The Helmholtz-Zentrum Hereon is operating imaging beamlines for X-ray tomography (P05 IBL, P07 HEMS) for academic and industrial users at the synchrotron-radiation source PETRA III at DESY in Hamburg, Germany. The high flux density and coherence of synchrotron radiation enable high-resolution in situ/operando/in vivo tomography experiments and phase-contrast imaging techniques, respectively. Large amounts of 3D and 4D data are collected that are difficult to process and analyze. Recently, we have explored machine learning approaches for the reconstruction, processing and analysis of synchrotron-radiation tomography data. Here, we report on the application of supervised learning for multimodal data analysis to generate a virtual 3D histology, digital volume correlation of 4D in situ tomography data, and instance segmentation. Furthermore, we present findings related to unsupervised learning in the context of semantic segmentation.

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.

Particle localization (picking) in digital tomograms is a laborious and time-intensive step in cryogenic electron tomography (cryoET) analysis often requiring considerable user involvement, thus becoming a bottleneck for automated cryoET subtomogram averaging (STA) pipelines. In this paper, we introduce a deep learning framework called PickYOLO to tackle this problem. PickYOLO is a super-fast, universal particle detector based on the deep-learning real-time object recognition system YOLO (You Only Look Once), and tested on single particles, filamentous structures, and membrane-embedded particles. After training with the centre coordinates of a few hundred representative particles, the network automatically detects additional particles with high yield and reliability at a rate of 0.24-3.75 s per tomogram. PickYOLO can automatically detect number of particles comparable to those manually selected by experienced microscopists. This makes PickYOLO a valuable tool to substantially reduce the time and manual effort needed to analyse cryoET data for STA, greatly aiding in highresolution cryoET structure determination.

The Helmholtz-Zentrum Hereon is operating imaging beamlines for X-ray tomography (P05 IBL, P07 HEMS) for academic and industrial users at the synchrotron radiation source PETRA III at DESY in Hamburg, Germany. The high X-ray flux density and coherence of synchrotron radiation enables high-resolution in situ/operando/vivo tomography experiments and provides phase contrast, respectively. Large amounts of 3D/4D data are collected that are difficult to process and analyze. Here, we report on the application of machine learning for image segmentation including a guided interactive framework, multimodal data analysis (virtual histology), image enhancement (denoising), and self-supervised learning for phase retrieval.

Biodegradable magnesium (Mg) alloys can revolutionize osteosynthesis, because they have mechanical properties similar to those of the bone, and degrade over time, avoiding the need of removal surgery. However, they are not yet routinely applied because their degradation behavior is not fully understood. In this study we have investigated and quantified the degradation and osseointegration behavior of two biodegradable Mg alloys based on gadolinium (Gd) at high resolution. Mg-5Gd and Mg-10Gd screws were inserted in rat tibia for 4, 8 and 12 weeks. Afterward, the degradation rate and degradation homogeneity, as well as bone-to-implant interface, were studied with synchrotron radiation micro computed tomography and histology. Titanium (Ti) and polyether ether ketone (PEEK) were used as controls material to evaluate osseointegration. Our results showed that Mg-5Gd degraded faster and less homogeneously than Mg-10Gd. Both alloys gradually form a stable degradation layer at the interface and were surrounded by new bone tissue. The results were correlated to in vitro data obtained from the same material and shape. The average bone-to-implant contact of the Mg-xGd implants was comparable to that of Ti and higher than for PEEK. The results suggest that both Mg-xGd alloys are suitable as materials for bone implants.

Die genaue Segmentierung großer 3D-Volumina ist eine sehr zeitaufwendige und für die Analyse und Interpretation unabdingbare Aufgabe. Die am Synchrotron gemessene Mikrotomogramme (SRμCT) zu segmentieren, ist besonders anspruchsvoll, sowohl für algorithmische Lösungen, als auch für die Experten, da sich die Daten durch geringen Kontrast, hohe räumliche Variabilität und Messartefakte auszeichnen. Am Beispiel von 3D Tomogrammen zu Biodegradationsprozessen von Knochenimplantaten untersuchten wir die Skalierung des 2D U-Nets für hochaufgelöste Graustufenvolumina unter Verwendung von drei wichtigen Modellhyperparametern (d. h. Modellbreite, -tiefe und Eingabegröße) [1].

Recent developments in cryogenic electron microscopy (cryo-EM) have enabled structural studies of large macromolecular complexes at resolutions previously only attainable using macromolecular crystallography. Although a number of methods can already assist in de novo building of models into high-resolution cryo-EM maps, automated and reliable map interpretation remains a challenge. Presented here is a systematic study of the accuracy of models built into cryo-EM maps using ARP/wARP. It is demonstrated that the local resolution is a good indicator of map interpretability, and for the majority of the test cases ARP/wARP correctly builds 90% of main-chain fragments in regions where the local resolution is 4.0 Å or better. It is also demonstrated that the coordinate accuracy for models built into cryo-EM maps is comparable to that of X-ray crystallographic models at similar local cryo-EM and crystallographic resolutions. The model accuracy also correlates with the refined atomic displacement parameters.

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.

Highly accurate segmentation of large 3D volumes is a demanding task. Challenging applications like the segmentation of synchrotron radiation microtomograms (SRμCT) at high-resolution, which suffer from low contrast, high spatial variability and measurement artifacts, readily exceed the capacities of conventional segmentation methods, including the manual segmentation by human experts. The quantitative characterization of the osseointegration and spatio-temporal biodegradation process of bone implants requires reliable, and very precise segmentation. We investigated the scaling of 2D U-net for high resolution grayscale volumes by three crucial model hyper-parameters (i.e., the model width, depth, and input size). To leverage the 3D information of high-resolution SRμCT, common three axes prediction fusing is extended, investigating the effect of adding more than three axes prediction. In a systematic evaluation we compare the performance of scaling the U-net by intersection over union (IoU) and quantitative measurements of osseointegration and degradation parameters. Overall, we observe that a compound scaling of the U-net and multi-axes prediction fusing with soft voting yields the highest IoU for the class "degradation layer". Finally, the quantitative analysis showed that the parameters calculated with model segmentation deviated less from the high quality results than those obtained by a semi-automatic segmentation method.

The performance of automated protein model building usually decreases with resolution, mainly owing to the lower information content of the experimental data. This calls for a more elaborate use of the available structural information about macromolecules. Here, a new method is presented that uses structural homologues to improve the quality of protein models automatically constructed using ARP/wARP. The method uses local structural similarity between deposited models and the model being built, and results in longer main-chain fragments that in turn can be more reliably docked to the protein sequence. The application of the homology-based model extension method to the example of a CFA synthase at 2.7 Å resolution resulted in a more complete model with almost all of the residues correctly built and docked to the sequence. The method was also evaluated on 1493 molecular-replacement solutions at a resolution of 4.0 Å and better that were submitted to the ARP/wARP web service for model building. A significant improvement in the completeness and sequence coverage of the built models has been observed.

The remote web service for macromolecular model building using ARP/wARP [1] was established in 2004 and has had over 5,000 users.Since 2017 it has undergone a complete redesign and now offers the use of all modules of the latest ARP/wARP software version 8.0 for crystallographic model building, including interpretation of cryoelectron microscopy maps.The new web service includes advanced options for real-time monitoring, re-running computational tasks with modified parameters and a comparison of the results.The redesigned web service is gaining popularity: 900 remote users ran 9,400 model-building tasks in 2018.92% of the tasks follow a molecular replacement-like scenario where some initial model is already available.Recent developments implemented in ARP/wARP enable to build atomic structures not only in maps of a medium-to-high resolution but also within 3.0-4.0Å resolution range.Half of the users operate Mac and Linux computers and 30% use Windows.A considerable portion of users (20%) submit or monitor tasks from tablets and smartphones.The ARP/wARP web service is gradually integrated into virtual frameworks [2].Most of the tasks (58%) are submitted via the dedicated web interface.Other model-building tasks are submitted to the web service automatically from the CCP4i interface and the molecular replacement pipelines Balbes, MoRDa and MrBump.The users also have an option to direct the built ARP/wARP model to PDB-REDO.

A load frame for in situ mechanical testing is developed for the microtomography end stations at the imaging beamline P05 and the high-energy material science beamline P07 of PETRA III at DESY, both operated by the Helmholtz- Zentrum Geesthacht. The load frame is fully integrated into the beamline control system and can be controlled via a feedback loop. All relevant parameters (load, displacement, temperature, etc.) are continuously logged. It can be operated in compression or tensile mode applying forces of up to 1 kN and is compatible with all contrast modalities available at IBL and HEMS i.e. conventional attenuation contrast, propagation based phase contrast and differential phase contrast using a grating interferometer. The modularity and flexibility of the load frame allows conducting a wide range of experiments. E.g. compression tests to understand the failure mechanisms in biodegradable implants in rat bone or to investigate the mechanics and kinematics of the tessellated cartilage skeleton of sharks and rays, or tensile tests to illuminate the structure-property relationship in poplar tension wood or to visualize the 3D deformation of the tendonbone insertion. We present recent results from the experiments described including machine-learning driven volume segmentation and digital volume correlation of load tomography sequences.

The West-Life project (https://about.west-life.eu/) is a Horizon 2020 project funded by the European Commission to provide data processing and data management services for the international community of structural biologists, and in particular to support integrative experimental approaches within the field of structural biology. It has developed enhancements to existing web services for structure solution and analysis, created new pipelines to link these services into more complex higher-level workflows, and added new data management facilities. Through this work it has striven to make the benefits of European e-Infrastructures more accessible to life-science researchers in general and structural biologists in particular.

The ARP/wARP software project [1,2] includes an automated model building and refinement for macromolecular crystal structure determination.It is based on the results of two decades of extensive research and development in the areas of Xray crystallography, informatics, data mining, and statistical pattern recognition.With the use of computationally efficient methods ARP/wARP provides easy-to-use pipelines for building models of proteins and their complexes with bound nucleotides and small-molecule ligands.Here we present recent innovations of ARP/wARP that improve performance at resolutions 3.0-3.5Å and enable interpretation of cryo-electron microscopy (cryo-EM) density maps.The main-chain tracing tools for both proteins and nucleic acids have been advanced to yield more reliable models with improved local stereochemistry.A new protein side-chain docking module has been developed and now provides better performance, particularly at low resolution.This enabled a provision of a new, fully automated tool for building atomic models of proteins and nucleic acids into cryo-EM maps at resolutions better than 3.5 Å.Finally, the ARP/wARP web-server has been completely redesigned and provides a more intuitive interface to all the ARP/wARP functionalities.Most recent version of ARP/wARP and the web-service are available at http://www.

The ARP/wARP software project combines automated model building and refinement into an unified approach for macromolecular crystal structure determination. The project is based on two decades of extensive research and development in the areas of macromolecular X-ray crystallography, informatics, data mining and statistical pattern recognition. ARP/wARP collects a vast amount of computationally efficient methods and provides easy-to-use pipelines for building models of proteins, nucleotides, ligands, as well as their complexes. All methods are intuitively accessible from the ArpNavigator [1], which grants direct visualisation and real-time interaction with model building results. Structures determined using ARP/wARP include histones, hsp70, viral proteases, an insect antifreeze protein, transferases, deadenylases, synthases, kinases, photolyases and the spliceosome. The novel release of ARP/wARP, version 7.4, comes with notable innovations for determining structures at medium-to-low resolution such as exploitation of non-crystallographic symmetry, improved protocols for model update and estimation of validity of built models. Joint releases with the CCP4 suite improve software development and integration, and make the installation and updates fast and convenient for the user. A novel procedure for the automatic identification of ligands in electron density maps is introduced. It is based on the sparse parameterisation of density clusters and the matching of the pseudo-atomic grids thus created to conformationally variant ligands using mathematical descriptors of molecular shape, size and topology. The integration of the ViCi web-server for in-silico ligand-based drug design and updated stereo-chemical restraints for ligand fitting make ARP/wARP an asset for crystallographic drug discovery pipelines.

Microsymposia C26(chaperonin containing TCP-1, or TRiC) is a 1-MDa oligomer that is built by two rings comprising eight different 60-kDa subunits.This chaperonin regulates the folding of important proteins including actin, α-tubulin and β-tubulin.We used an electron density map at 5.5 Å resolution to reconstruct CCT, which showed a substrate in the inner cavities of both rings.Here we present the crystal structure of the open conformation of this nanomachine in complex with tubulin, providing information about the mechanism by which it aids tubulin folding.The structure showed that the substrate interacts with loops in the apical and equatorial domains of CCT.The organization of the ATP-binding pockets suggests that the substrate is stretched inside the cavity.Our data provide the basis for understanding the function of this chaperonin.