Early intermediates in bacterial RNA polymerase promoter melting visualized by time-resolved cryo-electron microscopy.

During formation of the transcription-competent open complex (RPo) by bacterial RNA polymerases (RNAP), transient intermediates pile up before overcoming a rate-limiting step. Structural descriptions of these interconversions in real time are unavailable. To address this gap, time-resolved cryo-electron microscopy (cryo-EM) was used to capture four intermediates populated 120 or 500 milliseconds (ms) after mixing Escherichia coli σ70-RNAP and the λPR promoter. Cryo-EM snapshots revealed the upstream edge of the transcription bubble unpairs rapidly, followed by stepwise insertion of two conserved nontemplate strand (nt-strand) bases into RNAP pockets. As nt-strand "read-out" extends, the RNAP clamp closes, expelling an inhibitory σ70 domain from the active-site cleft. The template strand is fully unpaired by 120 ms but remains dynamic, indicating yet unknown conformational changes load it in subsequent steps. Because these events likely describe DNA opening at many bacterial promoters, this study provides needed insights into how DNA sequence regulates steps of RPo formation.

Cryo-Electron Microscopy Screening Automation across Multiple Grids using Smart Leginon.

Advancements in cryo-electron microscopy (cryoEM) techniques over the past decade have allowed structural biologists to routinely resolve macromolecular protein complexes to near-atomic resolution. The general workflow of the entire cryoEM pipeline involves iterating between sample preparation, cryoEM grid preparation, and sample/grid screening before moving on to high-resolution data collection. Iterating between sample/grid preparation and screening is typically a major bottleneck for researchers, as every iterative experiment must optimize for sample concentration, buffer conditions, grid material, grid hole size, ice thickness, and protein particle behavior in the ice, amongst other variables. Furthermore, once these variables are satisfactorily determined, grids prepared under identical conditions vary widely in whether they are ready for data collection, so additional screening sessions prior to selecting optimal grids for high-resolution data collection are recommended. This sample/grid preparation and screening process often consumes several dozen grids and days of operator time at the microscope. Furthermore, the screening process is limited to operator/microscope availability and microscope accessibility. Here, we demonstrate how to use Leginon and Smart Leginon Autoscreen to automate the majority of cryoEM grid screening. Autoscreen combines machine learning, computer vision algorithms, and microscope-handling algorithms to remove the need for constant manual operator input. Autoscreen can autonomously load and image grids with multi-scale imaging using an automated specimen-exchange cassette system, resulting in unattended grid screening for an entire cassette. As a result, operator time for screening 12 grids may be reduced to ~10 min with Autoscreen compared to ~6 h using previous methods which are hampered by their inability to account for high variability between grids. This protocol first introduces basic Leginon setup and functionality, then demonstrates Autoscreen functionality step-by-step from the creation of a template session to the end of a 12-grid automated screening session.

Signal Transduction in an Enzymatic Photoreceptor Revealed by Cryo-Electron Microscopy.

Phytochromes are essential photoreceptor proteins in plants with homologs in bacteria and fungi that regulate a variety of important environmental responses. They display a reversible photocycle between two distinct states, the red-light absorbing Pr and the far-red light absorbing Pfr, each with its own structure. The reversible Pr to Pfr photoconversion requires covalently bound bilin chromophore and regulates the activity of a C-terminal enzymatic domain, which is usually a histidine kinase (HK). In plants, phytochromes translocate to nucleus where the C-terminal effector domain interacts with protein interaction factors (PIFs) to induce gene expression. In bacteria, the HK phosphorylates a response-regulator (RR) protein triggering downstream gene expression through a two-component signaling pathway. Although plant and bacterial phytochromes share similar structural composition, they have contrasting activity in the presence of light with most BphPs being active in the dark. The molecular mechanism that explains bacterial and plant phytochrome signaling has not been well understood due to limited structures of full-length phytochromes with enzymatic domain resolved at or near atomic resolution in both Pr and Pfr states. Here, we report the first Cryo-EM structures of a wild-type bacterial phytochrome with a HK enzymatic domain, determined in both Pr and Pfr states, between 3.75 and 4.13 Å resolution, respectively. Furthermore, we capture a distinct Pr/Pfr heterodimer of the same protein as potential signal transduction intermediate at 3.75 Å resolution. Our three Cryo-EM structures of the distinct signaling states of BphPs are further reinforced by Cryo-EM structures of the truncated PCM of the same protein determined for the Pr/Pfr heterodimer as well as Pfr state. These structures provide insight into the different light-signaling mechanisms that could explain how bacteria and plants see the light.

Automated pipelines for rapid evaluation during cryoEM data acquisition.

Cryo-electron microscopy (cryoEM) has become a popular method for determining high-resolution structures of biomolecules. However, data processing can be time-consuming, particularly for new researchers entering the field. To improve data quality and increase data collection efficiency, several software packages have been developed for on-the-fly data processing with various degrees of automation. These software packages allow researchers to perform tasks such as motion correction, CTF estimation, 2D classification, and 3D reconstruction in real-time, with minimal human input. On-the-fly data processing can not only improve data collection efficiency but also increase the productivity of instrumentation in high demand. However, the various software packages available differ in their performance, computational requirements, and levels of automation. In this review, we describe the minimal metrics used to assess data quality during data collection, outline the features of an ideal on-the-fly data processing software systems, and provide results from using three of these systems.

Structural basis for substrate selection by the SARS-CoV-2 replicase.

The SARS-CoV-2 RNA-dependent RNA polymerase coordinates viral RNA synthesis as part of an assembly known as the replication-transcription complex (RTC)1. Accordingly, the RTC is a target for clinically approved antiviral nucleoside analogues, including remdesivir2. Faithful synthesis of viral RNAs by the RTC requires recognition of the correct nucleotide triphosphate (NTP) for incorporation into the nascent RNA. To be effective inhibitors, antiviral nucleoside analogues must compete with the natural NTPs for incorporation. How the SARS-CoV-2 RTC discriminates between the natural NTPs, and how antiviral nucleoside analogues compete, has not been discerned in detail. Here, we use cryogenic-electron microscopy to visualize the RTC bound to each of the natural NTPs in states poised for incorporation. Furthermore, we investigate the RTC with the active metabolite of remdesivir, remdesivir triphosphate (RDV-TP), highlighting the structural basis for the selective incorporation of RDV-TP over its natural counterpart adenosine triphosphate3,4. Our results explain the suite of interactions required for NTP recognition, informing the rational design of antivirals. Our analysis also yields insights into nucleotide recognition by the nsp12 NiRAN (nidovirus RdRp-associated nucleotidyltransferase), an enigmatic catalytic domain essential for viral propagation5. The NiRAN selectively binds guanosine triphosphate, strengthening proposals for the role of this domain in the formation of the 5' RNA cap6.

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.

Characterizing the resolution and throughput of the Apollo direct electron detector.

Advances in electron detection have been essential to the success of high-resolution cryo-EM structure determination. A new generation of direct electron detector called the Apollo, has been developed by Direct Electron. The Apollo uses a novel event-based MAPS detector custom designed for ultra-fast electron counting. We have evaluated this new camera, finding that it delivers high detective quantum efficiency (DQE) and low coincidence loss, enabling high-quality electron counting data acquisition at up to nearly 80 input electrons per pixel per second. We further characterized the performance of Apollo for single particle cryo-EM on real biological samples. Using mouse apoferritin, Apollo yielded better than 1.9 Å resolution reconstructions at all three tested dose rates from a half-day data collection session each. With longer collection time and improved specimen preparation, mouse apoferritin was reconstructed to 1.66 Å resolution. Applied to a more challenging small protein aldolase, we obtained a 2.24 Å resolution reconstruction. The high quality of the map indicates that the Apollo has sufficiently high DQE to reconstruct smaller proteins and complexes with high-fidelity. Our results demonstrate that the Apollo camera performs well across a broad range of dose rates and is capable of capturing high quality data that produce high-resolution reconstructions for large and small single particle samples.

Recent advances in infectious disease research using cryo-electron tomography.

With the increasing spread of infectious diseases worldwide, there is an urgent need for novel strategies to combat them. Cryogenic sample electron microscopy (cryo-EM) techniques, particularly electron tomography (cryo-ET), have revolutionized the field of infectious disease research by enabling multiscale observation of biological structures in a near-native state. This review highlights the recent advances in infectious disease research using cryo-ET and discusses the potential of this structural biology technique to help discover mechanisms of infection in native environments and guiding in the right direction for future drug discovery.

Better, Faster, Cheaper: Recent Advances in Cryo-Electron Microscopy.

Cryo-electron microscopy (cryo-EM) continues its remarkable growth as a method for visualizing biological objects, which has been driven by advances across the entire pipeline. Developments in both single-particle analysis and in situ tomography have enabled more structures to be imaged and determined to better resolutions, at faster speeds, and with more scientists having improved access. This review highlights recent advances at each stageof the cryo-EM pipeline and provides examples of how these techniques have been used to investigate real-world problems, including antibody development against the SARS-CoV-2 spike during the recent COVID-19 pandemic.

Throughput and resolution with a next-generation direct electron detector.

Direct electron detectors (DEDs) have revolutionized cryo-electron microscopy (cryo-EM) by facilitating the correction of beam-induced motion and radiation damage, and also by providing high-resolution image capture. A new-generation DED, the DE64, has been developed by Direct Electron that has good performance in both integrating and counting modes. The camera has been characterized in both modes in terms of image quality, throughput and resolution of cryo-EM reconstructions. The modulation transfer function, noise power spectrum and detective quantum efficiency (DQE) were determined for both modes, as well as the number of images per unit time. Although the DQE for counting mode was superior to that for integrating mode, the data-collection throughput for this mode was more than ten times slower. Since throughput and resolution are related in single-particle cryo-EM, data for apoferritin were collected and reconstructed using integrating mode, integrating mode in conjunction with a Volta phase plate (VPP) and counting mode. Only the counting-mode data resulted in a better than 3 Šresolution reconstruction with similar numbers of particles, and this increased performance could not be compensated for by the increased throughput of integrating mode or by the increased low-frequency contrast of integrating mode with the VPP. These data show that the superior image quality provided by counting mode is more important for high-resolution cryo-EM reconstructions than the superior throughput of integrating mode.

Assessing the quality of single particle reconstructions by atomic model building.

The 2015/2016 Map Challenge challenged cryo-EM practitioners to process a series of publicly available cryo-EM datasets. As part of the challenge, metrics needed to be developed to assess and compare the quality of the different map submissions. The most common metric for assessing maps is determining the resolution by Fourier shell correlation (FSC), but there are well known instances where the resolution can be misleading. In this manuscript, we present a new approach for assessing the quality of a map by determining the map "modelability" rather than on resolution. We used the automated map tracing and modeling algorithms in Rosetta to generate populations of models, and then compared the populations between different map entries by the Rosetta score, RMSD to a reference model provided by the map challenge, and by pair-wise RMSDs between different models in the population. These metrics were used to determine statistically significant rankings for the map challengers for each dataset. The rankings revealed inconsistencies between the resolution by FSC, emphasized the importance of the interplay between number of particles contributing to a map and map quality, and revealed the importance of software familiarity on single particle reconstruction results. However, because multiple variables changed between map entries, it was challenging to derive best practices from the map challenge results.

The first single particle analysis Map Challenge: A summary of the assessments.

The recent successes of cryo-electron microscopy fostered great expectation of solving many new and previously recalcitrant biomolecular structures. However, it also brings with it the danger of compromising the validity of the outcomes if not done properly. The Map Challenge is a first step in assessing the state of the art and to shape future developments in data processing. The organizers presented seven cases for single particle reconstruction, and 27 members of the community responded with 66 submissions. Seven groups analyzed these submissions, resulting in several assessment reports, summarized here. We devised a range of analyses to evaluate the submitted maps, including visual impressions, Fourier shell correlation, pairwise similarity and interpretation through modeling. Unfortunately, we did not find strong trends. We ascribe this to the complexity of the challenge, dealing with multiple cases, software packages and processing approaches. This puts the user in the spotlight, where his/her choices becomes the determinant of map quality. The future focus should therefore be on promulgating best practices and encapsulating these in the software. Such practices include adherence to validation principles, most notably the processing of independent sets, proper resolution-limited alignment, appropriate masking and map sharpening. We consider the Map Challenge to be a highly valuable exercise that should be repeated frequently or on an ongoing basis.

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 Šmap from 25,844 particles and a 3.6 Šmap 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.