Marcel Arheit

Dynamo: a flexible, user-friendly development tool for subtomogram averaging of cryo-EM data in high-performance computing environments.

Dynamo is a new software package for subtomogram averaging of cryo Electron Tomography (cryo-ET) data with three main goals: first, Dynamo allows user-transparent adaptation to a variety of high-performance computing platforms such as GPUs or CPU clusters. Second, Dynamo implements user-friendliness through GUI interfaces and scripting resources. Third, Dynamo offers user-flexibility through a plugin API. Besides the alignment and averaging procedures, Dynamo includes native tools for visualization and analysis of results and data, as well as support for third party visualization software, such as Chimera UCSF or EMAN2. As a demonstration of these functionalities, we studied bacterial flagellar motors and showed automatically detected classes with absent and present C-rings. Subtomogram averaging is a common task in current cryo-ET pipelines, which requires extensive computational resources and follows a well-established workflow. However, due to the data diversity, many existing packages offer slight variations of the same algorithm to improve results. One of the main purposes behind Dynamo is to provide explicit tools to allow the user the insertion of custom designed procedures - or plugins - to replace or complement the native algorithms in the different steps of the processing pipeline for subtomogram averaging without the burden of handling parallelization. Custom scripts that implement new approaches devised by the user are integrated into the Dynamo data management system, so that they can be controlled by the GUI or the scripting capacities. Dynamo executables do not require licenses for third party commercial software. Sources, executables and documentation are freely distributed on http://www.dynamo-em.org.

Ligand-induced structural changes in the cyclic nucleotide-modulated potassium channel MloK1

Cyclic nucleotide-modulated ion channels are important for signal transduction and pacemaking in eukaryotes. The molecular determinants of ligand gating in these channels are still unknown, mainly because of a lack of direct structural information. Here we report ligand-induced conformational changes in full-length MloK1, a cyclic nucleotide-modulated potassium channel from the bacterium Mesorhizobium loti, analysed by electron crystallography and atomic force microscopy. Upon cAMP binding, the cyclic nucleotide-binding domains move vertically towards the membrane, and directly contact the S1–S4 voltage sensor domains. This is accompanied by a significant shift and tilt of the voltage sensor domain helices. In both states, the inner pore-lining helices are in an ‘open’ conformation. We propose a mechanism in which ligand binding can favour pore opening via a direct interaction between the cyclic nucleotide-binding domains and voltage sensors. This offers a simple mechanistic hypothesis for the coupling between ligand gating and voltage sensing in eukaryotic HCN channels.

3D reconstruction from 2D crystal image and diffraction data.

Electron crystallography of 2D protein crystals can determine the structure of membrane embedded proteins at high resolution. Images or electron diffraction patterns are recorded with the electron microscope of the frozen hydrated samples, and the 3D structure of the proteins is then determined by computer data processing. Here we introduce the image-processing algorithms for crystallographic Fourier space based methods using the Medical Research Council (MRC) programs, and illustrate the usage of the software packages 2dx, XDP, and IPLT.

2dx_automator: Implementation of a semiautomatic high-throughput high-resolution cryo-electron crystallography pipeline

The introduction of direct electron detectors (DED) to cryo-electron microscopy has tremendously increased the signal-to-noise ratio (SNR) and quality of the recorded images. We discuss the optimal use of DEDs for cryo-electron crystallography, introduce a new automatic image processing pipeline, and demonstrate the vast improvement in the resolution achieved by the use of both together, especially for highly tilted samples. The new processing pipeline (now included in the software package 2dx) exploits the high SNR and frame readout frequency of DEDs to automatically correct for beam-induced sample movement, and reliably processes individual crystal images without human interaction as data are being acquired. A new graphical user interface (GUI) condenses all information required for quality assessment in one window, allowing the imaging conditions to be verified and adjusted during the data collection session. With this new pipeline an automatically generated unit cell projection map of each recorded 2D crystal is available less than 5 min after the image was recorded. The entire processing procedure yielded a three-dimensional reconstruction of the 2D-crystallized ion-channel membrane protein MloK1 with a much-improved resolution of 5Å in-plane and 7Å in the z-direction, within 2 days of data acquisition and simultaneous processing. The results obtained are superior to those delivered by conventional photographic film-based methodology of the same sample, and demonstrate the importance of drift-correction.

Single Particle 3D Reconstruction for 2D Crystal Images of Membrane Proteins

In cases where ultra-flat cryo-preparations of well-ordered two-dimensional (2D) crystals are available, electron crystallography is a powerful method for the determination of the high-resolution structures of membrane and soluble proteins. However, crystal unbending and Fourier-filtering methods in electron crystallography three-dimensional (3D) image processing are generally limited in their performance for 2D crystals that are badly ordered or non-flat. Here we present a single particle image processing approach, which is implemented as an extension of the 2D crystallographic pipeline realized in the 2dx software package, for the determination of high-resolution 3D structures of membrane proteins. The algorithm presented, addresses the low single-to-noise ratio (SNR) of 2D crystal images by exploiting neighborhood correlation between adjacent proteins in the 2D crystal. Compared with conventional single particle processing for randomly oriented particles, the computational costs are greatly reduced due to the crystal-induced limited search space, which allows a much finer search space compared to classical single particle processing. To reduce the considerable computational costs, our software features a hybrid parallelization scheme for multi-CPU clusters and computer with high-end graphic processing units (GPUs). We successfully apply the new refinement method to the structure of the potassium channel MloK1. The calculated 3D reconstruction shows more structural details and contains less noise than the map obtained by conventional Fourier-filtering based processing of the same 2D crystal images.

Image processing of 2D crystal images.

Electron crystallography of membrane proteins uses cryo-transmission electron microscopy to image frozen-hydrated 2D crystals. The processing of recorded images exploits the periodic arrangement of the structures in the images to extract the amplitudes and phases of diffraction spots in Fourier space. However, image imperfections require a crystal unbending procedure to be applied to the image before evaluation in Fourier space. We here describe the process of 2D crystal image unbending, using the 2dx software system.

Merging of image data in electron crystallography.

Electron crystallography of membrane proteins uses cryo-transmission electron microscopy to record images and diffraction patterns of frozen-hydrated 2D crystals. Each two-dimensional (2D) crystal is only imaged once, at one specific tilt angle, and the recorded images can be automatically processed with the 2dx/MRC software package. Processed image data from non-tilted and tilted 2D crystals then need to be merged into a 3D reconstruction of the membrane protein structure. We here describe the process of the 3D merging, using the 2dx software system.

Automation of Image Processing in Electron Crystallography

Electron crystallography of membrane proteins records images and diffraction patterns of frozen-hydrated two-dimensional (2D) crystals. To reconstruct the high-resolution three-dimensional (3D) structure of a membrane protein, a multitude of images of 2D crystals have to be processed. Certain processing steps are thereby similar for batches of images that were recorded under similar conditions. Here we describe how the 2dx software package can be used to automate the processing of 2D crystal images, and how the 2D and 3D merging results can be used to iteratively reprocess the images. While the processing of 2D crystal images has been fully automated, the merging process is still semi-manual.

Analysis of 2-D Crystals of Membrane Proteins by Electron Microscopy

Membrane protein structure determination continues to be a challenging endeavor. The key steps involved in determining the three-dimensional (3-D) structure of a membrane protein from two-dimensional (2-D) crystals are the expression and purification of the protein, obtaining well-ordered 2-D crystals, preparing the 2-D crystals for electron microscopy, collecting images and electron diffraction patterns of the 2-D crystals in the electron microscope, processing the data to extract the structural information, and finally reconstructing the 3-D structure. This review discusses these individual steps of electron crystallographic structure determination, highlighting the bottlenecks that can be encountered, and describing recent advances.