Single-particle cryo-electron microscopy final particle stacks and .star files from TSHR complexes
Ontology highlight
ABSTRACT:
SUBMITTER: Aashish Manglik
PROVIDER: EMPIAR-11120 | biostudies-other |
REPOSITORIES: biostudies-other
Publications
Autoantibody mimicry of hormone action at the thyrotropin receptor.
Faust Bryan B Billesbølle Christian B CB Suomivuori Carl-Mikael CM Singh Isha I Zhang Kaihua K Hoppe Nicholas N Pinto Antonio F M AFM Diedrich Jolene K JK Muftuoglu Yagmur Y Szkudlinski Mariusz W MW Saghatelian Alan A Dror Ron O RO Cheng Yifan Y Manglik Aashish A
Nature 20220808 7928
Thyroid hormones are vital in metabolism, growth and development<sup>1</sup>. Thyroid hormone synthesis is controlled by thyrotropin (TSH), which acts at the thyrotropin receptor (TSHR)<sup>2</sup>. In patients with Graves' disease, autoantibodies that activate the TSHR pathologically increase thyroid hormone activity<sup>3</sup>. How autoantibodies mimic thyrotropin function remains unclear. Here we determined cryo-electron microscopy structures of active and inactive TSHR. In inactive TSHR, th ...[more]
Similar Datasets
Project description: Not available
| EMPIAR-10786 | biostudies-other
Project description:Cryo-electron microscopy (cryo-EM) of single-particle specimens is used to determine the structure of proteins and macromolecular complexes without the need for crystals. Recent advances in detector technology and software algorithms now allow images of unprecedented quality to be recorded and structures to be determined at near-atomic resolution. However, compared with X-ray crystallography, cryo-EM is a young technique with distinct challenges. This primer explains the different steps and considerations involved in structure determination by single-particle cryo-EM to provide an overview for scientists wishing to understand more about this technique and the interpretation of data obtained with it, as well as a starting guide for new practitioners.
| S-EPMC4409659 | biostudies-literature
Project description:Automated data acquisition is used widely for single-particle reconstruction of three-dimensional (3D) volumes of biological complexes preserved in vitreous ice and imaged in a transmission electron microscope. Automation has become integral to this method because of the very large number of particle images required in order to overcome the typically low signal-to-noise ratio of these images. For optimal efficiency, automated data acquisition software packages typically employ some beam-image shift targeting as this method is both fast and accurate (±0.1?µm). In contrast, using only stage movement, relocation to a targeted area under low-dose conditions can only be achieved in combination with multiple iterations or long relaxation times, both reducing efficiency. Nevertheless it is well known that applying beam-image shift induces beam-tilt and with it a potential structure phase error with a phase error ?/4 the highest acceptable value. This theory has been used as an argument against beam-image shift for high resolution data collection. Nevertheless, in practice many small beam-image shift datasets have resulted in 3D reconstructions beyond the ?/4 phase error limit. To address this apparent contradiction, we performed cryo-EM single-particle reconstructions on a T20S proteasome sample using applied beam-image shifts corresponding to beam tilts from 0 to 10 mrad. To evaluate the results we compared the FSC values, and examined the water density peaks in the 3D map. We conclude that the phase error does not limit the validity of the 3D reconstruction from single-particle averaging beyond the ?/4 resolution limit.
| S-EPMC6163078 | biostudies-literature
Project description:In recent years, an abundance of new molecular structures have been elucidated using cryo-electron microscopy (cryo-EM), largely due to advances in hardware technology and data processing techniques. Owing to these new exciting developments, cryo-EM was selected by Nature Methods as Method of the Year 2015, and the Nobel Prize in Chemistry 2017 was awarded to three pioneers in the field. The main goal of this article is to introduce the challenging and exciting computational tasks involved in reconstructing 3-D molecular structures by cryo-EM. Determining molecular structures requires a wide range of computational tools in a variety of fields, including signal processing, estimation and detection theory, high-dimensional statistics, convex and non-convex optimization, spectral algorithms, dimensionality reduction, and machine learning. The tools from these fields must be adapted to work under exceptionally challenging conditions, including extreme noise levels, the presence of missing data, and massively large datasets as large as several Terabytes. In addition, we present two statistical models: multi-reference alignment and multi-target detection, that abstract away much of the intricacies of cryo-EM, while retaining some of its essential features. Based on these abstractions, we discuss some recent intriguing results in the mathematical theory of cryo-EM, and delineate relations with group theory, invariant theory, and information theory.
| S-EPMC7213211 | biostudies-literature
Project description:Here we present for the first time a three-dimensional cryo-EM map of the Saccharomyces cerevisiae respiratory supercomplex composed of dimeric complex III flanked on each side by one monomeric complex IV. A precise fit of the existing atomic x-ray structures of complex III from yeast and complex IV from bovine heart into the cryo-EM map resulted in a pseudo-atomic model of the three-dimensional structure for the supercomplex. The distance between cytochrome c binding sites of complexes III and IV is about 6 nm, which supports proposed channeling of cytochrome c between the individual complexes. The opposing surfaces of complexes III and IV differ considerably from those reported for the bovine heart supercomplex as determined by cryo-EM. A closer association between the individual complex domains at the aqueous membrane interface and larger spaces between the membrane-embedded domains where lipid molecules may reside are also demonstrated. The supercomplex contains about 50 molecules of cardiolipin (CL) with a fatty acid composition identical to that of the inner membrane CL pool, consistent with CL-dependent stabilization of the supercomplex.
| S-EPMC3391107 | biostudies-literature
Project description:SPHIRE (SPARX for High-Resolution Electron Microscopy) is a novel open-source, user-friendly software suite for the semi-automated processing of single particle electron cryo-microscopy (cryo-EM) data. The protocol presented here describes in detail how to obtain a near-atomic resolution structure starting from cryo-EM micrograph movies by guiding users through all steps of the single particle structure determination pipeline. These steps are controlled from the new SPHIRE graphical user interface and require minimum user intervention. Using this protocol, a 3.5 Å structure of TcdA1, a Tc toxin complex from Photorhabdus luminescens, was derived from only 9500 single particles. This streamlined approach will help novice users without extensive processing experience and a priori structural information, to obtain noise-free and unbiased atomic models of their purified macromolecular complexes in their native state.
| S-EPMC5607996 | biostudies-literature
Project description:Correct reconstruction of macromolecular structure by cryo-electron microscopy (cryo-EM) relies on accurate determination of the orientation of single-particle images. For small (<100 kDa) DNA-binding proteins, obtaining particle images with sufficiently asymmetric features to correctly guide alignment is challenging. We apply DNA origami to construct molecular goniometers-instruments that precisely orient objects-and use them to dock a DNA-binding protein on a double-helix stage that has user-programmable tilt and rotation angles. We construct goniometers with 14 different stage configurations to orient and visualize the protein just above the cryo-EM grid surface. Each goniometer has a distinct barcode pattern that we use during particle classification to assign angle priors to the bound protein. We use goniometers to obtain a 6.5-Å structure of BurrH, an 82-kDa DNA-binding protein whose helical pseudosymmetry prevents accurate image orientation using traditional cryo-EM. Our approach should be adaptable to other DNA-binding proteins as well as small proteins fused to DNA-binding domains.
| S-EPMC7956247 | biostudies-literature
Project description:Particle identification and selection, which is a prerequisite for high-resolution structure determination of biological macromolecules via single-particle cryo-electron microscopy poses a major bottleneck for automating the steps of structure determination. Here, we present a generalized deep learning tool, CASSPER, for the automated detection and isolation of protein particles in transmission microscope images. This deep learning tool uses Semantic Segmentation and a collection of visually prepared training samples to capture the differences in the transmission intensities of protein, ice, carbon, and other impurities found in the micrograph. CASSPER is a semantic segmentation based method that does pixel-level classification and completely eliminates the need for manual particle picking. Integration of Contrast Limited Adaptive Histogram Equalization (CLAHE) in CASSPER enables high-fidelity particle detection in micrographs with variable ice thickness and contrast. A generalized CASSPER model works with high efficiency on unseen datasets and can potentially pick particles on-the-fly, enabling data processing automation.
| S-EPMC7884729 | biostudies-literature
Project description:Bacteria downregulate their ribosomal activity through dimerization of 70S ribosomes, yielding inactive 100S complexes. In Escherichia coli, dimerization is mediated by the hibernation promotion factor (HPF) and ribosome modulation factor. Here we report the cryo-electron microscopy study on 100S ribosomes from Lactococcus lactis and a dimerization mechanism involving a single protein: HPFlong. The N-terminal domain of HPFlong binds at the same site as HPF in Escherichia coli 100S ribosomes. Contrary to ribosome modulation factor, the C-terminal domain of HPFlong binds exactly at the dimer interface. Furthermore, ribosomes from Lactococcus lactis do not undergo conformational changes in the 30S head domains upon binding of HPFlong, and the Shine-Dalgarno sequence and mRNA entrance tunnel remain accessible. Ribosome activity is blocked by HPFlong due to the inhibition of mRNA recognition by the platform binding center. Phylogenetic analysis of HPF proteins suggests that HPFlong-mediated dimerization is a widespread mechanism of ribosome hibernation in bacteria.When bacteria enter the stationary growth phase, protein translation is suppressed via the dimerization of 70S ribosomes into inactive complexes. Here the authors provide a structural basis for how the dual domain hibernation promotion factor promotes ribosome dimerization and hibernation in bacteria.
| S-EPMC5620043 | biostudies-literature
Project description:Single-particle cryo-electron microscopy (cryo-EM) has become a mainstream tool for the structural determination of biological macromolecular complexes. However, high-resolution cryo-EM reconstruction often requires hundreds of thousands of single-particle images. Particle extraction from experimental micrographs thus can be laborious and presents a major practical bottleneck in cryo-EM structural determination. Existing computational methods for particle picking often use low-resolution templates for particle matching, making them susceptible to reference-dependent bias. It is critical to develop a highly efficient template-free method for the automatic recognition of particle images from cryo-EM micrographs.We developed a deep learning-based algorithmic framework, DeepEM, for single-particle recognition from noisy cryo-EM micrographs, enabling automated particle picking, selection and verification in an integrated fashion. The kernel of DeepEM is built upon a convolutional neural network (CNN) composed of eight layers, which can be recursively trained to be highly "knowledgeable". Our approach exhibits an improved performance and accuracy when tested on the standard KLH dataset. Application of DeepEM to several challenging experimental cryo-EM datasets demonstrated its ability to avoid the selection of un-wanted particles and non-particles even when true particles contain fewer features.The DeepEM methodology, derived from a deep CNN, allows automated particle extraction from raw cryo-EM micrographs in the absence of a template. It demonstrates an improved performance, objectivity and accuracy. Application of this novel method is expected to free the labor involved in single-particle verification, significantly improving the efficiency of cryo-EM data processing.
| S-EPMC5521087 | biostudies-literature