3D printing of gas-dynamic virtual nozzles and optical characterization of high-speed microjets

Advanced manufacturing provides tailor-made solutions for crystallography with x-ray free-electron lasers

Serial crystallography at large facilities, such as x-ray free-electron lasers and synchrotrons, evolved as a powerful method for the high-resolution structural investigation of proteins that are critical for human health, thus advancing drug discovery and novel therapies. However, a critical barrier to successful serial crystallography experiments lies in the efficient handling of the protein microcrystals and solutions at microscales. Microfluidics are the obvious approach for any high-throughput, nano-to-microliter sample handling, that also requires design flexibility and rapid prototyping to deal with the variable shapes, sizes, and density of crystals. Here, we discuss recent advances in polymer 3D printing for microfluidics-based serial crystallography research and present a demonstration of emerging, large-scale, nano-3D printing approaches leading into the future of 3D sample environment and delivery device fabrication from liquid jet gas-dynamic virtual nozzles devices to fixed-target sample environment technology.

Thinner than a knife's edge: 3D-printed liquid sheet jet technology for solution phase XFEL experiments

In this commentary, we explore the pioneering implementation of 3D-printed thin liquid sheet devices for advanced X-ray scattering and spectroscopy experiments at high-repetition rate XFELs.

3D-printed sheet jet for stable megahertz liquid sample delivery at X-ray free-electron lasers

X-ray free-electron lasers (XFELs) can probe chemical and biological reactions as they unfold with unprecedented spatial and temporal resolution. A principal challenge in this pursuit involves the delivery of samples to the X-ray interaction point in such a way that produces data of the highest possible quality and with maximal efficiency. This is hampered by intrinsic constraints posed by the light source and operation within a beamline environment. For liquid samples, the solution typically involves some form of high-speed liquid jet, capable of keeping up with the rate of X-ray pulses. However, conventional jets are not ideal because of radiation-induced explosions of the jet, as well as their cylindrical geometry combined with the X-ray pointing instability of many beamlines which causes the interaction volume to differ for every pulse. This complicates data analysis and contributes to measurement errors. An alternative geometry is a liquid sheet jet which, with its constant thickness over large areas, eliminates the problems related to X-ray pointing. Since liquid sheets can be made very thin, the radiation-induced explosion is reduced, boosting their stability. These are especially attractive for experiments which benefit from small interaction volumes such as fluctuation X-ray scattering and several types of spectroscopy. Although their use has increased for soft X-ray applications in recent years, there has not yet been wide-scale adoption at XFELs. Here, gas-accelerated liquid sheet jet sample injection is demonstrated at the European XFEL SPB/SFX nano focus beamline. Its performance relative to a conventional liquid jet is evaluated and superior performance across several key factors has been found. This includes a thickness profile ranging from hundreds of nanometres to 60 nm, a fourfold increase in background stability and favorable radiation-induced explosion dynamics at high repetition rates up to 1.13 MHz. Its minute thickness also suggests that ultrafast single-particle solution scattering is a possibility.

Modular droplet injector for sample conservation providing new structural insight for the conformational heterogeneity in the disease-associated NQO1 enzyme

Droplet injection strategies are a promising tool to reduce the large amount of sample consumed in serial femtosecond crystallography (SFX) measurements at X-ray free electron lasers (XFELs) with continuous injection approaches. Here, we demonstrate a new modular microfluidic droplet injector (MDI) design that was successfully applied to deliver microcrystals of the human NAD(P)H:quinone oxidoreductase 1 (NQO1) and phycocyanin. We investigated droplet generation conditions through electrical stimulation for both protein samples and implemented hardware and software components for optimized crystal injection at the Macromolecular Femtosecond Crystallography (MFX) instrument at the Stanford Linac Coherent Light Source (LCLS). Under optimized droplet injection conditions, we demonstrate that up to 4-fold sample consumption savings can be achieved with the droplet injector. In addition, we collected a full data set with droplet injection for NQO1 protein crystals with a resolution up to 2.7 Å, leading to the first room-temperature structure of NQO1 at an XFEL. NQO1 is a flavoenzyme associated with cancer, Alzheimer's and Parkinson's disease, making it an attractive target for drug discovery. Our results reveal for the first time that residues Tyr128 and Phe232, which play key roles in the function of the protein, show an unexpected conformational heterogeneity at room temperature within the crystals. These results suggest that different substates exist in the conformational ensemble of NQO1 with functional and mechanistic implications for the enzyme's negative cooperativity through a conformational selection mechanism. Our study thus demonstrates that microfluidic droplet injection constitutes a robust sample-conserving injection method for SFX studies on protein crystals that are difficult to obtain in amounts necessary for continuous injection, including the large sample quantities required for time-resolved mix-and-inject studies.

Gas Dynamic Virtual Nozzle Sprayer for an Introduction of Liquid Samples in Atmospheric Pressure Ionization Mass Spectrometry

Electrospray may exhibit inadequate ionization efficiency in some applications. In such cases, atmospheric-pressure chemical ionization (APCI) and photoionization (APPI) can be used. Despite a wide application potential, no APCI and APPI sources dedicated to very low sample flow rates exist on the market. Since the ion source performance depends on the transfer of analytes from the liquid to the gas phase, a nebulizer is a critical component of an ion source. Here, we report on the nebulizer with a gas dynamic virtual nozzle (GDVN) and its applicability in APCI at microliter-per-minute flow rates. Nebulizers differing by geometrical parameters were fabricated and characterized regarding the jet breakup regime, droplet size, droplet velocity, and spray angle for liquid flow rates of 0.75-15.0 μL/min. A micro-APCI source with the GDVN nebulizer behaved as a mass-flow-sensitive detector and provided stable and intense analyte signals. Compared to a classical APCI source, an order of magnitude lower detection limit for verapamil was achieved. Mass spectra recorded with the nebulizer in dripping and jetting modes were almost identical and did not differ from normal APCI spectra. Clogging never occurred during the experiments, indicating the high robustness of the nebulizer. Low-flow-rate APCI and APPI sources with a GDVN sprayer promise new applications for low- and medium-polar analytes.

Room-temperature structural studies of SARS-CoV-2 protein NendoU with an X-ray free-electron laser

NendoU from SARS-CoV-2 is responsible for the virus's ability to evade the innate immune system by cleaving the polyuridine leader sequence of antisense viral RNA. Here we report the room-temperature structure of NendoU, solved by serial femtosecond crystallography at an X-ray free-electron laser to 2.6 Å resolution. The room-temperature structure provides insight into the flexibility, dynamics, and other intrinsic properties of NendoU, with indications that the enzyme functions as an allosteric switch. Functional studies examining cleavage specificity in solution and in crystals support the uridine-purine cleavage preference, and we demonstrate that enzyme activity is fully maintained in crystal form. Optimizing the purification of NendoU and identifying suitable crystallization conditions set the benchmark for future time-resolved serial femtosecond crystallography studies. This could advance the design of antivirals with higher efficacy in treating coronaviral infections, since drugs that block allosteric conformational changes are less prone to drug resistance.

An experimental study of liquid micro-jets produced with a gas dynamic virtual nozzle under the influence of an electric field

The results of an experimental study of micro-jets produced with a gas dynamic virtual nozzle (GDVN) under the influence of an electric field are provided and discussed for the first time. The experimental study is performed with a 50% volume mixture of water and ethanol, and nitrogen focusing gas. The liquid sample and gas Reynolds numbers range from 0.09-5.4 and 0-190, respectively. The external electrode was positioned 400-500 μm downstream of the nozzle tip and an effect of electric potential between the electrode and the sample liquid from 0-7 kV was investigated. The jetting parametric space is examined as a function of operating gas and liquid flow rates, outlet chamber pressure, and an external electric field. The experimentally observed jet diameter, length and velocity ranged from 1-25 μm, 50-500 μm and 0.5-10 m/s, respectively. The jetting shape snapshots were processed automatically using purposely developed computer vision software. The velocity of the jet was calculated from the measured jet diameter and the sample flow rate. It is found that micro-jets accelerate in the direction of the applied electric field in the downstream direction at a constant acceleration as opposed to the standard GDVNs. New jetting modes were observed, where either the focusing gas or the electric forces dominate, encouraging further theoretical and numerical studies towards optimized system design. The study shows the potential to unlock a new generation of low background sample delivery for serial diffraction measurements of weakly scattering objects.

Mechanical property of pixel extrusion and pin forming for polymer, ceramic, and metal formation

The rapid material fabrications in pixel shape were mechanically studied in comparison with FDM and STL 3D printing technique. The pixel extrusion technique was the extrusion with a set of holes in the die. By controlling the flow of each hole in the die, the shape could be adjustable. The pixel molding technique composed of a set of pins. By adjusting the length of pin inside the mold, the shape of cavity could be designed. Compared to 3D printing which requires the material deposition with 2D scanning for several layers, 3D material fabrication by pixel extrusion and pixel molding were much faster; however, their resolutions were still much worse compared to 3D printing at the moment. SEM, Tensile test, flexural test, including hardness were used to observe the properties of pixel extrusion and pixel molding. The pixel molding technique was also used to fabricate many materials to compare the properties such as cement, iron, and silica. Apparently, materials could be formed and mechanical properties were investigated.

Electrically stimulated droplet injector for reduced sample consumption in serial crystallography

With advances in X-ray free-electron lasers (XFELs), serial femtosecond crystallography (SFX) has enabled the static and dynamic structure determination for challenging proteins such as membrane protein complexes. In SFX with XFELs, the crystals are typically destroyed after interacting with a single XFEL pulse. Therefore, thousands of new crystals must be sequentially introduced into the X-ray beam to collect full data sets. Because of the serial nature of any SFX experiment, up to 99% of the sample delivered to the X-ray beam during its "off-time" between X-ray pulses is wasted due to the intrinsic pulsed nature of all current XFELs. To solve this major problem of large and often limiting sample consumption, we report on improvements of a revolutionary sample-saving method that is compatible with all current XFELs. We previously reported 3D-printed injection devices coupled with gas dynamic virtual nozzles (GDVNs) capable of generating samples containing droplets segmented by an immiscible oil phase for jetting crystal-laden droplets into the path of an XFEL. Here, we have further improved the device design by including metal electrodes inducing electrowetting effects for improved control over droplet generation frequency to stimulate the droplet release to matching the XFEL repetition rate by employing an electrical feedback mechanism. We report the improvements in this electrically triggered segmented flow approach for sample conservation in comparison with a continuous GDVN injection using the microcrystals of lysozyme and 3-deoxy-D-manno-octulosonate 8-phosphate synthase and report the segmented flow approach for sample injection applied at the Macromolecular Femtosecond Crystallography instrument at the Linear Coherent Light Source for the first time.

Observations of phase changes in monoolein during high viscous injection

Serial crystallography of membrane proteins often employs high-viscosity injectors (HVIs) to deliver micrometre-sized crystals to the X-ray beam. Typically, the carrier medium is a lipidic cubic phase (LCP) media, which can also be used to nucleate and grow the crystals. However, despite the fact that the LCP is widely used with HVIs, the potential impact of the injection process on the LCP structure has not been reported and hence is not yet well understood. The self-assembled structure of the LCP can be affected by pressure, dehydration and temperature changes, all of which occur during continuous flow injection. These changes to the LCP structure may in turn impact the results of X-ray diffraction measurements from membrane protein crystals. To investigate the influence of HVIs on the structure of the LCP we conducted a study of the phase changes in monoolein/water and monoolein/buffer mixtures during continuous flow injection, at both atmospheric pressure and under vacuum. The reservoir pressure in the HVI was tracked to determine if there is any correlation with the phase behaviour of the LCP. The results indicated that, even though the reservoir pressure underwent (at times) significant variation, this did not appear to correlate with observed phase changes in the sample stream or correspond to shifts in the LCP lattice parameter. During vacuum injection, there was a three-way coexistence of the gyroid cubic phase, diamond cubic phase and lamellar phase. During injection at atmospheric pressure, the coexistence of a cubic phase and lamellar phase in the monoolein/water mixtures was also observed. The degree to which the lamellar phase is formed was found to be strongly dependent on the co-flowing gas conditions used to stabilize the LCP stream. A combination of laboratory-based optical polarization microscopy and simulation studies was used to investigate these observations.

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

A convolutional neural network is applied for the single-hit diffraction-pattern classification step in single-particle-imaging experiments at X-ray free-electron lasers. This approach can be employed not only after the experiment but, importantly, also during an experiment and can significantly reduce the size of data storage for further analysis stages.

Single particle imaging (SPI) at X-ray free-electron lasers is particularly well suited to determining the 3D structure of particles at room temperature. For a successful reconstruction, diffraction patterns originating from a single hit must be isolated from a large number of acquired patterns. It is proposed that this task could be formulated as an image-classification problem and solved using convolutional neural network (CNN) architectures. Two CNN configurations are developed: one that maximizes the F1 score and one that emphasizes high recall. The CNNs are also combined with expectation-maximization (EM) selection as well as size filtering. It is observed that the CNN selections have lower contrast in power spectral density functions relative to the EM selection used in previous work. However, the reconstruction of the CNN-based selections gives similar results. Introducing CNNs into SPI experiments allows the reconstruction pipeline to be streamlined, enables researchers to classify patterns on the fly, and, as a consequence, enables them to tightly control the duration of their experiments. Incorporating non-standard artificial-intelligence-based solutions into an existing SPI analysis workflow may be beneficial for the future development of SPI experiments.

3D printed devices and infrastructure for liquid sample delivery at the European XFEL

The Sample Environment and Characterization (SEC) group of the European X-ray Free-Electron Laser (EuXFEL) develops sample delivery systems for the various scientific instruments, including systems for the injection of liquid samples that enable serial femtosecond X-ray crystallography (SFX) and single-particle imaging (SPI) experiments, among others. For rapid prototyping of various device types and materials, sub-micrometre precision 3D printers are used to address the specific experimental conditions of SFX and SPI by providing a large number of devices with reliable performance. This work presents the current pool of 3D printed liquid sample delivery devices, based on the two-photon polymerization (2PP) technique. These devices encompass gas dynamic virtual nozzles (GDVNs), mixing-GDVNs, high-viscosity extruders (HVEs) and electrospray conical capillary tips (CCTs) with highly reproducible geometric features that are suitable for time-resolved SFX and SPI experiments at XFEL facilities. Liquid sample injection setups and infrastructure on the Single Particles, Clusters, and Biomolecules and Serial Femtosecond Crystallography (SPB/SFX) instrument are described, this being the instrument which is designated for biological structure determination at the EuXFEL.

Co-flow injection for serial crystallography at X-ray free-electron lasers

Serial femtosecond crystallography (SFX) is a powerful technique that exploits X-ray free-electron lasers to determine the structure of macro-molecules at room temperature. Despite the impressive exposition of structural details with this novel crystallographic approach, the methods currently available to introduce crystals into the path of the X-ray beam sometimes exhibit serious drawbacks. Samples requiring liquid injection of crystal slurries consume large quantities of crystals (at times up to a gram of protein per data set), may not be compatible with vacuum configurations on beamlines or provide a high background due to additional sheathing liquids present during the injection. Proposed and characterized here is the use of an immiscible inert oil phase to supplement the flow of sample in a hybrid microfluidic 3D-printed co-flow device. Co-flow generation is reported with sample and oil phases flowing in parallel, resulting in stable injection conditions for two different resin materials experimentally. A numerical model is presented that adequately predicts these flow-rate conditions. The co-flow generating devices reduce crystal clogging effects, have the potential to conserve protein crystal samples up to 95% and will allow degradation-free light-induced time-resolved SFX.

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.

Recent Advances and Future Perspectives on Microfluidic Mix-and-Jet Sample Delivery Devices

The integration of the Gas Dynamic Virtual Nozzle (GDVN) and microfluidic technologies has proven to be a promising sample delivery solution for biomolecular imaging studies and has the potential to be transformative for a range of applications in physics, biology, and chemistry. Here, we review the recent advances in the emerging field of microfluidic mix-and-jet sample delivery devices for the study of biomolecular reaction dynamics. First, we introduce the key parameters and dimensionless numbers involved in their design and characterisation. Then we critically review the techniques used to fabricate these integrated devices and discuss their advantages and disadvantages. We then summarise the most common experimental methods used for the characterisation of both the mixing and jetting components. Finally, we discuss future perspectives on the emerging field of microfluidic mix-and-jet sample delivery devices. In summary, this review aims to introduce this exciting new topic to the wider microfluidics community and to help guide future research in the field.

The XBI BioLab for life science experiments at the European XFEL

The science of X-ray free-electron lasers (XFELs) critically depends on the performance of the X-ray laser and on the quality of the samples placed into the X-ray beam. The stability of biological samples is limited and key biomolecular transformations occur on short timescales. Experiments in biology require a support laboratory in the immediate vicinity of the beamlines. The XBI BioLab of the European XFEL (XBI denotes XFEL Biology Infrastructure) is an integrated user facility connected to the beamlines for supporting a wide range of biological experiments. The laboratory was financed and built by a collaboration between the European XFEL and the XBI User Consortium, whose members come from Finland, Germany, the Slovak Republic, Sweden and the USA, with observers from Denmark and the Russian Federation. Arranged around a central wet laboratory, the XBI BioLab provides facilities for sample preparation and scoring, laboratories for growing prokaryotic and eukaryotic cells, a Bio Safety Level 2 laboratory, sample purification and characterization facilities, a crystallization laboratory, an anaerobic laboratory, an aerosol laboratory, a vacuum laboratory for injector tests, and laboratories for optical microscopy, atomic force microscopy and electron microscopy. Here, an overview of the XBI facility is given and some of the results of the first user experiments are highlighted.

Diffraction data from aerosolized Coliphage PR772 virus particles imaged with the Linac Coherent Light Source

Single Particle Imaging (SPI) with intense coherent X-ray pulses from X-ray free-electron lasers (XFELs) has the potential to produce molecular structures without the need for crystallization or freezing. Here we present a dataset of 285,944 diffraction patterns from aerosolized Coliphage PR772 virus particles injected into the femtosecond X-ray pulses of the Linac Coherent Light Source (LCLS). Additional exposures with background information are also deposited. The diffraction data were collected at the Atomic, Molecular and Optical Science Instrument (AMO) of the LCLS in 4 experimental beam times during a period of four years. The photon energy was either 1.2 or 1.7 keV and the pulse energy was between 2 and 4 mJ in a focal spot of about 1.3 μm x 1.7 μm full width at half maximum (FWHM). The X-ray laser pulses captured the particles in random orientations. The data offer insight into aerosolised virus particles in the gas phase, contain information relevant to improving experimental parameters, and provide a basis for developing algorithms for image analysis and reconstruction.

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.