KINNTREX: a neural network to unveil protein mechanisms from time-resolved X-ray crystallography.

Here, a machine-learning method based on a kinetically informed neural network (NN) is introduced. The proposed method is designed to analyze a time series of difference electron-density maps from a time-resolved X-ray crystallographic experiment. The method is named KINNTREX (kinetics-informed NN for time-resolved X-ray crystallography). To validate KINNTREX, multiple realistic scenarios were simulated with increasing levels of complexity. For the simulations, time-resolved X-ray data were generated that mimic data collected from the photocycle of the photoactive yellow protein. KINNTREX only requires the number of intermediates and approximate relaxation times (both obtained from a singular valued decomposition) and does not require an assumption of a candidate mechanism. It successfully predicts a consistent chemical kinetic mechanism, together with difference electron-density maps of the intermediates that appear during the reaction. These features make KINNTREX attractive for tackling a wide range of biomolecular questions. In addition, the versatility of KINNTREX can inspire more NN-based applications to time-resolved data from biological macromolecules obtained by other methods.

Signal Transduction in an Enzymatic Photoreceptor Revealed by Cryo-Electron Microscopy.

Phytochromes are essential photoreceptor proteins in plants with homologs in bacteria and fungi that regulate a variety of important environmental responses. They display a reversible photocycle between two distinct states, the red-light absorbing Pr and the far-red light absorbing Pfr, each with its own structure. The reversible Pr to Pfr photoconversion requires covalently bound bilin chromophore and regulates the activity of a C-terminal enzymatic domain, which is usually a histidine kinase (HK). In plants, phytochromes translocate to nucleus where the C-terminal effector domain interacts with protein interaction factors (PIFs) to induce gene expression. In bacteria, the HK phosphorylates a response-regulator (RR) protein triggering downstream gene expression through a two-component signaling pathway. Although plant and bacterial phytochromes share similar structural composition, they have contrasting activity in the presence of light with most BphPs being active in the dark. The molecular mechanism that explains bacterial and plant phytochrome signaling has not been well understood due to limited structures of full-length phytochromes with enzymatic domain resolved at or near atomic resolution in both Pr and Pfr states. Here, we report the first Cryo-EM structures of a wild-type bacterial phytochrome with a HK enzymatic domain, determined in both Pr and Pfr states, between 3.75 and 4.13 Å resolution, respectively. Furthermore, we capture a distinct Pr/Pfr heterodimer of the same protein as potential signal transduction intermediate at 3.75 Å resolution. Our three Cryo-EM structures of the distinct signaling states of BphPs are further reinforced by Cryo-EM structures of the truncated PCM of the same protein determined for the Pr/Pfr heterodimer as well as Pfr state. These structures provide insight into the different light-signaling mechanisms that could explain how bacteria and plants see the light.

Heterogeneity in M. tuberculosis ß-lactamase inhibition by Sulbactam.

For decades, researchers have elucidated essential enzymatic functions on the atomic length scale by tracing atomic positions in real-time. Our work builds on possibilities unleashed by mix-and-inject serial crystallography (MISC) at X-ray free electron laser facilities. In this approach, enzymatic reactions are triggered by mixing substrate or ligand solutions with enzyme microcrystals. Here, we report in atomic detail (between 2.2 and 2.7 Å resolution) by room-temperature, time-resolved crystallography with millisecond time-resolution (with timepoints between 3 ms and 700 ms) how the Mycobacterium tuberculosis enzyme BlaC is inhibited by sulbactam (SUB). Our results reveal ligand binding heterogeneity, ligand gating, cooperativity, induced fit, and conformational selection all from the same set of MISC data, detailing how SUB approaches the catalytic clefts and binds to the enzyme noncovalently before reacting to a trans-enamine. This was made possible in part by the application of singular value decomposition to the MISC data using a program that remains functional even if unit cell parameters change up to 3 Å during the reaction.

Beyond ManifoldEM: geometric relationships between manifold embeddings of a continuum of 3D molecular structures and their 2D projections.

ManifoldEM is an established method of geometric machine learning developed to extract information on conformational motions of molecules from their projections obtained by cryogenic electron microscopy (cryo-EM). In a previous work, in-depth analysis of the properties of manifolds obtained for simulated ground-truth data from molecules exhibiting domain motions has led to improvements of this method, as demonstrated in selected applications of single-particle cryo-EM. In the present work this analysis has been extended to investigate the properties of manifolds constructed by embedding data from synthetic models represented by atomic coordinates in motion, or three-dimensional density maps from biophysical experiments other than single-particle cryo-EM, with extensions to cryo-electron tomography and single-particle imaging with a X-ray free-electron laser. Our theoretical analysis revealed interesting relationships between all these manifolds, which can be exploited in future work.

Heterogeneity in the M. tuberculosis ß-Lactamase Inhibition by Sulbactam.

For decades, researchers have been determined to elucidate essential enzymatic functions on the atomic lengths scale by tracing atomic positions in real time. Our work builds on new possibilities unleashed by mix-and-inject serial crystallography (MISC) 1-5 at X-ray free electron laser facilities. In this approach, enzymatic reactions are triggered by mixing substrate or ligand solutions with enzyme microcrystals 6 . Here, we report in atomic detail and with millisecond time-resolution how the Mycobacterium tuberculosis enzyme BlaC is inhibited by sulbactam (SUB). Our results reveal ligand binding heterogeneity, ligand gating 7-9 , cooperativity, induced fit 10,11 and conformational selection 11-13 all from the same set of MISC data, detailing how SUB approaches the catalytic clefts and binds to the enzyme non-covalently before reacting to a trans- enamine. This was made possible in part by the application of the singular value decomposition 14 to the MISC data using a newly developed program that remains functional even if unit cell parameters change during the reaction.

Energy landscapes from cryo-EM snapshots: a benchmarking study.

Biomolecules undergo continuous conformational motions, a subset of which are functionally relevant. Understanding, and ultimately controlling biomolecular function are predicated on the ability to map continuous conformational motions, and identify the functionally relevant conformational trajectories. For equilibrium and near-equilibrium processes, function proceeds along minimum-energy pathways on one or more energy landscapes, because higher-energy conformations are only weakly occupied. With the growing interest in identifying functional trajectories, the need for reliable mapping of energy landscapes has become paramount. In response, various data-analytical tools for determining structural variability are emerging. A key question concerns the veracity with which each data-analytical tool can extract functionally relevant conformational trajectories from a collection of single-particle cryo-EM snapshots. Using synthetic data as an independently known ground truth, we benchmark the ability of four leading algorithms to determine biomolecular energy landscapes and identify the functionally relevant conformational paths on these landscapes. Such benchmarking is essential for systematic progress toward atomic-level movies of continuous biomolecular function.

Recovery of Conformational Continuum From Single-Particle Cryo-EM Images: Optimization of ManifoldEM Informed by Ground Truth.

This work is based on the manifold-embedding approach to study biological molecules exhibiting continuous conformational changes. Previous work established a method-now termed ManifoldEM-capable of reconstructing 3D movies and accompanying free-energy landscapes from single-particle cryo-EM images of macromolecules exercising multiple conformational degrees of freedom. While ManifoldEM has proven its viability in several experimental studies, critical limitations and uncertainties have been found throughout its extended development and use. Guided by insights from studies with cryo-EM ground-truth data, simulated from atomic structures undergoing conformational changes, we have built a novel framework, ESPER, able to retrieve the free-energy landscape and respective 3D Coulomb potential maps for all states simulated. As shown by a direct comparison of ground truth vs. recovered maps, and analysis of experimental data from the 80S ribosome and ryanodine receptor, ESPER offers substantial improvements relative to the previous work.

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

[This corrects the article DOI: 10.1107/S2052252520012798.].

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.

Observation of substrate diffusion and ligand binding in enzyme crystals using high-repetition-rate mix-and-inject serial crystallography.

Here, we illustrate what happens inside the catalytic cleft of an enzyme when substrate or ligand binds on single-millisecond timescales. The initial phase of the enzymatic cycle is observed with near-atomic resolution using the most advanced X-ray source currently available: the European XFEL (EuXFEL). The high repetition rate of the EuXFEL combined with our mix-and-inject technology enables the initial phase of ceftriaxone binding to the Mycobacterium tuberculosis ß-lactamase to be followed using time-resolved crystallography in real time. It is shown how a diffusion coefficient in enzyme crystals can be derived directly from the X-ray data, enabling the determination of ligand and enzyme-ligand concentrations at any position in the crystal volume as a function of time. In addition, the structure of the irreversible inhibitor sulbactam bound to the enzyme at a 66 ms time delay after mixing is described. This demonstrates that the EuXFEL can be used as an important tool for biomedically relevant research.

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.

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.

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.

Retrieving functional pathways of biomolecules from single-particle snapshots.

A primary reason for the intense interest in structural biology is the fact that knowledge of structure can elucidate macromolecular functions in living organisms. Sustained effort has resulted in an impressive arsenal of tools for determining the static structures. But under physiological conditions, macromolecules undergo continuous conformational changes, a subset of which are functionally important. Techniques for capturing the continuous conformational changes underlying function are essential for further progress. Here, we present chemically-detailed conformational movies of biological function, extracted data-analytically from experimental single-particle cryo-electron microscopy (cryo-EM) snapshots of ryanodine receptor type 1 (RyR1), a calcium-activated calcium channel engaged in the binding of ligands. The functional motions differ substantially from those inferred from static structures in the nature of conformationally active structural domains, the sequence and extent of conformational motions, and the way allosteric signals are transduced within and between domains. Our approach highlights the importance of combining experiment, advanced data analysis, and molecular simulations.

Time-resolved serial femtosecond crystallography at the European XFEL.

The European XFEL (EuXFEL) is a 3.4-km long X-ray source, which produces femtosecond, ultrabrilliant and spatially coherent X-ray pulses at megahertz (MHz) repetition rates. This X-ray source has been designed to enable the observation of ultrafast processes with near-atomic spatial resolution. Time-resolved crystallographic investigations on biological macromolecules belong to an important class of experiments that explore fundamental and functional structural displacements in these molecules. Due to the unusual MHz X-ray pulse structure at the EuXFEL, these experiments are challenging. Here, we demonstrate how a biological reaction can be followed on ultrafast timescales at the EuXFEL. We investigate the picosecond time range in the photocycle of photoactive yellow protein (PYP) with MHz X-ray pulse rates. We show that difference electron density maps of excellent quality can be obtained. The results connect the previously explored femtosecond PYP dynamics to timescales accessible at synchrotrons. This opens the door to a wide range of time-resolved studies at the EuXFEL.

Evaluation of the performance of classification algorithms for XFEL single-particle imaging data.

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.

Free-electron laser data for multiple-particle fluctuation scattering analysis.

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

Enzyme intermediates captured "on the fly" by mix-and-inject serial crystallography.

BACKGROUND: Ever since the first atomic structure of an enzyme was solved, the discovery of the mechanism and dynamics of reactions catalyzed by biomolecules has been the key goal for the understanding of the molecular processes that drive life on earth. Despite a large number of successful methods for trapping reaction intermediates, the direct observation of an ongoing reaction has been possible only in rare and exceptional cases. RESULTS: Here, we demonstrate a general method for capturing enzyme catalysis "in action" by mix-and-inject serial crystallography (MISC). Specifically, we follow the catalytic reaction of the Mycobacterium tuberculosis ß-lactamase with the third-generation antibiotic ceftriaxone by time-resolved serial femtosecond crystallography. The results reveal, in near atomic detail, antibiotic cleavage and inactivation from 30 ms to 2 s. CONCLUSIONS: MISC is a versatile and generally applicable method to investigate reactions of biological macromolecules, some of which are of immense biological significance and might be, in addition, important targets for structure-based drug design. With megahertz X-ray pulse rates expected at the Linac Coherent Light Source II and the European X-ray free-electron laser, multiple, finely spaced time delays can be collected rapidly, allowing a comprehensive description of biomolecular reactions in terms of structure and kinetics from the same set of X-ray data.

Conformational landscape of a virus by single-particle X-ray scattering.

Using a manifold-based analysis of experimental diffraction snapshots from an X-ray free electron laser, we determine the three-dimensional structure and conformational landscape of the PR772 virus to a detector-limited resolution of 9 nm. Our results indicate that a single conformational coordinate controls reorganization of the genome, growth of a tubular structure from a portal vertex and release of the genome. These results demonstrate that single-particle X-ray scattering has the potential to shed light on key biological processes.

Coherent soft X-ray diffraction imaging of coliphage PR772 at the Linac coherent light source.

Single-particle diffraction from X-ray Free Electron Lasers offers the potential for molecular structure determination without the need for crystallization. In an effort to further develop the technique, we present a dataset of coherent soft X-ray diffraction images of Coliphage PR772 virus, collected at the Atomic Molecular Optics (AMO) beamline with pnCCD detectors in the LAMP instrument at the Linac Coherent Light Source. The diameter of PR772 ranges from 65-70 nm, which is considerably smaller than the previously reported ~600 nm diameter Mimivirus. This reflects continued progress in XFEL-based single-particle imaging towards the single molecular imaging regime. The data set contains significantly more single particle hits than collected in previous experiments, enabling the development of improved statistical analysis, reconstruction algorithms, and quantitative metrics to determine resolution and self-consistency.