Novel applications of Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs) in the analysis of ultrafast electron diffraction (UED) images

We employ generative adversarial networks (GANs) and convolutional neural networks (CNNs) in the study of ultrafast electron diffraction images. We propose a machine learning approach that employs a GAN to convert experimental images into idealized diffraction patterns from which information is extracted via a CNN trained on synthetic data only. We validate this approach on ultrafast electron diffraction (UED) data of bismuth samples undergoing thermalization upon excitation via 800 nm laser pulses. The network was able to predict transient temperatures with a deviation of less than 6% from analytically estimated values. Notably, this performance was achieved on a dataset of 408 images only. We believe employing this network in experimental settings where high volumes of visual data are collected, such as beam lines, could provide insights into the structural dynamics of different samples

Resolving polymorphs and radiation-driven effects in microcrystals using fixed-target serial synchrotron crystallography

The ability to determine high-quality, artefact-free structures is a challenge in micro-crystallography, and the rapid onset of radiation damage and requirement for a high-brilliance X-ray beam mean that a multi-crystal approach is essential. However, the combination of crystal-to-crystal variation and X-ray-induced changes can make the formation of a final complete data set challenging; this is particularly true in the case of metalloproteins, where X-ray-induced changes occur rapidly and at the active site. An approach is described that allows the resolution, separation and structure determination of crystal polymorphs, and the tracking of radiation damage in microcrystals. Within the microcrystal population of copper nitrite reductase, two polymorphs with different unit-cell sizes were successfully separated to determine two independent structures, and an X-ray-driven change between these polymorphs was followed. This was achieved through the determination of multiple serial structures from microcrystals using a high-throughput high-speed fixed-target approach coupled with robust data processing

A modular and compact portable mini-endstation for high-precision, high-speed fixed target serial crystallography at FEL and synchrotron sources

The design and implementation of a compact and portable sample alignment system suitable for use at both synchrotron and free-electron laser (FEL) sources and its performance are described. The system provides the ability to quickly and reliably deliver large numbers of samples using the minimum amount of sample possible, through positioning of fixed target arrays into the X-ray beam. The combination of high-precision stages, high-quality sample viewing, a fast controller and a software layer overcome many of the challenges associated with sample alignment. A straightforward interface that minimizes setup and sample changeover time as well as simplifying communication with the stages during the experiment is also described, together with an intuitive naming convention for defining, tracking and locating sample positions. The setup allows the precise delivery of samples in predefined locations to a specific position in space and time, reliably and simply

Capturing Functionally Relevant Protein Motions at the Atomic Level: Femtosecond Time Resolved Serial Crystallography of Ligand Dissociation of Carboxy-Myoglobin

The recent advent of X-Ray free electron lasers with highest brilliance and femtosecond pulses opens new possibilities for time-resolved protein crystallography [Miller, R.J.D, Science, 2014, 343, 1108-1116]. A fundamental biophysical question becomes accessible experimentally now: The investigation of protein dynamics with all atomic resolution on the shortest biochemically relevant timescale around 100 fs. Here is where bond-breaking events occur, which in turn translate into secondary and tertiary structure changes and cause a protein to fulfill its function over a wide range of timescales

Fixed-target serial oscillation crystallography at room temperature

A fixed-target approach to high-throughput room-temperature serial synchrotron crystallography with oscillation is described. Patterned silicon chips with microwells provide high crystal-loading density with an extremely high hit rate. The microfocus, undulator-fed beamline at CHESS, which has compound refractive optics and a fast-framing detector, was built and optimized for this experiment. The high-throughput oscillation method described here collects 1–5° of data per crystal at room temperature with fast (10° s−1) oscillation rates and translation times, giving a crystal-data collection rate of 2.5 Hz. Partial datasets collected by the oscillation method at a storage-ring source provide more complete data per crystal than still images, dramatically lowering the total number of crystals needed for a complete dataset suitable for structure solution and refinement – up to two orders of magnitude fewer being required. Thus, this method is particularly well suited to instances where crystal quantities are low. It is demonstrated, through comparison of first and last oscillation images of two systems, that dose and the effects of radiation damage can be minimized through fast rotation and low angular sweeps for each crystal