Search

Ultrafast, high-intensity X-ray free-electron lasers can perform diffraction imaging of single protein molecules. Various algorithms have been developed to determine the orientation of each single-particle diffraction pattern and reconstruct the 3D diffraction intensity. Most of these algorithms rely on the premise that all diffraction patterns originate from identical protein molecules. However, in actual experiments, diffraction patterns from multiple different molecules may be collected simultaneously. Here, we propose a predicted model-aided one-step classification–multireconstruction algorithm that can handle mixed diffraction patterns from various molecules. The algorithm uses predicted structures of different protein molecules as templates to classify diffraction patterns based on correlation coefficients and determines orientations using a correlation maximization method. Tests on simulated data demonstrated high accuracy and efficiency in classification and reconstruction.

Ultra-intense, ultra-fast X-ray free-electron lasers (XFELs) enable the imaging of single protein molecules under ambient temperature and pressure. A crucial aspect of structure reconstruction involves determining the relative orientations of each diffraction pattern and recovering the missing phase information. In this paper, we introduce a predicted model-aided algorithm for orientation determination and phase retrieval, which has been tested on various simulated datasets and has shown significant improvements in the success rate, accuracy and efficiency of XFEL data reconstruction.

The formation of macrophage-derived foam cells has been recognized as the pathological hallmark of atherosclerotic diseases. However, the pathological evolution dynamics and underlying regulatory mechanisms remain largely unknown. Herein, we introduce a single-particle rotational microrheology method for pathological staging of macrophage foaming and antiatherosclerotic explorations by probing the dynamic changes of lysosomal viscous feature over the pathological evolution progression. The principle of this method involves continuous monitoring of out-of-plane rotation-caused scattering brightness fluctuations of the gold nanorod (AuNR) probe-based microrheometer and subsequent determination of rotational relaxation time to analyze the viscous feature in macrophage lysosomes. With this method, we demonstrated the lysosomal viscous feature as a robust pathological reporter and uncovered three distinct pathological stages underlying the evolution dynamics, which are highly correlated with a pathological stage-dependent activation of the NLRP3 inflammasome-involved positive feedback loop. We also validated the potential of this positive feedback loop as a promising therapeutic target and revealed the time window-dependent efficacy of NLRP3 inflammasome-targeted drugs against atherosclerotic diseases. To our knowledge, the pathological staging of macrophage foaming and the pathological stage-dependent activation of the NLRP3 inflammasome-involved positive feedback mechanism have not yet been reported. These findings provide insights into in-depth understanding of evolutionary features and regulatory mechanisms of macrophage foaming, which can benefit the analysis of effective therapeutical drugs as well as the time window of drug treatment against atherosclerotic diseases in preclinical studies. [ABSTRACT FROM AUTHOR]

Fluctuation X‐ray scattering (FXS) offers a complementary approach for nano‐ and bioparticle imaging with an X‐ray free‐electron laser (XFEL), by extracting structural information from correlations in scattered XFEL pulses. Here a workflow is presented for single‐particle structure determination using FXS. The workflow includes procedures for extracting the rotational invariants from FXS patterns, performing structure reconstructions via iterative phasing of the invariants, and aligning and averaging multiple reconstructions. The reconstruction pipeline is implemented in the open‐source software xFrame and its functionality is demonstrated on several simulated structures. [ABSTRACT FROM AUTHOR]

This work investigates the performance of the electrospray aerosol generator at the European X-ray Free Electron Laser (EuXFEL). This generator is, together with an aerodynamic lens stack that transports the particles into the X-ray interaction vacuum chamber, the method of choice to deliver particles for single-particle coherent diffractive imaging (SPI) experiments at the EuXFEL. For these experiments to be successful, it is necessary to achieve high transmission of particles from solution into the vacuum interaction region. Particle transmission is highly dependent on efficient neutralization of the charged aerosol generated by the electrospray mechanism as well as the geometry in the vicinity of the Taylor cone. We report absolute particle transmission values for different neutralizers and geometries while keeping the conditions suitable for SPI experiments. Our findings reveal that a vacuum ultraviolet ionizer demonstrates a transmission efficiency approximately seven times greater than the soft X-ray ionizer used previously. Combined with an optimized orifice size on the counter electrode, we achieve >40% particle transmission from solution into the X-ray interaction region. These findings offer valuable insights for optimizing electrospray aerosol generator configurations and data rates for SPI experiments.

Single-particle imaging using X-ray free-electron lasers (XFELs) is a promising technique for observing nanoscale biological samples under near-physiological conditions. However, as the sample's orientation in each diffraction pattern is unknown, advanced algorithms are required to reconstruct the 3D diffraction intensity volume and subsequently the sample's density model. While most approaches perform 3D reconstruction via determining the orientation of each diffraction pattern, a correlation-based approach utilizes the averaged spatial correlations of diffraction intensities over all patterns, making it well suited for processing experimental data with a poor signal-to-noise ratio of individual patterns. Here, a method is proposed to determine the 3D structure of a sample by analyzing the double, triple and quadruple spatial correlations in diffraction patterns. This ab initio method can reconstruct the basic shape of an irregular unsymmetric 3D sample without requiring any prior knowledge of the sample. The impact of background and noise on correlations is investigated and corrected to ensure the success of reconstruction under simulated experimental conditions. Additionally, the feasibility of using the correlation-based approach to process incomplete partial diffraction patterns is demonstrated. The proposed method is a variable addition to existing algorithms for 3D reconstruction and will further promote the development and adoption of XFEL single-particle imaging techniques.

This work investigates the performance of the electrospray aerosol generator at the European X-ray Free Electron Laser (EuXFEL). This generator is, together with an aerodynamic lens stack that transports the particles into the X-ray interaction vacuum chamber, the method of choice to deliver particles for single-particle coherent diffractive imaging (SPI) experiments at the EuXFEL. For these experiments to be successful, it is necessary to achieve high transmission of particles from solution into the vacuum interaction region. Particle transmission is highly dependent on efficient neutralization of the charged aerosol generated by the electrospray mechanism as well as the geometry in the vicinity of the Taylor cone. We report absolute particle transmission values for different neutralizers and geometries while keeping the conditions suitable for SPI experiments. Our findings reveal that a vacuum ultraviolet ionizer demonstrates a transmission efficiency approximately seven times greater than the soft X-ray ionizer used previously. Combined with an optimized orifice size on the counter electrode, we achieve >40% particle transmission from solution into the X-ray interaction region. These findings offer valuable insights for optimizing electrospray aerosol generator configurations and data rates for SPI experiments. [ABSTRACT FROM AUTHOR]

X‐ray imaging of virus particles at the European XFEL could eventually allow their complete structures to be solved, potentially approaching the resolution of other structural virology methods. To achieve this ambitious goal with today's technologies, about 1 ml of purified virus suspension containing at least 1012 particles per millilitre is required. Such large amounts of concentrated suspension have never before been obtained for enveloped viruses. Tick‐borne encephalitis virus (TBEV) represents an attractive model system for the development of enveloped virus purification and concentration protocols, given the availability of large amounts of inactivated virus material provided by vaccine‐manufacturing facilities. Here, the development of a TBEV vaccine purification and concentration scheme is presented combined with a quality‐control protocol that allows substantial amounts of highly concentrated non‐aggregated suspension to be obtained. Preliminary single‐particle imaging experiments were performed for this sample at the European XFEL, showing distinct diffraction patterns. [ABSTRACT FROM AUTHOR]

With X-ray free-electron lasers (XFELs), it is possible to determine the three-dimensional structure of noncrystalline nanoscale particles using X-ray single-particle imaging (SPI) techniques at room temperature. Classifying SPI scattering patterns, or `speckles', to extract single-hits that are needed for real-time vetoing and three-dimensional reconstruction poses a challenge for high-data-rate facilities like the European XFEL and LCLS-II-HE. Here, we introduce SpeckleNN, a unified embedding model for real-time speckle pattern classification with limited labeled examples that can scale linearly with dataset size. Trained with twin neural networks, SpeckleNN maps speckle patterns to a unified embedding vector space, where similarity is measured by Euclidean distance. We highlight its few-shot classification capability on new never-seen samples and its robust performance despite having only tens of labels per classification category even in the presence of substantial missing detector areas. Without the need for excessive manual labeling or even a full detector image, our classification method offers a great solution for real-time high-throughput SPI experiments.

The transport behavior of ions in the nanopores has an important impact on the performance of the electrochemical devices. Although the classical Transmission‐Line (TL) model has long been used to describe ion transport in pores, the boundary conditions for the applicability of the TL model remain controversial. Here, we investigated the transport kinetics of different ions, within nanochannels of different lengths, by using transient single‐particle imaging with temporal resolution up to microseconds. We found that the ion transport kinetics within short nanochannels may deviate significantly from the TL model. The reason is that the ion transport under nanoconfinement is composed of multi basic stages, and the kinetics differ much under different stage domination. With the shortening of nanochannels, the electrical double layer (EDL) formation would become the "rate‐determining step" and dominate the apparent ion kinetics. Our results imply that using the TL model directly and treating the in‐pore mobility as an unchanged parameter to estimate the ion transport kinetics in short nanopores/nanochannels may lead to orders of magnitude bias. These findings may advance the understanding of the nanoconfined ion transport and promote the related applications. [ABSTRACT FROM AUTHOR]

Covalent organic frameworks (COFs) are promising solid absorbents for the treatment of gaseous iodine. However, extensive efforts are still focused on empirical optimizations of specific binding sites and pore structures in COFs, and the chemical control of gaseous iodine uptake on COFs remains challenging. In this study, the chemically triggered sorption properties of COF‐300 for I2 vapors at the single‐particle level with the dark‐field microscope (DFM) are explored. The present operando single‐particle DFM imaging method enables the direct visualization of an adsorption activity transformation from inactive COF‐300 to active solvated COF‐300 toward gaseous I2 vapors. Exploiting the useful reaction information from time‐lapsed DFM images, the tunable adsorption performance of solvated COF‐300 is quantitatively compared by various solvents. The results illustrate that the isopropanol (IPA)‐solvated COF‐300 achieves the optimum adsorption capacity for I2 among the absorbents. The reaction mechanism is elucidated to be the channel size enlargement and modification of internal surface chemistry in the IPA‐solvated COF‐300, producing a stable I2/IPA‐solvated COF‐300 complex after the sorption reaction. The present chemical control of the sorption behavior of COF‐300 revealed by DFM opens up a new fundamental paradigm for rationally developing high‐performance COF‐based absorbents for removing I2 vapors. [ABSTRACT FROM AUTHOR]

The study of virus structures by X-ray free-electron lasers (XFELs) has attracted increased attention in recent decades. Such experiments are based on the collection of 2D diffraction patterns measured at the detector following the application of femtosecond X-ray pulses to biological samples. To prepare an experiment at the European XFEL, the diffraction data for the tick-borne encephalitis virus (TBEV) was simulated with different parameters and the optimal values were identified. Following the necessary steps of a well established data-processing pipeline, the structure of TBEV was obtained. In the structure determination presented, a priori knowledge of the simulated virus orientations was used. The efficiency of the proposed pipeline was demonstrated.

Upconversion Nanoparticles (UCNPs) have attracted exceptional attention due to their great potential in high-contrast, free-background biofluorescence deep tissue imaging and quantum sensing. Most of these interesting studies have been performed using an ensemble of UCNPs as fluorescent probes in bioapplications. Here, we report a synthesis of small and efficient YLiF4:Yb,Er UCNPs for single-particle imaging as well as sensitive optical temperature sensing. The reported particles demonstrated a bright and photostable upconversion emission at a single particle level under a low laser intensity excitation of 20 W/cm2. Furthermore, the synthesized UCNPs were tested and compared to the commonly used two-photon excitation QDs and organic dyes and showed a nine times better performance at a single particle level under the same experimental conditions. In addition, the synthesized UCNPs demonstrated sensitive optical temperature sensing at a single particle level within the biological temperature range. The good optical properties of single YLiF4:Yb,Er UCNPs open an avenue for small and efficient fluorescent markers in imaging and sensing applications. [ABSTRACT FROM AUTHOR]

Understanding the guest‐induced dynamic deformation process of covalent organic frameworks (COFs) is vitally important to further increase their stimulus‐response performances. Here we report on the dark‐field microscopic (DFM) imaging approach to in situ monitor the guest‐induced deformation evolution of individual COF‐300 crystals in real time. We observe not only transient and nonequilibrium intermediate deformation states but also local surface curvature‐driven diverse adsorption behaviours of single COF‐300 particles for dichloromethane (DCM), undergoing one, two, and multiple expansion‐contraction deformations as well as contraction‐to‐expansion transition. The surface curvature‐dominated deformations are ascribed to the significant differences in the adsorption capacity for DCM at the curved tip and flat side regions, in which DCM can be adsorbed preferentially by curved tip regions of COF‐300. [ABSTRACT FROM AUTHOR]

The study of virus structures by X-ray free-electron lasers (XFELs) has attracted increased attention in recent decades. Such experiments are based on the collection of 2D diffraction patterns measured at the detector following the application of femtosecond X-ray pulses to biological samples. To prepare an experiment at the European XFEL, the diffraction data for the tick-borne encephalitis virus (TBEV) was simulated with different parameters and the optimal values were identified. Following the necessary steps of a well established data-processing pipeline, the structure of TBEV was obtained. In the structure determination presented, a priori knowledge of the simulated virus orientations was used. The efficiency of the proposed pipeline was demonstrated. [ABSTRACT FROM AUTHOR]

Due to the pathogen-specific targeting, neutralization capabilities, and enduring efficacy, neutralizing antibodies (NAs) have received widespread attentions as a critical immunotherapeutic strategy against infectious viruses. However, because of the high variability and complexity of pathogens, rapid determination of neutralization activity of antiviral antibodies remains a challenge. Here, we report a new method, named as out-of-plane polarization imaging based single-particle rotational sensing, for rapid analysis of neutralization activity of antiviral antibody against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Using the spike protein functionalized gold nanorods (AuNRs) and angiotensin-converting enzyme 2 (ACE2) coated gold nanoparticles (AuNPs) as the rotational sensors and chaperone probes, we demonstrated the single-particle rotational sensing strategy for the measurement of rotational diffusion coefficient of the chaperone-bound rotational sensors caused by the specific spike protein-ACE2 interactions. This enables us to measure the neutralizing activity of neutralizing antibody from the analysis of dose-dependent changes in rotational diffusion coefficient (Dr) of the rotational sensors upon the treatment of SARS-CoV-2 antibody. With this technique, we achieved the quantitative determination of neutralization activity of a commercially available SARS-CoV-2 antibody (IC50, 294.1 ng/mL) with satisfying accuracy and anti-interference ability. This simple and robust method holds the potential for rapid and accurate evaluation of neutralization activity against different pathogenic viruses. A novel out-of-plane polarization imaging-based single-particle rotational sensing strategy was proposed for quantitative determination of neutralization activity of SARS-CoV-2 antibody, which was achieved by probing the dose-dependent changes in rotational diffusion coefficient of rotational sensors upon the antibody treatment. [Display omitted] • A novel single-particle rotational sensing strategy method was introduced. • The visualization of spike protein-ACE2 interactions was achieved by charperon-aided rotational sensing. • The IC50 of SARS-CoV-2 antibody was quantified with satisfying accuracy and strong anti-interference ability. [ABSTRACT FROM AUTHOR]

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.

The analysis of a single-particle imaging (SPI) experiment performed at the AMO beamline at LCLS as part of the SPI initiative is presented here. A workflow for the three-dimensional virus reconstruction of the PR772 bacteriophage from measured single-particle data is developed. It consists of several well defined steps including single-hit diffraction data classification, refined filtering of the classified data, reconstruction of three-dimensional scattered intensity from the experimental diffraction patterns by orientation determination and a final three-dimensional reconstruction of the virus electron density without symmetry constraints. The analysis developed here revealed and quantified nanoscale features of the PR772 virus measured in this experiment, with the obtained resolution better than 10 nm, with a clear indication that the structure was compressed in one direction and, as such, deviates from ideal icosahedral symmetry.

The quantitative detection of critical biomolecules and in particular low-abundance biomarkers in biofluids is crucial for early-stage diagnosis and management but remains a challenge largely owing to the insufficient sensitivity of existing ensemble-sensing methods. The single-particle imaging technique has emerged as an important tool to analyze ultralow-abundance biomolecules by engineering and exploiting the distinct physical and chemical property of individual luminescent particles. In this review, we focus and survey the latest advances in single-particle optical imaging (OSPI) for ultrasensitive bioanalysis pertaining to basic biological studies and clinical applications. We first introduce state-of-the-art OSPI techniques, including fluorescence, surface-enhanced Raman scattering, electrochemiluminescence, and dark-field scattering, with emphasis on the contributions of various metal and nonmetal nano-labels to the improvement of the signal-to-noise ratio. During the discussion of individual techniques, we also highlight their applications in spatial–temporal measurement of key biomarkers such as proteins, nucleic acids and extracellular vesicles with single-entity sensitivity. To that end, we discuss the current challenges and prospective trends of single-particle optical-imaging-based bioanalysis. [ABSTRACT FROM AUTHOR]

T7 phages are E. coli-infecting viruses that find and invade their target with high specificity and efficiency. The exact molecular mechanisms of the T7 infection cycle are yet unclear. As the infection involves mechanical events, single-particle methods are to be employed to alleviate the problems of ensemble averaging. Here we used TIRF microscopy to uncover the spatial dynamics of the target recognition and binding by individual T7 phage particles. In the initial phase, T7 virions bound reversibly to the bacterial membrane via two-dimensional diffusive exploration. Stable bacteriophage anchoring was achieved by tail-fiber complex to receptor binding which could be observed in detail by atomic force microscopy (AFM) under aqueous buffer conditions. The six anchored fibers of a given T7 phage-displayed isotropic spatial orientation. The viral infection led to the onset of an irreversible structural program in the host which occurred in three distinct steps. First, bacterial cell surface roughness, as monitored by AFM, increased progressively. Second, membrane blebs formed on the minute time scale (average ~5 min) as observed by phase-contrast microscopy. Finally, the host cell was lysed in a violent and explosive process that was followed by the quick release and dispersion of the phage progeny. DNA ejection from T7 could be evoked in vitro by photothermal excitation, which revealed that genome release is mechanically controlled to prevent premature delivery of host-lysis genes. The single-particle approach employed here thus provided an unprecedented insight into the details of the complete viral cycle. [ABSTRACT FROM AUTHOR]

In single-particle imaging (SPI) experiments, diffraction patterns of identical particles are recorded. The particles are injected into the X-ray free-electron laser (XFEL) beam in random orientations. The crucial step of the data processing of SPI is finding the orientations of the recorded diffraction patterns in reciprocal space and reconstructing the 3D intensity distribution. Here, two orientation methods are compared: the expansion maximization compression (EMC) algorithm and the correlation maximization (CM) algorithm. To investigate the efficiency, reliability and accuracy of the methods at various XFEL pulse fluences, simulated diffraction patterns of biological molecules are used.

X-ray free-electron lasers (XFELs) have the ability to produce ultra-bright femtosecond X-ray pulses for coherent diffraction imaging of biomolecules. While the development of methods and algorithms for macromolecular crystallography is now mature, XFEL experiments involving aerosolized or solvated biomolecular samples offer new challenges in terms of both experimental design and data processing. Skopi is a simulation package that can generate single-hit diffraction images for reconstruction algorithms, multihit diffraction images of aggregated particles for training machine learning classifiers using labeled data, diffraction images of randomly distributed particles for fluctuation X-ray scattering algorithms, and diffraction images of reference and target particles for holographic reconstruction algorithms. Skopi is a resource to aid feasibility studies and advance the development of algorithms for noncrystalline experiments at XFEL facilities. [ABSTRACT FROM AUTHOR]

Free-electron lasers now have the ability to collect X-ray diffraction patterns from individual molecules; however, each sample is delivered at unknown orientation and may be in one of several conformational states, each with a different molecular structure. Hit rates are often low, typically around 0.1%, limiting the number of useful images that can be collected. Determining accurate structural information requires classifying and orienting each image, accurately assembling them into a 3D diffraction intensity function, and determining missing phase information. Additionally, single particles typically scatter very few photons, leading to high image noise levels. We develop a multitiered iterative phasing algorithm to reconstruct structural information from single-particle diffraction data by simultaneously determining the states, orientations, intensities, phases, and underlying structure in a single iterative procedure. We leverage real-space constraints on the structure to help guide optimization and reconstruct underlying structure from very few images with excellent global convergence properties. We show that this approach can determine structural resolution beyond what is suggested by standard Shannon sampling arguments for ideal images and is also robust to noise.

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. [ABSTRACT FROM AUTHOR]

The reconstruction of a single-particle image from the modulus of its Fourier transform, by phase-retrieval methods, has been extensively applied in X-ray structural science. Particularly for strong-phase objects, such as the phase domains found inside crystals by Bragg coherent diffraction imaging (BCDI), conventional iteration methods are time consuming and sensitive to their initial guess because of their iterative nature. Here, a deep-neural-network model is presented which gives a fast and accurate estimate of the complex single-particle image in the form of a universal approximator learned from synthetic data. A way to combine the deep-neural-network model with conventional iterative methods is then presented to refine the accuracy of the reconstructed results from the proposed deep-neural-network model. Improved convergence is also demonstrated with experimental BCDI data.

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. [ABSTRACT FROM AUTHOR]

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.

Resolving the electronic structure of single biological molecules in their native state was among the primary motivations behind X-ray free-electron lasers. The ultra-short pulses they produce can outrun the atomic motion induced by radiation damage, but the electronic structure of the sample is still significantly modified from its original state. This paper explores the decoherence of the scattered signal induced by temporal evolution of the electronic structure in the sample molecule. It is shown that the undamaged electron density of a single-molecule sample can often be retrieved using only the two most occupied modes from the coherent mode decomposition of the partially coherent diffraction fluence.

Ultrafast, high-intensity X-ray free-electron lasers can perform diffraction imaging of single protein molecules. Various algorithms have been developed to determine the orientation of each single-particle diffraction pattern and reconstruct the 3D diffraction intensity. Most of these algorithms rely on the premise that all diffraction patterns originate from identical protein molecules. However, in actual experiments, diffraction patterns from multiple different molecules may be collected simultaneously. Here, we propose a predicted model-aided one-step classification-multireconstruction algorithm that can handle mixed diffraction patterns from various molecules. The algorithm uses predicted structures of different protein molecules as templates to classify diffraction patterns based on correlation coefficients and determines orientations using a correlation maximization method. Tests on simulated data demonstrated high accuracy and efficiency in classification and reconstruction., (open access.)

The formation of macrophage-derived foam cells has been recognized as the pathological hallmark of atherosclerotic diseases. However, the pathological evolution dynamics and underlying regulatory mechanisms remain largely unknown. Herein, we introduce a single-particle rotational microrheology method for pathological staging of macrophage foaming and antiatherosclerotic explorations by probing the dynamic changes of lysosomal viscous feature over the pathological evolution progression. The principle of this method involves continuous monitoring of out-of-plane rotation-caused scattering brightness fluctuations of the gold nanorod (AuNR) probe-based microrheometer and subsequent determination of rotational relaxation time to analyze the viscous feature in macrophage lysosomes. With this method, we demonstrated the lysosomal viscous feature as a robust pathological reporter and uncovered three distinct pathological stages underlying the evolution dynamics, which are highly correlated with a pathological stage-dependent activation of the NLRP3 inflammasome-involved positive feedback loop. We also validated the potential of this positive feedback loop as a promising therapeutic target and revealed the time window-dependent efficacy of NLRP3 inflammasome-targeted drugs against atherosclerotic diseases. To our knowledge, the pathological staging of macrophage foaming and the pathological stage-dependent activation of the NLRP3 inflammasome-involved positive feedback mechanism have not yet been reported. These findings provide insights into in-depth understanding of evolutionary features and regulatory mechanisms of macrophage foaming, which can benefit the analysis of effective therapeutical drugs as well as the time window of drug treatment against atherosclerotic diseases in preclinical studies., Competing Interests: Competing interests statement:The authors declare no competing interest.

The dynamics of ion transport at the interface is the critical factor for determining the performance of an electrochemical energy storage device. While practical applications are realized in concentrated electrolytes and nanopores, there is a limited understanding of their ion dynamic features. Herein, we studied the interfacial ion dynamics in room-temperature ionic liquids by transient single-particle imaging with microsecond-scale resolution. We observed slowed-down dynamics at lower potential while acceleration was observed at higher potential. Combined with simulation, we found that the microstructure evolution of the electric double layer (EDL) results in potential-dependent kinetics. Then, we established a correspondence between the ion dynamics and interfacial ion composition. Besides, the ordered ion orientation within EDL is also an essential factor for accelerating interfacial ion transport. These results inspire us with a new possibility to optimize electrochemical energy storage through the good control of the rational design of the interfacial ion structures.

Covalent organic frameworks (COFs) are promising iodine adsorbents. For improved performances, it is critical and essential to fundamentally understand the underlying mechanism. Here, using the operando dark-field optical microscopy (DFM) imaging technique, the observation of an extraordinary structure shrinkage of 2D triphenylbenzene (TPB)-dimethoxyterephthaldehyde (DMTP)-COF upon the adsorption of I 2 vapor at the single-particle resolution is reported. Combining single-particle DFM imaging with other experimental and theoretical methods, it is revealed that the shrinkage mechanism of the TPB-DMTP-COF is attributed to the I 2 sorption-induced synchronous skeleton-pore interactions. The redox reaction of I 2 and TPB-DMTP-COF yields some cationic skeletons and I 3 - species, which triggers the multi-directional halogen-bonding interactions of I 2 and I 3 - as well as strong cation-π interactions between neutral and cationic skeletons, accompanying the synchronous in-plane skeleton shrinking in the xy plane and compact out-of-plane layer packing in the z-direction. This understanding of the synchronous action between the skeleton and pore breaks the perspective on the structure robustness of 2D COFs with excellent stability during the I 2 uptake, which offers pivotal guidance for the rational design and creation of advanced microporous adsorbents., (© 2024 Wiley‐VCH GmbH.)

We developed multiwavelength evanescent scattering microscopy (MWESM), which can acquire plasmonic nanoparticle images at the particle level using the evanescent field as the incident source and distinguish different LSPR (localized surface plasmon resonance) spectral peaks among four wavelengths. Our microscope could be easily and simply built by modifying a commercial total internal reflection fluorescence microscope (TIRFM) with the substitution of a beamsplitter and the addition of a semicircular stop. The ultrathin depth of illumination and rejection of the reflected incident source together contribute to the high sensitivity and contrast of single nanoparticle imaging. We first validated the capability of our imaging system in distinguishing plasmonic nanoparticles bearing different LSPR spectral peaks, and the results were consistent with the scattering spectra results of hyperspectral imaging. Moreover, we demonstrated high imaging quality from the aspects of the signal/noise ratio and point spread function of the single-particle images. Meaningfully, the system can be utilized in rapidly determining the concentration of toxic lead ions in environmental and biological samples with good linearity and sensitivity, based on single-particle evanescent scattering imaging through the detection of the alteration of the LSPR of silver nanoparticles. This system holds the potential to advance the field of nanoparticle imaging and foster the application of nanomaterials as sensors.

Ultra-intense, ultra-fast X-ray free-electron lasers (XFELs) enable the imaging of single protein molecules under ambient temperature and pressure. A crucial aspect of structure reconstruction involves determining the relative orientations of each diffraction pattern and recovering the missing phase information. In this paper, we introduce a predicted model-aided algorithm for orientation determination and phase retrieval, which has been tested on various simulated datasets and has shown significant improvements in the success rate, accuracy and efficiency of XFEL data reconstruction., (open access.)

The quantitative detection of critical biomolecules and in particular low-abundance biomarkers in biofluids is crucial for early-stage diagnosis and management but remains a challenge largely owing to the insufficient sensitivity of existing ensemble-sensing methods. The single-particle imaging technique has emerged as an important tool to analyze ultralow-abundance biomolecules by engineering and exploiting the distinct physical and chemical property of individual luminescent particles. In this review, we focus and survey the latest advances in single-particle optical imaging (OSPI) for ultrasensitive bioanalysis pertaining to basic biological studies and clinical applications. We first introduce state-of-the-art OSPI techniques, including fluorescence, surface-enhanced Raman scattering, electrochemiluminescence, and dark-field scattering, with emphasis on the contributions of various metal and nonmetal nano-labels to the improvement of the signal-to-noise ratio. During the discussion of individual techniques, we also highlight their applications in spatial–temporal measurement of key biomarkers such as proteins, nucleic acids and extracellular vesicles with single-entity sensitivity. To that end, we discuss the current challenges and prospective trends of single-particle optical-imaging-based bioanalysis.

Lipid nanoparticles (LNPs) containing ionizable cationic lipids are proven delivery systems for therapeutic nucleic acids, such as small interfering RNA (siRNA). It is important to understand the relationship between the interior pH of LNPs and the pH of the external environment to understand LNP formulation and function. Here, we developed a simple and rapid approach for determining the pH of the LNP core using a pH-sensitive fluorescent dye-based DNA probe. LNP siRNA systems containing pH-responsive DNA probes (LNP-siRNA&DNA) were generated by rapid mixing of lipids in ethanol and pH 4 aqueous buffer containing siRNA and DNA probes. We demonstrated that DNA probes were readily encapsulated in LNP systems and were sequestered into an environment at a high concentration as evidenced by an inter-probe FRET signal. It was shown that the pH of LNP encapsulated probes closely follows the pH increase or decrease of the external environment. This indicates that the clinically approved LNP RNA systems with similar lipid compositions (e.g., Onpattro and Comirnaty) are highly permeable to protons and that the pH of the interior environment closely mirrors the external environment. The pH-dependent response of the probe in LNPs was also confirmed under buffer conditions at various pHs. Furthermore, we showed that the pH-sensitive DNA probe can be incorporated into LNP systems at levels that allow the pH response to be monitored at a single LNP level using convex lens-induced confinement (CLiC) confocal microscopy. Direct visualization of the internal pH of single particles with the fluorescent DNA probe was achieved by CLiC for LNP-siRNA&DNA systems formulated under both high and normal ionic strength conditions. [Display omitted] [ABSTRACT FROM AUTHOR]

Using X-ray free-electron lasers (XFELs), it is possible to determine three-dimensional structures of nanoscale particles using single-particle imaging methods. Classification algorithms are needed to sort out the single-particle diffraction patterns from the large amount of XFEL experimental data. However, different methods often yield inconsistent results. This study compared the performance of three classification algorithms: convolutional neural network, graph cut and diffusion map manifold embedding methods. The identified single-particle diffraction data of the PR772 virus particles were assembled in the three-dimensional Fourier space for real-space model reconstruction. The comparison showed that these three classification methods lead to different datasets and subsequently result in different electron density maps of the reconstructed models. Interestingly, the common dataset selected by these three methods improved the quality of the merged diffraction volume, as well as the resolutions of the reconstructed maps.

The analysis of a single-particle imaging (SPI) experiment performed at the AMO beamline at LCLS as part of the SPI initiative is presented here. A workflow for the three-dimensional virus reconstruction of the PR772 bacteriophage from measured single-particle data is developed. It consists of several well defined steps including single-hit diffraction data classification, refined filtering of the classified data, reconstruction of three-dimensional scattered intensity from the experimental diffraction patterns by orientation determination and a final three-dimensional reconstruction of the virus electron density without symmetry constraints. The analysis developed here revealed and quantified nanoscale features of the PR772 virus measured in this experiment, with the obtained resolution better than 10 nm, with a clear indication that the structure was compressed in one direction and, as such, deviates from ideal icosahedral symmetry.

Single-particle imaging with X-ray free-electron lasers (XFELs) has the potential to provide structural information at atomic resolution for non-crystalline biomolecules. This potential exists because ultra-short intense pulses can produce interpretable diffraction data notwithstanding radiation damage. This paper explores the impact of pulse duration on the interpretability of diffraction data using comprehensive and realistic simulations of an imaging experiment at the European X-ray Free-Electron Laser. It is found that the optimal pulse duration for molecules with a few thousand atoms at 5 keV lies between 3 and 9 fs.

Single-particle imaging using X-ray free-electron lasers (XFELs) is a promising technique for observing nanoscale biological samples under near-physiological conditions. However, as the sample's orientation in each diffraction pattern is unknown, advanced algorithms are required to reconstruct the 3D diffraction intensity volume and subsequently the sample's density model. While most approaches perform 3D reconstruction via determining the orientation of each diffraction pattern, a correlation-based approach utilizes the averaged spatial correlations of diffraction intensities over all patterns, making it well suited for processing experimental data with a poor signal-to-noise ratio of individual patterns. Here, a method is proposed to determine the 3D structure of a sample by analyzing the double, triple and quadruple spatial correlations in diffraction patterns. This ab initio method can reconstruct the basic shape of an irregular unsymmetric 3D sample without requiring any prior knowledge of the sample. The impact of background and noise on correlations is investigated and corrected to ensure the success of reconstruction under simulated experimental conditions. Additionally, the feasibility of using the correlation-based approach to process incomplete partial diffraction patterns is demonstrated. The proposed method is a variable addition to existing algorithms for 3D reconstruction and will further promote the development and adoption of XFEL single-particle imaging techniques., (open access.)

Background: Tick-borne encephalitis virus (TBEV) is a dangerous human pathogen which envelope structure is already known from cryoEM study. TBEV mature viral particle size (~50 nm in diameter) makes it suitable for single-particle imaging (SPI) on X-ray free-electron laser (XFEL). XFEL SPI studies are at the early stages of development; thus, a well-described and conformationally homogeneous sample is required to develop approaches for experimental setup and data analysis. Here we present the image analysis results of data collected in October 2019 during the European XFEL experiment #2316. Methods: The detector was placed at 1.62 m from the injector; photon energy was around 6 keV, pulse energy 4 mJ, beam diameter ~ 500 nm. All runs were processed to detect hits with threshold filter (5th percentile of lit pixels) and further filtered to omit low-intensity images and images that lack detector modules. Filtered hits were background and geometry corrected with SPImage library and custom python scripts. Then hits were azimuthally integrated using PyFAI library. Scattering profiles were further clustered using the affinity propagation algorithm with cosine similarity metric in log space. Extracted classes were used to build averaged images. All hit profiles were fitted with model scattering to estimate the diameter of the particle. Simulated diffraction patterns were prepared using Condor from the cryoEM electron density map (EMDB ID 3752). Results: During the analysis after the filtering, only 276 clean and bright hits were collected per 135 min of injection (from 27287 hits detected via lit pixels threshold). Thus the hit rate was around ~ 2 hits/min, which is expected to rise in the future. The majority of hits correspond to the 40-50 nm particles (Fig. 1a), which is expected for TBEV. However, the exact size may vary due to solvent evaporation, ion condensation, and possible variability in the sample. Conclusion: The averaged images and their scattering profiles correlate with the simulated scattering patterns, though not ideally (Fig. 1 bc). Such discrepancy is expected due to the absence of electron density in the center of modeled viral structures.

We herein demonstrate robust two‐dimensional (2D) UFO‐shaped plasmonic supraparticles made of gold nanoparticles (AuNPs) and MnO2 nanosheets (denoted as AMNS‐SPs) for directly monitoring cell membrane vesiculation at the single‐particle level. Because the decorated MnO2 nanosheets are ultrathin (4.2 nm) and have large diameters (230 nm), they are flexible enough for deformation and folding for parceling of the AuNPs during the endocytosis process. Correspondingly, the surrounding refractive index of the AuNPs increases dramatically, which results in a distinct red‐shift of the localized surface plasmon resonance (LSPR). Such LSPR modulation provides a convenient and accurate means for directly monitoring the dynamic interactions between 2D nanomaterials and cell membranes. Furthermore, for the endocytosed AMNS‐SPs, the subsequent LSPR blue‐shift induced by etching effects of reducing molecules is promising for exploring the local environment redox states at the single‐cell level. [ABSTRACT FROM AUTHOR]

A numerical simulation infrastructure capable of calculating the flow of gas and the trajectories of particles through an aerodynamic lens injector is presented. The simulations increase the fundamental understanding and predict optimized injection geometries and parameters. Our simulation results were compared to previous reports and also validated against experimental data for 500 nm polystyrene spheres from an aerosol-beam-characterization setup. The simulations yielded a detailed understanding of the radial phase-space distribution and highlighted weaknesses of current aerosol injectors for single-particle diffractive imaging. With the aid of these simulations we developed new experimental implementations to overcome current limitations. [ABSTRACT FROM AUTHOR]