Visualization and quality assessment of the contrast transfer function estimation

Fully automated multi-grid cryoEM screening using Smart Leginon

Single-particle cryo-electron microscopy (cryoEM) is a swiftly growing method for understanding protein structure. With increasing demand for high-throughput, high-resolution cryoEM services comes greater demand for rapid and automated cryoEM grid and sample screening. During screening, optimal grids and sample conditions are identified for subsequent high-resolution data collection. Screening is a major bottleneck for new cryoEM projects because grids must be optimized for several factors, including grid type, grid hole size, sample concentration, buffer conditions, ice thickness and particle behavior. Even for mature projects, multiple grids are commonly screened to select a subset for high-resolution data collection. Here, machine learning and novel purpose-built image-processing and microscope-handling algorithms are incorporated into the automated data-collection software Leginon, to provide an open-source solution for fully automated high-throughput grid screening. This new version, broadly called Smart Leginon, emulates the actions of an operator in identifying areas on the grid to explore as potentially useful for data collection. Smart Leginon Autoscreen sequentially loads and examines grids from an automated specimen-exchange system to provide completely unattended grid screening across a set of grids. Comparisons between a multi-grid autoscreen session and conventional manual screening by 5 expert microscope operators are presented. On average, Autoscreen reduces operator time from ∼6 h to <10 min and provides a percentage of suitable images for evaluation comparable to the best operator. The ability of Smart Leginon to target holes that are particularly difficult to identify is analyzed. Finally, the utility of Smart Leginon is illustrated with three real-world multi-grid user screening/collection sessions, demonstrating the efficiency and flexibility of the software package. The fully automated functionality of Smart Leginon significantly reduces the burden on operator screening time, improves the throughput of screening and recovers idle microscope time, thereby improving availability of cryoEM services.

Emerging Themes in CryoEM─Single Particle Analysis Image Processing

Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars have contributed to the boosting of CryoEM in the past decade. This work reviews the main contributions in image processing to the current reconstruction workflow of single particle analysis (SPA) by CryoEM. Our review emphasizes the time evolution of the algorithms across the different steps of the workflow differentiating between two groups of approaches: analytical methods and deep learning algorithms. We present an analysis of the current state of the art. Finally, we discuss the emerging problems and challenges still to be addressed in the evolution of CryoEM image processing methods in SPA.

trans-Translation inhibitors bind to a novel site on the ribosome and clear Neisseria gonorrhoeae in vivo

Bacterial ribosome rescue pathways that remove ribosomes stalled on mRNAs during translation have been proposed as novel antibiotic targets because they are essential in bacteria and are not conserved in humans. We previously reported the discovery of a family of acylaminooxadiazoles that selectively inhibit trans-translation, the main ribosome rescue pathway in bacteria. Here, we report optimization of the pharmacokinetic and antibiotic properties of the acylaminooxadiazoles, producing MBX-4132, which clears multiple-drug resistant Neisseria gonorrhoeae infection in mice after a single oral dose. Single particle cryogenic-EM studies of non-stop ribosomes show that acylaminooxadiazoles bind to a unique site near the peptidyl-transfer center and significantly alter the conformation of ribosomal protein bL27, suggesting a novel mechanism for specific inhibition of trans-translation by these molecules. These results show that trans-translation is a viable therapeutic target and reveal a new conformation within the bacterial ribosome that may be critical for ribosome rescue pathways.

Processing apoferritin with the Appion pipeline

The 3DEM map challenge provided an opportunity to test different algorithms and workflows for processing single particle cryo-EM data. We were interested in testing whether we could use the standard Appion workflow with minimal manual intervention to achieve similar or better resolution than other challengers. Another question we were interested in testing was what the influence of particle sorting and elimination would be on the resolution and quality of 3D reconstructions. Since apoferritin is historically a challenging particle for single particle reconstruction and the authors of the original map challenge data used only a fraction of the particles present in the dataset, we focused on the apoferritin dataset for our entry. We submitted a 3.7 Å map from 25,844 particles and a 3.6 Å map from 53,334 particles and after assessment were among the best of the apoferritin maps that were submitted. Here we present the details of our reconstruction strategy and compare our strategy to that of another high-scoring apoferritin map. Altogether, our results suggest that for a relatively conformationally homogeneous particle like apoferritin, including as many particles as possible after elimination of junk leads to the highest resolution, and the choice of parameters for custom mask creation can lead to subtle but significant changes in the resolution of 3D reconstructions.

cisTEM, user-friendly software for single-particle image processing

We have developed new open-source software called cisTEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging. cisTEM features a graphical user interface that is used to submit jobs, monitor their progress, and display results. It implements a full processing pipeline including movie processing, image defocus determination, automatic particle picking, 2D classification, ab-initio 3D map generation from random parameters, 3D classification, and high-resolution refinement and reconstruction. Some of these steps implement newly-developed algorithms; others were adapted from previously published algorithms. The software is optimized to enable processing of typical datasets (2000 micrographs, 200 k – 300 k particles) on a high-end, CPU-based workstation in half a day or less, comparable to GPU-accelerated processing. Jobs can also be scheduled on large computer clusters using flexible run profiles that can be adapted for most computing environments. cisTEM is available for download from cistem.org.

Strategies for Automated CryoEM Data Collection Using Direct Detectors

The new generation of direct electron detectors has been a major contributor to the recent resolution revolution in cryo-electron microscopy. Optimal use of these new cameras using automated data collection software is critical for high-throughput near-atomic resolution cryo-electron microscopy research. We present an overview of the practical aspects of automated data collection in the context of this new generation of direct detectors, highlighting the differences, challenges, and opportunities the new detectors provide compared to the previous generation of data acquisition media.

Automated data collection in single particle electron microscopy

Automated data collection is an integral part of modern workflows in single particle electron microscopy (EM) research. This review surveys the software packages available for automated single particle EM data collection. The degree of automation at each stage of data collection is evaluated, and the capabilities of the software packages are described. Finally, future trends in automation are discussed.

Automated batch fiducial-less tilt-series alignment in Appion using Protomo

The field of electron tomography has benefited greatly from manual and semi-automated approaches to marker-based tilt-series alignment that have allowed for the structural determination of multitudes of in situ cellular structures as well as macromolecular structures of individual protein complexes. The emergence of complementary metal-oxide semiconductor detectors capable of detecting individual electrons has enabled the collection of low dose, high contrast images, opening the door for reliable correlation-based tilt-series alignment. Here we present a set of automated, correlation-based tilt-series alignment, contrast transfer function (CTF) correction, and reconstruction workflows for use in conjunction with the Appion/Leginon package that are primarily targeted at automating structure determination with cryogenic electron microscopy.

The influence of frame alignment with dose compensation on the quality of single particle reconstructions

As direct electron detection devices in cryo-electron microscopy become ubiquitous, the field is now ripe for new developments in image analysis techniques that take advantage of their increased SNR coupled with their high-throughput frame collection abilities. In approaching atomic resolution of native-like biomolecules, the accurate extraction of structural locations and orientations of side-chains from frames depends not only on the electron dose that a sample receives but also on the ability to accurately estimate the CTF. Here we use a new 2.8Å resolution structure of a recombinant gene therapy virus, AAV-DJ with Arixtra, imaged on an FEI Titan Krios with a DE-20 direct electron detector to probe new metrics including relative side-chain density and ResLog analysis for optimizing the compensation of electron beam damage and to characterize the factors that are limiting the resolution of the reconstruction. The influence of dose compensation on the accuracy of CTF estimation and particle classifiability are also presented. We show that rigorous dose compensation allows for better particle classifiability and greater recovery of structural information from negatively charged, electron-sensitive side-chains, resulting in a more accurate macromolecular model.