In the era of single-particle cryogenic electron microscopy (cryo-EM) and AI-driven protein structure prediction, obtaining high-resolution protein structures, either experimentally or computationally, has become increasingly routine. Yet studying and understanding protein dynamics remains challenging. In single-particle cryo-EM, protein dynamics are most obviously manifested as poor local resolution or disappearing densities in specific regions of a reconstruction. No method is yet available to computationally generate conformational ensembles that fully deconvolute these experimental observations. When dynamics are key to understanding protein function, it is clear to us that introducing new experimental approaches is necessary to close this gap and make sense of invisible densities in single-particle cryo-EM.

The systematic comparison of 3D-ED methods in terms of data quality presented by Schmitt et al. [IUCrJ (2026), 13, https://doi.org/10.1107/S2052252526003155] is discussed.

Understanding structure at the atomic scale is fundamental for understanding the functioning and the development of materials with improved properties. Compared with other probes providing atomic resolution, electrons offer the strongest interaction in combination with minimal radiation damage, which makes them an ideal tool for investigating very small and radiation-sensitive samples [Henderson (1995), Q. Rev. Biophys. 28, 171-193]. However, these benefits are often offset by the laborious preparation of nanometre-sized samples that are not visible using a light microscope, and the fact that experiments are largely restricted to ultra-high vacuum [Duyvesteyn et al. (2018), Proc. Natl Acad. Sci. USA 115, 9569-9573; Gruene et al. (2021), Nat. Rev. Chem. 5, 660-668]. Here, we report the successful implementation of MeV electron diffraction for ab initio 3D structure determination of the quasi-2D material muscovite and the quantum material 1T-TaS2 at atomic resolution. By employing ultrashort electron pulses from the REGAE (Relativistic electron gun for atomic exploration) accelerator, we obtained high-quality diffraction datasets suitable for structural refinements based on dynamical scattering theory, enabling precise localization of even hydrogen atoms. The increased penetration depth of MeV electrons significantly expands the applicable thickness range of samples, overcoming previous restrictions associated with traditional electron diffraction. These findings establish MeV electron diffraction as a viable approach for investigating a broad range of materials, including nanostructures and radiation-sensitive compounds, and open up new opportunities for in situ and time-resolved experiments [Chao et al. (2023), Chem. Rev. 123, 8347-8394; Filippetto et al. (2022), Rev. Mod. Phys. 94, 045004].

The Volta phase plate (VPP) can enhance low-frequency phase contrast in cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET), but its impact on tomogram alignment has not been systematically assessed. Using sub-2 Å single-particle analysis (SPA) and analytical contrast transfer function (CTF) modeling, we show that despite high-frequency information loss and moderate signal damping, the VPP enhances signal in low-frequency bands that are crucial for tilt-series alignment. We show that VPP tomograms exhibit increased contrast and remain higher in contrast post denoising, for thick and crowded specimens. Quantitative comparison of tomograms acquired with and without the VPP shows improved tilt-axis orientation measurements and a higher fraction of tomograms amenable to local tilt-series alignment. Although acquisition with the VPP yields lower subtomogram averaging (STA) resolution, these results show that the primary benefits of the VPP for cryo-ET are contrast enhancement and improved tilt-series alignment robustness, which are crucial for studying cellular ultrastructure and protein organization in crowded environments, where STA at moderate resolutions remains valuable.

The complement system is a blood-based immune network that plays a crucial role in fighting infection and maintaining immune homeostasis. The membrane attack complex (MAC) is a pore assembled from complement proteins that creates holes in cells when the immune system is activated. Over the last ten years, advances in cryo-electron microscopy (cryo-EM) have enabled key molecular insights into how the MAC assembles, remodels membranes and is regulated. These new tools revealed the inherent flexibility of complement complexes. By adapting computational approaches that disentangle diverse conformations, these studies have provided detailed mechanisms for MAC activity that could underpin novel complement-targeted therapeutics. Now accelerated by AI-driven image analysis and advances in structural cell biology, the next revolution in cryo-EM offers new opportunities to understand the cellular consequences of immune activation.

Sustaining public investment in neutron and photon science facilities demands breakthrough results comparable to a Higgs moment. Harnessing AI across their accumulated experimental data and collaborative programmes is what makes that possible.

Lytic transglycosylases (LTs) play a central role in bacterial cell wall remodeling by cleaving the β-1,4-glycosidic bond in peptidoglycan via a non-hydrolytic mechanism, producing 1,6-anhydroMurNAc termini crucial for recycling and signaling. Among LTs, membrane-bound lytic transglycosylase B (MltB) contributes to peptidoglycan turnover, antibiotic resistance and protein-protein interactions. Despite its importance, the structural basis of MltB function in Acinetobacter baumannii, a multidrug-resistant pathogen, remains unclear. Here, we report the crystal structure of abMltB at 1.79 Å resolution. abMltB adopts a monomeric structure comprising three domains: an N-terminal domain (NTD), a catalytic domain (CD) and a C-terminal domain (CTD). The NTD connects to the CD via a flexible loop that partially occludes the active site, forming a tunnel-like cavity. Comparative analysis with homologous enzymes such as SltB1 and Slt35 reveals conserved catalytic residues, including Glu129 and key aromatic residues, while the CTD in abMltB adopts a distinct orientation. Notably, although calcium ions stabilize related enzymes, no metal binding was observed in abMltB. These findings highlight conserved mechanistic features and unique structural adaptations of abMltB, offering insight into its functional role in A. baumannii and potential as a novel antimicrobial target.

Three-dimensional electron diffraction (3D ED) has become increasingly popular over the last two decades, challenging the limits of established single-crystal X-ray diffraction experiments. In particular, continuous-rotation and precession-assisted protocols have been established as important tools in the collection of electron diffraction data, and the data for most of the crystal structures solved by 3D ED nowadays are acquired with one of these two methods. This is particularly true for ceramic materials, where 3D ED allows deep insights into complex structure-property relationships. As ceramic syntheses tend to yield thick and highly crystalline particles, one issue in the refinement against electron diffraction data is the effect of coherent inelastic scattering. While dynamical refinement procedures allow the simulation of multiple scattering events, in general they ignore the inelastic contribution. This work aims to evaluate the impact of dynamical inelastic effects on the diffraction data of ceramics and how their overall quality depends on the measurement strategy used. This was done by comparing the structure models derived from the same crystals under similar experimental conditions of three ceramic compounds, namely NATP [Na1+xAlxTi2-x(PO4)3], LATP [Li2-xAlxTi2-x(PO3)4] and (Fe3Al2[SiO4]3), based on precession, continuous-rotation and stepwise static tilt data. The different methods allowed the detection of low-occupancy sites in the difference electrostatic potential maps corresponding to mobile sodium and lithium ions, paving the way for future studies on their migration behaviour in solid-state electrolytes.

Interest in electron diffraction (ED) for structural characterization of both proteins and small molecules has grown significantly over the last decade. While ab initio phasing methods remain the gold standard for ED data from small-molecule samples, radiation beam damage during data collection and poor crystallinity of the nanocrystalline sample can make this method unfeasible - particularly for challenging molecules that exhibit conformational flexibility. Molecular replacement (MR) is the most commonly used phasing method for protein ED data and can circumnavigate issues related to diminished data quality. However, its application to small molecules has been limited due to the lack of methods for generating optimal trial conformations. Herein, a high-throughput automated molecular replacement workflow has been developed to solve a novel ED structure of corilagin, a macrocyclic gallotannin with pharmaceutical relevance, which could not be solved with ab initio phasing. The method was validated against three similar macrocycles with known structures (paritaprevir-α, paritaprevir-β and grazoprevir) at varying data resolution limits (1.0, 1.2, 1.4, 1.5, 1.6, 1.8 and 2.0 Å). At all these resolutions for all three structures, the developed workflow was successful and produced solutions with R factors and RMSD values within acceptable limits of the ab initio solved structure.

We demonstrate a grazing-incidence X-ray platform that simultaneously records time-resolved grazing-incidence small-angle X-ray scattering (GISAXS) and grazing-incidence X-ray diffraction (GID) from a femtosecond-laser-irradiated gold film above the melting threshold, with picosecond resolution using an X-ray free-electron laser (XFEL). By tuning the X-ray incidence angle, the probe depth is set to tens of nanometres, enabling depth-selective sensitivity to near-surface dynamics. GISAXS resolves ultrafast changes in surface nanomorphology (correlation length, roughness), while GID quantifies subsurface lattice compression, grain orientation, melting and recrystallization. The approach overcomes photon-flux limitations of synchrotron grazing-incidence geometries and provides stringent, time-resolved benchmarks for complex theoretical models of ultrafast laser-matter interaction and warm dense matter. Looking ahead, the same depth-selective methodology is well suited to inertial confinement fusion (ICF): it can visualize buried-interface perturbations and interfacial thermal resistance on micron to sub-micron scales that affect instability seeding and burn propagation.