolatile contaminants in the solution. The amount of contamination on the sample depends on the initial droplet size during aerosolization. Here, we show that, with our electrospray injector, we can decrease the size of aerosol droplets and demonstrate virtually contaminant-free sample delivery of organelles, small virions, and proteins. The results presented here, together with the increased performance of next-generation x-ray lasers, constitute an important stepping stone toward the ultimate goal of protein structure determination from imaging at room temperature and high temporal resolution.

Experimental 3D coherent diffractive imaging from photon-sparse random projections

The routine atomic resolution structure determination of single particles is expected to have profound implications for probing structure-function relationships in systems ranging from energy-storage materials to biological molecules. Extremely bright ultrashort-pulse X-ray sources - X-ray free-electron lasers (XFELs) - provide X-rays that can be used to probe ensembles of nearly identical nanoscale particles. When combined with coherent diffractive imaging, these objects can be imaged; however, as the resolution of the images approaches the atomic scale, the measured data are increasingly difficult to obtain and, during an X-ray pulse, the number of photons incident on the 2D detector is much smaller than the number of pixels. This latter concern, the signal 'sparsity', materially impedes the application of the method. An experimental analog using a conventional X-ray source is demonstrated and yields signal levels comparable with those expected from single biomolecules illuminated by focused XFEL pulses. The analog experiment provides an invaluable cross check on the fidelity of the reconstructed data that is not available during XFEL experiments. Using these experimental data, it is established that a sparsity of order 1.3 × 10-3 photons per pixel per frame can be overcome, lending vital insight to the solution of the atomic resolution XFEL single-particle imaging problem by experimentally demonstrating 3D coherent diffractive imaging from photon-sparse random projections.

Native mass spectrometry provides sufficient ion flux for XFEL single-particle imaging

The SPB/SFX instrument at the European XFEL provides unique conditions for single-particle imaging (SPI) experiments due to its high brilliance, nano-focus and unique pulse structure. Promising initial results provided by the international LCLS (Linac Coherent Light Source) SPI initiative highlight the potential of SPI. Current available injection methods generally have high sample consumption and do not provide any options for pulsing, selection or orientation of particles, which poses a problem for data evaluation. Aerosol-injector-based sample delivery is the current method of choice for SPI experiments, although, to a lesser extent, electrospray and electrospinning are used. Single particles scatter only a limited number of photons providing a single orientation for data evaluation, hence large datasets are required from particles in multiple orientations in order to reconstruct a structure. Here, a feasibility study demonstrates that nano-electrospray ionization, usually employed in biomolecular mass spectrometry, provides enough ion flux for SPI experiments. A novel instrument setup at the SPB/SFX instrument is proposed, which has the benefit of extremely low background while delivering mass over charge and conformation-selected ions for SPI.

Kinetics of Mimivirus Infection Stages Quantified Using Image Flow Cytometry

Due to the heterogeneity of viruses and their hosts, a comprehensive view of viral infection is best achieved by analyzing large populations of infected cells. However, information regarding variation in infected cell populations is lost in bulk measurements. Motivated by an interest in the temporal progression of events in virally infected cells, we used image flow cytometry (IFC) to monitor changes in Acanthamoeba polyphaga cells infected with Mimivirus. This first use of IFC to study viral infection required the development of methods to preserve morphological features of adherent amoeba cells prior to detachment and analysis in suspension. It also required the identification of IFC parameters that best report on key events in the Mimivirus infection cycle. The optimized IFC protocol enabled the simultaneous monitoring of diverse processes including generation of viral factories, transport, and fusion of replication centers within the cell, accumulation of viral progeny, and changes in cell morphology for tens of thousands of cells. After obtaining the time windows for these processes, we used IFC to evaluate the effects of perturbations such as oxidative stress and cytoskeletal disruptors on viral infection. Accurate dose‐response curves could be generated, and we found that mild oxidative stress delayed multiple stages of virus production, but eventually infection processes occurred with approximately the same amplitudes. We also found that functional actin cytoskeleton is required for fusion of viral replication centers and later for the production of viral progeny. Through this report, we demonstrate that IFC offers a quantitative, high‐throughput, and highly robust approach to study viral infection cycles and virus–host interactions. © The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.