Propagation of Conformational Coordinates Across Angular Space in Mapping the Continuum of States from Cryo-EM Data by Manifold Embedding.

Recent approaches to the study of biological molecules employ manifold learning to single-particle cryo-EM data sets to map the continuum of states of a molecule into a low-dimensional space spanned by eigenvectors or "conformational coordinates". This is done separately for each projection direction (PD) on an angular grid. One important step in deriving a consolidated map of occupancies, from which the free energy landscape of the molecule can be derived, is to propagate the conformational coordinates from a given choice of "anchor PD" across the entire angular space. Even when one eigenvector dominates, its sign might invert from one PD to the next. The propagation of the second eigenvector is particularly challenging when eigenvalues of the second and third eigenvector are closely matched, leading to occasional inversions in their ranking as we move across the angular grid. In the absence of a computational approach, this propagation across the angular space has been done thus far "by hand" using visual clues, thus greatly limiting the general use of the technique. In this work we have developed a method that is able to solve the propagation problem computationally, by using optical flow and a probabilistic graphical model. We demonstrate its utility by selected examples.

Efficient estimation of three-dimensional covariance and its application in the analysis of heterogeneous samples in cryo-electron microscopy.

Single-particle cryogenic electron microscopy (cryo-EM) is a powerful tool for the study of macromolecular structures at high resolution. Classification allows multiple structural states to be extracted and reconstructed from the same sample. One classification approach is via the covariance matrix, which captures the correlation between every pair of voxels. Earlier approaches employ computing-intensive resampling and estimate only the eigenvectors of the matrix, which are then used in a separate fast classification step. We propose an iterative scheme to explicitly estimate the covariance matrix in its entirety. In our approach, the flexibility in choosing the solution domain allows us to examine a part of the molecule in greater detail. Three-dimensional covariance maps obtained in this way from experimental data (cryo-EM images of the eukaryotic pre-initiation complex) prove to be in excellent agreement with conclusions derived by using traditional approaches, revealing in addition the interdependencies of ligand bindings and structural changes.

CTF Challenge: Result summary.

Image formation in bright field electron microscopy can be described with the help of the contrast transfer function (CTF). In this work the authors describe the "CTF Estimation Challenge", called by the Madrid Instruct Image Processing Center (I2PC) in collaboration with the National Center for Macromolecular Imaging (NCMI) at Houston. Correcting for the effects of the CTF requires accurate knowledge of the CTF parameters, but these have often been difficult to determine. In this challenge, researchers have had the opportunity to test their ability in estimating some of the key parameters of the electron microscope CTF on a large micrograph data set produced by well-known laboratories on a wide set of experimental conditions. This work presents the first analysis of the results of the CTF Estimation Challenge, including an assessment of the performance of the different software packages under different conditions, so as to identify those areas of research where further developments would be desirable in order to achieve high-resolution structural information.

Trajectories of the ribosome as a Brownian nanomachine.

A Brownian machine, a tiny device buffeted by the random motions of molecules in the environment, is capable of exploiting these thermal motions for many of the conformational changes in its work cycle. Such machines are now thought to be ubiquitous, with the ribosome, a molecular machine responsible for protein synthesis, increasingly regarded as prototypical. Here we present a new analytical approach capable of determining the free-energy landscape and the continuous trajectories of molecular machines from a large number of snapshots obtained by cryogenic electron microscopy. We demonstrate this approach in the context of experimental cryogenic electron microscope images of a large ensemble of nontranslating ribosomes purified from yeast cells. The free-energy landscape is seen to contain a closed path of low energy, along which the ribosome exhibits conformational changes known to be associated with the elongation cycle. Our approach allows model-free quantitative analysis of the degrees of freedom and the energy landscape underlying continuous conformational changes in nanomachines, including those important for biological function.

Hepatitis-C-virus-like internal ribosome entry sites displace eIF3 to gain access to the 40S subunit.

Hepatitis C virus (HCV) and classical swine fever virus (CSFV) messenger RNAs contain related (HCV-like) internal ribosome entry sites (IRESs) that promote 5'-end independent initiation of translation, requiring only a subset of the eukaryotic initiation factors (eIFs) needed for canonical initiation on cellular mRNAs. Initiation on HCV-like IRESs relies on their specific interaction with the 40S subunit, which places the initiation codon into the P site, where it directly base-pairs with eIF2-bound initiator methionyl transfer RNA to form a 48S initiation complex. However, all HCV-like IRESs also specifically interact with eIF3 (refs 2, 5-7, 9-12), but the role of this interaction in IRES-mediated initiation has remained unknown. During canonical initiation, eIF3 binds to the 40S subunit as a component of the 43S pre-initiation complex, and comparison of the ribosomal positions of eIF3 and the HCV IRES revealed that they overlap, so that their rearrangement would be required for formation of ribosomal complexes containing both components. Here we present a cryo-electron microscopy reconstruction of a 40S ribosomal complex containing eIF3 and the CSFV IRES. Remarkably, although the position and interactions of the CSFV IRES with the 40S subunit in this complex are similar to those of the HCV IRES in the 40S-IRES binary complex, eIF3 is completely displaced from its ribosomal position in the 43S complex, and instead interacts through its ribosome-binding surface exclusively with the apical region of domain III of the IRES. Our results suggest a role for the specific interaction of HCV-like IRESs with eIF3 in preventing ribosomal association of eIF3, which could serve two purposes: relieving the competition between the IRES and eIF3 for a common binding site on the 40S subunit, and reducing formation of 43S complexes, thereby favouring translation of viral mRNAs.

Structure of the mammalian ribosomal 43S preinitiation complex bound to the scanning factor DHX29.

Eukaryotic translation initiation begins with assembly of a 43S preinitiation complex. First, methionylated initiator methionine transfer RNA (Met-tRNAi(Met)), eukaryotic initiation factor (eIF) 2, and guanosine triphosphate form a ternary complex (TC). The TC, eIF3, eIF1, and eIF1A cooperatively bind to the 40S subunit, yielding the 43S preinitiation complex, which is ready to attach to messenger RNA (mRNA) and start scanning to the initiation codon. Scanning on structured mRNAs additionally requires DHX29, a DExH-box protein that also binds directly to the 40S subunit. Here, we present a cryo-electron microscopy structure of the mammalian DHX29-bound 43S complex at 11.6 Å resolution. It reveals that eIF2 interacts with the 40S subunit via its α subunit and supports Met-tRNAi(Met) in an unexpected P/I orientation (eP/I). The structural core of eIF3 resides on the back of the 40S subunit, establishing two principal points of contact, whereas DHX29 binds around helix 16. The structure provides insights into eukaryote-specific aspects of translation, including the mechanism of action of DHX29.

High-resolution cryo-electron microscopy structure of the Trypanosoma brucei ribosome.

Ribosomes, the protein factories of living cells, translate genetic information carried by messenger RNAs into proteins, and are thus involved in virtually all aspects of cellular development and maintenance. The few available structures of the eukaryotic ribosome reveal that it is more complex than its prokaryotic counterpart, owing mainly to the presence of eukaryote-specific ribosomal proteins and additional ribosomal RNA insertions, called expansion segments. The structures also differ among species, partly in the size and arrangement of these expansion segments. Such differences are extreme in kinetoplastids, unicellular eukaryotic parasites often infectious to humans. Here we present a high-resolution cryo-electron microscopy structure of the ribosome of Trypanosoma brucei, the parasite that is transmitted by the tsetse fly and that causes African sleeping sickness. The atomic model reveals the unique features of this ribosome, characterized mainly by the presence of unusually large expansion segments and ribosomal-protein extensions leading to the formation of four additional inter-subunit bridges. We also find additional rRNA insertions, including one large rRNA domain that is not found in other eukaryotes. Furthermore, the structure reveals the five cleavage sites of the kinetoplastid large ribosomal subunit (LSU) rRNA chain, which is known to be cleaved uniquely into six pieces, and suggests that the cleavage is important for the maintenance of the T. brucei ribosome in the observed structure. We discuss several possible implications of the large rRNA expansion segments for the translation-regulation process. The structure could serve as a basis for future experiments aimed at understanding the functional importance of these kinetoplastid-specific ribosomal features in protein-translation regulation, an essential step towards finding effective and safe kinetoplastid-specific drugs.

Cryo-EM structure of the mammalian eukaryotic release factor eRF1-eRF3-associated termination complex.

Eukaryotic translation termination results from the complex functional interplay between two eukaryotic release factors, eRF1 and eRF3, and the ribosome, in which GTP hydrolysis by eRF3 couples codon recognition with peptidyl-tRNA hydrolysis by eRF1. Here, using cryo-electron microscopy (cryo-EM) and flexible fitting, we determined the structure of eRF1-eRF3-guanosine 5'-[ß,γ-imido]triphosphate (GMPPNP)-bound ribosomal pretermination complex (pre-TC), which corresponds to the initial, pre-GTP hydrolysis stage of factor attachment. Our results show that eukaryotic translation termination involves a network of interactions between the two release factors and the ribosome. Our structure provides mechanistic insight into the coordination between GTP hydrolysis by eRF3 and subsequent peptide release by eRF1.

Structural characterization of mRNA-tRNA translocation intermediates.

Cryo-EM analysis of a wild-type Escherichia coli pretranslocational sample has revealed the presence of previously unseen intermediate substates of the bacterial ribosome during the first phase of translocation, characterized by intermediate intersubunit rotations, L1 stalk positions, and tRNA configurations. Furthermore, we describe the domain rearrangements in quantitative terms, which has allowed us to characterize the processivity and coordination of the conformational reorganization of the ribosome, along with the associated changes in tRNA ribosome-binding configuration. The results are consistent with the view of the ribosome as a molecular machine employing Brownian motion to reach a functionally productive state via a series of substates with incremental changes in conformation.

Visualizing the transfer-messenger RNA as the ribosome resumes translation.

Bacterial ribosomes stalled by truncated mRNAs are rescued by transfer-messenger RNA (tmRNA), a dual-function molecule that contains a tRNA-like domain (TLD) and an internal open reading frame (ORF). Occupying the empty A site with its TLD, the tmRNA enters the ribosome with the help of elongation factor Tu and a protein factor called small protein B (SmpB), and switches the translation to its own ORF. In this study, using cryo-electron microscopy, we obtained the first structure of an in vivo-formed complex containing ribosome and the tmRNA at the point where the TLD is accommodated into the ribosomal P site. We show that tmRNA maintains a stable 'arc and fork' structure on the ribosome when its TLD moves to the ribosomal P site and translation resumes on its ORF. Based on the density map, we built an atomic model, which suggests that SmpB interacts with the five nucleotides immediately upstream of the resume codon, thereby determining the correct selection of the reading frame on the ORF of tmRNA.

CLASSIFICATION BY BOOTSTRAPPING IN SINGLE PARTICLE METHODS.

In single-particle reconstruction methods, projections of macromolecules at random orientations are collected. Often, several classes of conformations or binding states coexist in a biological sample, which requires classification, so that each conformation can be reconstructed separately. In this work, we examine bootstrap techniques for classifying the projection data. When these techniques are applied to variance estimation, the projection images (particles) are randomly sampled with replacement from the data set and a bootstrap volume is reconstructed from each sample. In a recent extension of the bootstrap technique to classification, each particle is assigned to a volume in the space spanned by the bootstrap volumes, such that the projection of the assigned volume best matches the particle. In this work we explain the rationale of these techniques by discussing the nature of the bootstrap volumes and provide some statistical analyses.

Definition and estimation of resolution in single-particle reconstructions.

In this paper, we review current practices for establishing the resolution in single-particle reconstructions. The classical Raleigh criterion for the resolution is not applicable in this case, and the resolution is commonly defined by a consistency test, whereby the data set is randomly split in half and the two resulting reconstructions are then compared. Such a procedure, however, may introduce statistical dependence between the two half-sets, which leads to a too optimistic resolution estimate. On the other hand, this overestimation is counteracted by the diminished statistical properties of a mere half of the data set. The "true" resolution of the whole data set can be estimated when the functional relationship between the data size and the resolution is known. We are able to estimate this functional by taking into account the B-factor and the geometry of data collection. Finally, the drawbacks of resolution estimation are entirely avoided by computing the correlation of neighboring voxels in the Fourier domain.