Project description:Macromolecular structure determination by electron cryo-microscopy (cryo-EM) is limited by the alignment of noisy images of individual particles. Because smaller particles have weaker signals, alignment errors impose size limitations on its applicability. Here, we explore how image alignment is improved by the application of deep learning to exploit prior knowledge about biological macromolecular structures that would otherwise be difficult to express mathematically. We train a denoising convolutional neural network on pairs of half-set reconstructions from the electron microscopy data bank (EMDB) and use this denoiser as an alternative to a commonly used smoothness prior. We demonstrate that this approach, which we call Blush regularization, yields better reconstructions than do existing algorithms, in particular for data with low signal-to-noise ratios. The reconstruction of a protein-nucleic acid complex with a molecular weight of 40 kDa, which was previously intractable, illustrates that denoising neural networks will expand the applicability of cryo-EM structure determination for a wide range of biological macromolecules.
Project description:The formation of amyloid filaments is characteristic of various degenerative diseases. Recent breakthroughs in electron cryo-microscopy (cryo-EM) have led to atomic structure determination of multiple amyloid filaments, both of filaments assembled in vitro from recombinant proteins, and of filaments extracted from diseased tissue. These observations revealed that a single protein may adopt multiple different amyloid folds, and that in vitro assembly does not necessarily lead to the same filaments as those observed in disease. In order to develop relevant model systems for disease, and ultimately to better understand the molecular mechanisms of disease, it will be important to determine which factors determine the formation of distinct amyloid folds. High-throughput cryo-EM, in which structure determination becomes a tool rather than a project in itself, will facilitate the screening of large numbers of in vitro assembly conditions. To this end, we describe a new filament picking algorithm based on the Topaz approach, and we outline image processing strategies in Relion that enable atomic structure determination of amyloids within days.
Project description:Three-dimensional (3D) structure determination by single-particle analysis of cryo-electron microscopy (cryo-EM) images requires many parameters to be determined from extremely noisy data. This makes the method prone to overfitting, that is, when structures describe noise rather than signal, in particular near their resolution limit where noise levels are highest. Cryo-EM structures are typically filtered using ad hoc procedures to prevent overfitting, but the tuning of arbitrary parameters may lead to subjectivity in the results. I describe a Bayesian interpretation of cryo-EM structure determination, where smoothness in the reconstructed density is imposed through a Gaussian prior in the Fourier domain. The statistical framework dictates how data and prior knowledge should be combined, so that the optimal 3D linear filter is obtained without the need for arbitrariness and objective resolution estimates may be obtained. Application to experimental data indicates that the statistical approach yields more reliable structures than existing methods and is capable of detecting smaller classes in data sets that contain multiple different structures.
Project description:Cryo-EM structure determination of protein-free RNAs has remained difficult with most attempts yielding low to moderate resolution and lacking nucleotide-level detail. These difficulties are compounded for small RNAs as cryo-EM is inherently more difficult for lower molecular weight macromolecules. Here we present a strategy for fusing small RNAs to a group II intron that yields high resolution structures of the appended RNA. We demonstrate this technology by determining the structures of the 86-nucleotide (nt) thiamine pyrophosphate (TPP) riboswitch aptamer domain and the recently described 210-nt raiA bacterial non-coding RNA involved in sporulation and biofilm formation. In the case of the TPP riboswitch aptamer domain, the scaffolding approach allowed visualization of the riboswitch ligand binding pocket at 2.5 Å resolution. We also determined the structure of the ligand-free apo state and observe that the aptamer domain of the riboswitch adopts an open Y-shaped conformation in the absence of ligand. Using this scaffold approach, we determined the structure of raiA at 2.5 Å in the core. Our versatile scaffolding strategy enables efficient RNA structure determination for a broad range of small to moderate-sized RNAs, which were previously intractable for high-resolution cryo-EM studies.
Project description:The electron cryo-microscopy (cryoEM) method MicroED has been rapidly developing. In this review we highlight some of the key steps in MicroED from crystal analysis to structure determination. We compare and contrast MicroED and the latest X-ray based diffraction method the X-ray free-electron laser (XFEL). Strengths and shortcomings of both MicroED and XFEL are discussed. Finally, all current MicroED structures are tabulated with a view to the future.
Project description:Cryo-electron microscopy (cryo-EM) of small membrane proteins, such as G protein-coupled receptors (GPCRs), remains challenging. Pushing the performance boundaries of the technique requires quantitative knowledge about the contribution of multiple factors. Here, we present an in-depth analysis and optimization of the main experimental parameters in cryo-EM. We combined actual structural studies with methods development to quantify the effects of the Volta phase plate, zero-loss energy filtering, objective lens aperture, defocus magnitude, total exposure, and grid type. By using this information to carefully maximize the experimental performance, it is now possible to routinely determine GPCR structures at resolutions better than 2.5 Å. The improved fidelity of such maps enables the building of better atomic models and will be crucial for the future expansion of cryo-EM into the structure-based drug design domain. The optimization guidelines given here are not limited to GPCRs and can be applied directly to other small proteins.
Project description:Despite the recent rapid progress in cryo-electron microscopy (cryo-EM), there still exist ample opportunities for improvement in sample preparation. Macromolecular complexes may disassociate or adopt nonrandom orientations against the extended air-water interface that exists for a short time before the sample is frozen. We designed a hollow support structure using 3D DNA origami to protect complexes from the detrimental effects of cryo-EM sample preparation. For a first proof-of-principle, we concentrated on the transcription factor p53, which binds to specific DNA sequences on double-stranded DNA. The support structures spontaneously form monolayers of preoriented particles in a thin film of water, and offer advantages in particle picking and sorting. By controlling the position of the binding sequence on a single helix that spans the hollow support structure, we also sought to control the orientation of individual p53 complexes. Although the latter did not yet yield the desired results, the support structures did provide partial information about the relative orientations of individual p53 complexes. We used this information to calculate a tomographic 3D reconstruction, and refined this structure to a final resolution of ∼15 Å. This structure settles an ongoing debate about the symmetry of the p53 tetramer bound to DNA.
Project description:Cryo-EM structure determination of protein-free RNAs has remained difficult with most attempts yielding low to moderate resolution and lacking nucleotide-level detail. These difficulties are compounded for small RNAs as cryo-EM is inherently more difficult for lower molecular weight macromolecules. Here we present a strategy for fusing small RNAs to a group II intron that yields high resolution structures of the appended RNA, which we demonstrate with the 86-nucleotide thiamine pyrophosphate (TPP) riboswitch, and visualizing the riboswitch ligand binding pocket at 2.5 Å resolution. We also determined the structure of the ligand-free apo state and observe that the aptamer domain of the riboswitch undergoes a large-scale conformational change upon ligand binding, illustrating how small molecule binding to an RNA can induce large effects on gene expression. This study both sets a new standard for cryo-EM riboswitch visualization and offers a versatile strategy applicable to a broad range of small to moderate-sized RNAs, which were previously intractable for high-resolution cryo-EM studies.
Project description:Cryogenic electron microscopy has become an essential tool for structure determination of biological macromolecules. In practice, the difficulty to reliably prepare samples with uniform ice thickness still represents a barrier for routine high-resolution imaging and limits the current throughput of the technique. We show that a nanofluidic sample support with well-defined geometry can be used to prepare cryo-EM specimens with reproducible ice thickness from picoliter sample volumes. The sample solution is contained in electron-transparent nanochannels that provide uniform thickness gradients without further optimisation and eliminate the potentially destructive air-water interface. We demonstrate the possibility to perform high-resolution structure determination with three standard protein specimens. Nanofabricated sample supports bear potential to automate the cryo-EM workflow, and to explore new frontiers for cryo-EM applications such as time-resolved imaging and high-throughput screening.