Macromolecular crystallography is a well established method in the field of structural biology and has led to the majority of known protein structures to date. After focusing on static structures, the method is now under development towards the investigation of protein dynamics through time-resolved methods. These experiments often require multiple handling steps of the sensitive protein crystals, e.g. for ligand-soaking and cryo-protection. These handling steps can cause significant crystal damage, and hence reduce data quality. Furthermore, in time-resolved experiments based on serial crystallography, which use micrometre-sized crystals for short diffusion times of ligands, certain crystal morphologies with small solvent channels can prevent sufficient ligand diffusion. Described here is a method that combines protein crystallization and data collection in a novel one-step process. Corresponding experiments were successfully performed as a proof-of-principle using hen egg-white lysozyme and crystallization times of only a few seconds. This method, called JINXED (Just IN time Crystallization for Easy structure Determination), promises high-quality data due to the avoidance of crystal handling and has the potential to enable time-resolved experiments with crystals containing small solvent channels by adding potential ligands to the crystallization buffer, simulating traditional co-crystallization approaches.

The Lysinibacillus sphaericus proteins Tpp49Aa1 and Cry48Aa1 can together act as a toxin toward the mosquito Culex quinquefasciatus and have potential use in biocontrol. Given that proteins with sequence homology to the individual proteins can have activity alone against other insect species, the structure of Tpp49Aa1 was solved in order to understand this protein more fully and inform the design of improved biopesticides. Tpp49Aa1 is naturally expressed as a crystalline inclusion within the host bacterium, and MHz serial femtosecond crystallography using the novel nanofocus option at an X-ray free electron laser allowed rapid and high-quality data collection to determine the structure of Tpp49Aa1 at 1.62 Å resolution. This revealed the packing of Tpp49Aa1 within these natural nanocrystals as a homodimer with a large intermolecular interface. Complementary experiments conducted at varied pH also enabled investigation of the early structural events leading up to the dissolution of natural Tpp49Aa1 crystals—a crucial step in its mechanism of action. To better understand the cooperation between the two proteins, assays were performed on a range of different mosquito cell lines using both individual proteins and mixtures of the two. Finally, bioassays demonstrated Tpp49Aa1/Cry48Aa1 susceptibility of Anopheles stephensi , Aedes albopictus, and Culex tarsalis larvae—substantially increasing the potential use of this binary toxin in mosquito control.

Serial crystallography (SX) has become an established technique for protein structure determination, especially when dealing with small or radiation-sensitive crystals and investigating fast or irreversible protein dynamics. The advent of newly developed multi-megapixel X-ray area detectors, capable of capturing over 1000 images per second, has brought about substantial benefits. However, this advancement also entails a notable increase in the volume of collected data. Today, up to 2 PB of data per experiment could be easily obtained under efficient operating conditions. The combined costs associated with storing data from multiple experiments provide a compelling incentive to develop strategies that effectively reduce the amount of data stored on disk while maintaining the quality of scientific outcomes. Lossless data-compression methods are designed to preserve the information content of the data but often struggle to achieve a high compression ratio when applied to experimental data that contain noise. Conversely, lossy compression methods offer the potential to greatly reduce the data volume. Nonetheless, it is vital to thoroughly assess the impact of data quality and scientific outcomes when employing lossy compression, as it inherently involves discarding information. The evaluation of lossy compression effects on data requires proper data quality metrics. In our research, we assess various approaches for both lossless and lossy compression techniques applied to SX data, and equally importantly, we describe metrics suitable for evaluating SX data quality.

Serial crystallography (SX) is a cutting-edge technique in structural biology, involving the systematic collection of X-ray diffraction data from numerous randomly oriented microcrystals. To extract comprehensive three-dimensional information about the studied system, SX utilises thousands of measured diffraction patterns. As such, SX takes advantages of the properties of modern X-ray sources, including Free Electron Lasers (FELs) and third and fourth generation synchrotrons, as well as contemporary high-repetition-rate detectors. Efficient analysis of the extensive datasets generated during SX experiments demands fast and effective algorithms. The FDIP library offers meticulously optimised functions tailored for preprocessing data obtained in SX experiments. This encompasses tasks such as background subtraction, identification and masking of parasitic streaks, elimination of unwanted powder diffraction (e.g., from ice or salt crystals), and pinpointing useful Bragg peaks in each diffraction pattern. The library is equipped with a user-friendly graphical interface for facile parameter adjustment tailored to specific datasets. Compatible with popular SX processing software like OnDA, Cheetah, CrystFEL, and Merge3D, the FDIP library enhances the capabilities of these tools for streamlined and precise serial crystallography analyses.

A central question in macromolecular crystallography is what X-ray free-electron laser pulse duration is required to obtain damage-free structural information. We compare serial femtosecond crystallography data from hemoglobin crystals using 3 and 10 fs pulses at comparable peak intensities (∼3 × 10 ¹⁷ W cm ⁻² ) and fixed photon energy (7.15 keV). Structural refinement produced very similar models and resolution-dependent data-quality indicators remained comparable. Both datasets also retained sufficient anomalous signal for phasing. These observations support the conclusion that high-resolution scattering was preserved under both pulse durations. Hybrid collisional–radiative and molecular-dynamics simulations show that under typical experimental conditions, atomic form-factor changes are negligible (<1%) and atomic displacements fall below the resolution limit imposed by the X-ray photon energy and the geometry of the detector. The combined experimental and theoretical results indicate that 10 fs pulses are adequate to obtain damage-free protein structures using femtosecond crystallography under the intensity conditions explored.

Serial crystallography is a rapidly developing method for the determination of the structure of biomolecules at room temperature at near-atomic resolution from an ensemble of small crystals. Numerous advances in detectors, data analysis pipelines, sample delivery methods, and crystallization protocols expand the scope of structural biology to understand the fundamental processes that take place in living cells. Many experimental strategies for serial crystallography are in use, depending on the type and sizes of the crystals or other needs of the experiment. Such strategies should ideally minimize the wastage of samples or beamtime without compromising experimental goals. This paper proposes a way to optimize beamtime utilization in serial crystallography experiments that use fixed-target sample delivery methods, such as chips. The strategy involves two key steps. Firstly, a fast raster scan of the chip is performed to determine the positions of the crystals based on their diffraction. Subsequently, a rotational series is collected at each identified crystal position, covering a narrow range of chip orientations. This approach enables the exclusion of empty positions during data acquisition, resulting in significant savings in beam time utilization and a reduced volume of measured data.