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17 items found (0 items not approved), displaying 1 to 10.[First/Prev] 1, 2 [Next/Last]

Instruments / Technical Area	Publication Details	Published
Krios I-Titan Krios I at Diamond	Investigation of the milling characteristics of different focused-ion-beam sources assessed by three-dimensional electron diffraction from crystal lamellae James M. Parkhurst , Adam D. Crawshaw , C. Alistair Siebert , Maud Dumoux , C. David Owen , Pedro Nunes , David Waterman , Thomas Glen , David I. Stuart , James H. Naismith , Gwyndaf Evans Iucrj 10 DOI: 10.1107/S2052252523001902 Open Access Show Abstract ▼ Abstract: Three-dimensional electron diffraction (3DED) from nanocrystals of biological macromolecules requires the use of very small crystals. These are typically less than 300 nm-thick in the direction of the electron beam due to the strong interaction between electrons and matter. In recent years, focused-ion-beam (FIB) milling has been used in the preparation of thin samples for 3DED. These instruments typically use a gallium liquid metal ion source. Inductively coupled plasma (ICP) sources in principle offer faster milling rates. Little work has been done to quantify the damage these sources cause to delicate biological samples at cryogenic temperatures. Here, an analysis of the effect that milling with plasma FIB (pFIB) instrumentation has on lysozyme crystals is presented. This work evaluates both argon and xenon plasmas and compares them with crystals milled with a gallium source. A milling protocol was employed that utilizes an overtilt to produce wedge-shaped lamellae with a shallow thickness gradient which yielded very thin crystalline samples. 3DED data were then acquired and standard data-processing statistics were employed to assess the quality of the diffraction data. An upper bound to the depth of the pFIB-milling damage layer of between 42.5 and 50 nm is reported, corresponding to half the thickness of the thinnest lamellae that resulted in usable diffraction data. A lower bound of between 32.5 and 40 nm is also reported, based on a literature survey of the minimum amount of diffracting material required for 3DED.	May 2023
	Parakeet: a digital twin software pipeline to assess the impact of experimental parameters on tomographic reconstructions for cryo-electron tomography James M. Parkhurst , Maud Dumoux , Mark Basham , Daniel Clare , C. Alistair Siebert , Trond Varslot , Angus Kirkland , James H. Naismith , Gwyndaf Evans Open Biology 11 DOI: 10.1098/rsob.210160 Open Access Show Abstract ▼ Abstract: In cryo-electron tomography (cryo-ET) of biological samples, the quality of tomographic reconstructions can vary depending on the transmission electron microscope (TEM) instrument and data acquisition parameters. In this paper, we present Parakeet, a ‘digital twin’ software pipeline for the assessment of the impact of various TEM experiment parameters on the quality of three-dimensional tomographic reconstructions. The Parakeet digital twin is a digital model that can be used to optimize the performance and utilization of a physical instrument to enable in silico optimization of sample geometries, data acquisition schemes and instrument parameters. The digital twin performs virtual sample generation, TEM image simulation, and tilt series reconstruction and analysis within a convenient software framework. As well as being able to produce physically realistic simulated cryo-ET datasets to aid the development of tomographic reconstruction and subtomogram averaging programs, Parakeet aims to enable convenient assessment of the effects of different microscope parameters and data acquisition parameters on reconstruction quality. To illustrate the use of the software, we present the example of a quantitative analysis of missing wedge artefacts on simulated planar and cylindrical biological samples and discuss how data collection parameters can be modified for cylindrical samples where a full 180° tilt range might be measured.	Oct 2021
B24-Cryo Soft X-ray Tomography	Single cell cryo-soft X-ray tomography shows that each Chlamydia trachomatis inclusion is a unique community of bacteria Patrick Phillips , James M. Parkhurst , Ilias Kounatidis , Chidinma Okolo , Thomas M. Fish , James H. Naismith , Martin A. Walsh , Maria Harkiolaki , Maud Dumoux Life 11 DOI: 10.3390/life11080842 Open Access Show Abstract ▼ Abstract: Chlamydiae are strict intracellular pathogens residing within a specialised membrane-bound compartment called the inclusion. Therefore, each infected cell can, be considered as a single entity where bacteria form a community within the inclusion. It remains unclear as to how the population of bacteria within the inclusion influences individual bacterium. The life cycle of Chlamydia involves transitioning between the invasive elementary bodies (EBs) and replicative reticulate bodies (RBs). We have used cryo-soft X-ray tomography to observe individual inclusions, an approach that combines 40 nm spatial resolution and large volume imaging (up to 16 µm). Using semi-automated segmentation pipeline, we considered each inclusion as an individual bacterial niche. Within each inclusion, we identifyed and classified different forms of the bacteria and confirmed the recent finding that RBs have a variety of volumes (small, large and abnormal). We demonstrate that the proportions of these different RB forms depend on the bacterial concentration in the inclusion. We conclude that each inclusion operates as an autonomous community that influences the characteristics of individual bacteria within the inclusion.	Aug 2021
Krios I-Titan Krios I at Diamond	A workflow for protein structure determination from thin crystal lamella by micro-electron diffraction Emma V. Beale , David G. Waterman , Corey Hecksel , Jason Van Rooyen , James B. Gilchrist , James M. Parkhurst , Felix De Haas , Bart Buijsse , Gwyndaf Evans , Peijun Zhang Frontiers In Molecular Biosciences 7 DOI: 10.3389/fmolb.2020.00179 Diamond Proposal Number(s): [23169] Open Access Show Abstract ▼ Abstract: MicroED has recently emerged as a powerful method for the analysis of biological structures at atomic resolution. This technique has been largely limited to protein nanocrystals which grow either as needles or plates measuring only a few hundred nanometers in thickness. Furthermore, traditional microED data processing uses established X-ray crystallography software that is not optimized for handling compound effects that are unique to electron diffraction data. Here, we present an integrated workflow for microED, from sample preparation by cryo-focused ion beam milling, through data collection with a standard Ceta-D detector, to data processing using the DIALS software suite, thus enabling routine atomic structure determination of protein crystals of any size and shape using microED. We demonstrate the effectiveness of the workflow by determining the structure of proteinase K to 2.0 Å resolution and show the advantage of using protein crystal lamellae over nanocrystals.	Aug 2020
	Scaling diffraction data in the DIALS software package: algorithms and new approaches for multi-crystal scaling James Beilsten-Edmands , Graeme Winter , Richard Gildea , James Parkhurst , David Waterman , Gwyndaf Evans Acta Crystallographica Section D Structural Biology 76, 385 - 399 DOI: 10.1107/S2059798320003198 Open Access Show Abstract ▼ Abstract: In processing X-ray diffraction data, the intensities obtained from integration of the diffraction images must be corrected for experimental effects in order to place all intensities on a common scale both within and between data collections. Scaling corrects for effects such as changes in sample illumination, absorption and, to some extent, global radiation damage that cause the measured intensities of symmetry-equivalent observations to differ throughout a data set. This necessarily requires a prior evaluation of the point-group symmetry of the crystal. This paper describes and evaluates the scaling algorithms implemented within the DIALS data-processing package and demonstrates the effectiveness and key features of the implementation on example macromolecular crystallographic rotation data. In particular, the scaling algorithms enable new workflows for the scaling of multi-crystal or multi-sweep data sets, providing the analysis required to support current trends towards collecting data from ever-smaller samples. In addition, the implementation of a free-set validation method is discussed, which allows the quantification of the suitability of scaling-model and algorithm choices.	Apr 2020
I03-Macromolecular Crystallography I04-1-Macromolecular Crystallography (fixed wavelength) I04-Macromolecular Crystallography I24-Microfocus Macromolecular Crystallography	The predictive power of data-processing statistics Melanie Vollmar , James M. Parkhurst , Dominic Jaques , Arnaud Basle , Garib N. Murshudov , David G. Waterman , Gwyndaf Evans Iucrj 7, 342 - 354 DOI: 10.1107/S2052252520000895 Open Access Show Abstract ▼ Abstract: This study describes a method to estimate the likelihood of success in determining a macromolecular structure by X-ray crystallography and experimental single-wavelength anomalous dispersion (SAD) or multiple-wavelength anomalous dispersion (MAD) phasing based on initial data-processing statistics and sample crystal properties. Such a predictive tool can rapidly assess the usefulness of data and guide the collection of an optimal data set. The increase in data rates from modern macromolecular crystallography beamlines, together with a demand from users for real-time feedback, has led to pressure on computational resources and a need for smarter data handling. Statistical and machine-learning methods have been applied to construct a classifier that displays 95% accuracy for training and testing data sets compiled from 440 solved structures. Applying this classifier to new data achieved 79% accuracy. These scores already provide clear guidance as to the effective use of computing resources and offer a starting point for a personalized data-collection assistant.	Mar 2020
	Improving signal strength in serial crystallography with DIALS geometry refinement Aaron S. Brewster , David G. Waterman , James Parkhurst , Richard J. Gildea , Iris D. Young , Lee J. O'Riordan , Junko Yano , Graeme Winter , Gwyndaf Evans , Nicholas K. Sauter Acta Crystallographica Section D Structural Biology 74, 877 - 894 DOI: 10.1107/S2059798318009191 Open Access Show Abstract ▼ Abstract: The DIALS diffraction-modeling software package has been applied to serial crystallography data. Diffraction modeling is an exercise in determining the experimental parameters, such as incident beam wavelength, crystal unit cell and orientation, and detector geometry, that are most consistent with the observed positions of Bragg spots. These parameters can be refined by nonlinear least-squares fitting. In previous work, it has been challenging to refine both the positions of the sensors (metrology) on multipanel imaging detectors such as the CSPAD and the orientations of all of the crystals studied. Since the optimal models for metrology and crystal orientation are interdependent, alternate cycles of panel refinement and crystal refinement have been required. To simplify the process, a sparse linear algebra technique for solving the normal equations was implemented, allowing the detector panels to be refined simultaneously against the diffraction from thousands of crystals with excellent computational performance. Separately, it is shown how to refine the metrology of a second CSPAD detector, positioned at a distance of 2.5 m from the crystal, used for recording low-angle reflections. With the ability to jointly refine the detector position against the ensemble of all crystals used for structure determination, it is shown that ensemble refinement greatly reduces the apparent nonisomorphism that is often observed in the unit-cell distributions from still-shot serial crystallography. In addition, it is shown that batching the images by timestamp and re-refining the detector position can realistically model small, time-dependent variations in detector position relative to the sample, and thereby improve the integrated structure-factor intensity signal and heavy-atom anomalous peak heights.	Sep 2018
Data acquisition	Electron diffraction data processing with DIALS Max T. B. Clabbers , Tim Gruene , James M. Parkhurst , Jan Pieter Abrahams , David G. Waterman Acta Crystallographica Section D Structural Biology 74, 506 - 518 DOI: 10.1107/S2059798318007726 Open Access Show Abstract ▼ Abstract: Electron diffraction is a relatively novel alternative to X-ray crystallography for the structure determination of macromolecules from three-dimensional nanometre-sized crystals. The continuous-rotation method of data collection has been adapted for the electron microscope. However, there are important differences in geometry that must be considered for successful data integration. The wavelength of electrons in a TEM is typically around 40 times shorter than that of X-rays, implying a nearly flat Ewald sphere, and consequently low diffraction angles and a high effective sample-to-detector distance. Nevertheless, the DIALS software package can, with specific adaptations, successfully process continuous-rotation electron diffraction data. Pathologies encountered specifically in electron diffraction make data integration more challenging. Errors can arise from instrumentation, such as beam drift or distorted diffraction patterns from lens imperfections. The diffraction geometry brings additional challenges such as strong correlation between lattice parameters and detector distance. These issues are compounded if calibration is incomplete, leading to uncertainty in experimental geometry, such as the effective detector distance and the rotation rate or direction. Dynamic scattering, absorption, radiation damage and incomplete wedges of data are additional factors that complicate data processing. Here, recent features of DIALS as adapted to electron diffraction processing are shown, including diagnostics for problematic diffraction geometry refinement, refinement of a smoothly varying beam model and corrections for distorted diffraction images. These novel features, combined with the existing tools in DIALS, make data integration and refinement feasible for electron crystallography, even in difficult cases.	Jun 2018
I19-Small Molecule Single Crystal Diffraction	DIALS : implementation and evaluation of a new integration package Graeme Winter , David G. Waterman , James M. Parkhurst , Aaron S. Brewster , Richard J. Gildea , Markus Gerstel , Luis Fuentes-Montero , Melanie Vollmar , Tara Michels-Clark , Iris D. Young , Nicholas K. Sauter , Gwyndaf Evans Acta Crystallographica Section D Structural Biology 74, 85 - 97 DOI: 10.1107/S2059798317017235 Open Access Show Abstract ▼ Abstract: The DIALS project is a collaboration between Diamond Light Source, Lawrence Berkeley National Laboratory and CCP4 to develop a new software suite for the analysis of crystallographic X-ray diffraction data, initially encompassing spot finding, indexing, refinement and integration. The design, core algorithms and structure of the software are introduced, alongside results from the analysis of data from biological and chemical crystallography experiments.	Feb 2018
	Background modelling of diffraction data in the presence of ice rings James M. Parkhurst , Andrea Thorn , Melanie Vollmar , Graeme Winter , David G. Waterman , Luis Fuentes-Montero , Richard J. Gildea , Garib N. Murshudov , Gwyndaf Evans Iucrj 4 DOI: 10.1107/S2052252517010259 Open Access Show Abstract ▼ Abstract: An algorithm for modelling the background for each Bragg reflection in a series of X-ray diffraction images containing Debye–Scherrer diffraction from ice in the sample is presented. The method involves the use of a global background model which is generated from the complete X-ray diffraction data set. Fitting of this model to the background pixels is then performed for each reflection independently. The algorithm uses a static background model that does not vary over the course of the scan. The greatest improvement can be expected for data where ice rings are present throughout the data set and the local background shape at the size of a spot on the detector does not exhibit large time-dependent variation. However, the algorithm has been applied to data sets whose background showed large pixel variations (variance/mean > 2) and has been shown to improve the results of processing for these data sets. It is shown that the use of a simple flat-background model as in traditional integration programs causes systematic bias in the background determination at ice-ring resolutions, resulting in an overestimation of reflection intensities at the peaks of the ice rings and an underestimation of reflection intensities either side of the ice ring. The new global background-model algorithm presented here corrects for this bias, resulting in a noticeable improvement in R factors following refinement.	Sep 2017

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