Cryo electron micrographs of Pol delta-PCNA-DNA-FEN1 sample
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ABSTRACT:
SUBMITTER: Claudia Lancey
PROVIDER: EMPIAR-10823 | biostudies-other |
REPOSITORIES: biostudies-other
Publications
Structure of the processive human Pol δ holoenzyme.
Lancey Claudia C Tehseen Muhammad M Raducanu Vlad-Stefan VS Rashid Fahad F Merino Nekane N Ragan Timothy J TJ Savva Christos G CG Zaher Manal S MS Shirbini Afnan A Blanco Francisco J FJ Hamdan Samir M SM De Biasio Alfredo A
Nature communications 20200228 1
In eukaryotes, DNA polymerase δ (Pol δ) bound to the proliferating cell nuclear antigen (PCNA) replicates the lagging strand and cooperates with flap endonuclease 1 (FEN1) to process the Okazaki fragments for their ligation. We present the high-resolution cryo-EM structure of the human processive Pol δ-DNA-PCNA complex in the absence and presence of FEN1. Pol δ is anchored to one of the three PCNA monomers through the C-terminal domain of the catalytic subunit. The catalytic core sits on top of ...[more]
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| EMPIAR-10934 | biostudies-other
Project description:Y-family DNA polymerase κ (Pol κ) can replicate damaged DNA templates to rescue stalled replication forks. Access of Pol κ to DNA damage sites is facilitated by its interaction with the processivity clamp PCNA and is regulated by PCNA mono-ubiquitylation. Here, we present cryo-EM reconstructions of human Pol κ bound to DNA, an incoming nucleotide, and wild type or mono-ubiquitylated PCNA (Ub-PCNA). In both reconstructions, the internal PIP-box adjacent to the Pol κ Polymerase-Associated Domain (PAD) docks the catalytic core to one PCNA protomer in an angled orientation, bending the DNA exiting the Pol κ active site through PCNA, while Pol κ C-terminal domain containing two Ubiquitin Binding Zinc Fingers (UBZs) is invisible, in agreement with disorder predictions. The ubiquitin moieties are partly flexible and extend radially away from PCNA, with the ubiquitin at the Pol κ-bound protomer appearing more rigid. Activity assays suggest that, when the internal PIP-box interaction is lost, Pol κ is retained on DNA by a secondary interaction between the UBZs and the ubiquitins flexibly conjugated to PCNA. Our data provide a structural basis for the recruitment of a Y-family TLS polymerase to sites of DNA damage.
| S-EPMC8526622 | biostudies-literature
Project description:BackgroundIdentification and selection of protein particles in cryo-electron micrographs is an important step in single particle analysis. In this study, we developed a deep learning-based particle picking network to automatically detect particle centers from cryoEM micrographs. This is a challenging task due to the nature of cryoEM data, having low signal-to-noise ratios with variable particle sizes, shapes, distributions, grayscale variations as well as other undesirable artifacts.ResultsWe propose a double convolutional neural network (CNN) cascade for automated detection of particles in cryo-electron micrographs. This approach, entitled Deep Regression Picker Network or "DRPnet", is simple but very effective in recognizing different particle sizes, shapes, distributions and grayscale patterns corresponding to 2D views of 3D particles. Particles are detected by the first network, a fully convolutional regression network (FCRN), which maps the particle image to a continuous distance map that acts like a probability density function of particle centers. Particles identified by FCRN are further refined to reduce false particle detections by the second classification CNN. DRPnet's first CNN pretrained with only a single cryoEM dataset can be used to detect particles from different datasets without retraining. Compared to RELION template-based autopicking, DRPnet results in better particle picking performance with drastically reduced user interactions and processing time. DRPnet also outperforms the state-of-the-art particle picking networks in terms of the supervised detection evaluation metrics recall, precision, and F-measure. To further highlight quality of the picked particle sets, we compute and present additional performance metrics assessing the resulting 3D reconstructions such as number of 2D class averages, efficiency/angular coverage, Rosenthal-Henderson plots and local/global 3D reconstruction resolution.ConclusionDRPnet shows greatly improved time-savings to generate an initial particle dataset compared to manual picking, followed by template-based autopicking. Compared to other networks, DRPnet has equivalent or better performance. DRPnet excels on cryoEM datasets that have low contrast or clumped particles. Evaluating other performance metrics, DRPnet is useful for higher resolution 3D reconstructions with decreased particle numbers or unknown symmetry, detecting particles with better angular orientation coverage.
| S-EPMC7869254 | biostudies-literature
Project description:Cryo-electron microscopy is a popular method for the determination of protein structures; however, identifying a sufficient number of particles for analysis can take months of manual effort. Current computational approaches find many false positives and require ad hoc postprocessing, especially for unusually shaped particles. To address these shortcomings, we develop Topaz, an efficient and accurate particle-picking pipeline using neural networks trained with a general-purpose positive-unlabeled learning method. This framework enables particle detection models to be trained with few sparsely labeled particles and no labeled negatives. Topaz retrieves many more real particles than conventional picking methods while maintaining low false-positive rates, is capable of picking challenging unusually shaped proteins (for example, small, non-globular and asymmetric particles), produces more representative particle sets and does not require post hoc curation. We demonstrate the performance of Topaz on two difficult datasets and three conventional datasets. Topaz is modular, standalone, free and open source ( http://topaz.csail.mit.edu ).
| S-EPMC6858545 | biostudies-literature
Project description:BackgroundDNA polymerase D (PolD) is the representative member of the D family of DNA polymerases. It is an archaea-specific DNA polymerase required for replication and unrelated to other known DNA polymerases. PolD consists of a heterodimer of two subunits, DP1 and DP2, which contain catalytic sites for 3'-5' editing exonuclease and DNA polymerase activities, respectively, with both proteins being mutually required for the full activities of each enzyme. However, the processivity of the replicase holoenzyme has additionally been shown to be enhanced by the clamp molecule proliferating cell nuclear antigen (PCNA), making it crucial to elucidate the interaction between PolD and PCNA on a structural level for a full understanding of its functional relevance. We present here the 3D structure of a PolD-PCNA-DNA complex from Thermococcus kodakarensis using single-particle cryo-electron microscopy (EM).ResultsTwo distinct forms of the PolD-PCNA-DNA complex were identified by 3D classification analysis. Fitting the reported crystal structures of truncated forms of DP1 and DP2 from Pyrococcus abyssi onto our EM map showed the 3D atomic structural model of PolD-PCNA-DNA. In addition to the canonical interaction between PCNA and PolD via PIP (PCNA-interacting protein)-box motif, we found a new contact point consisting of a glutamate residue at position 171 in a β-hairpin of PCNA, which mediates interactions with DP1 and DP2. The DNA synthesis activity of a mutant PolD with disruption of the E171-mediated PCNA interaction was not stimulated by PCNA in vitro.ConclusionsBased on our analyses, we propose that glutamate residues at position 171 in each subunit of the PCNA homotrimer ring can function as hooks to lock PolD conformation on PCNA for conversion of its activity. This hook function of the clamp molecule may be conserved in the three domains of life.
| S-EPMC7594292 | biostudies-literature
Project description:Single-particle cryo-electron microscopy (cryo-EM) is a powerful imaging modality capable of visualizing proteins and macromolecular complexes at near-atomic resolution. The low electron-doses used to prevent radiation damage to the biological samples, however, result in images where the power of the noise is 100 times greater than the power of the signal. To overcome these low signal-to-noise ratios (SNRs), hundreds of thousands of particle projections are averaged to determine the three-dimensional structure of the molecule of interest. The sampling requirements of high-resolution imaging impose limitations on the pixel sizes that can be used for acquisition, limiting the size of the field of view and requiring data collection sessions of several days to accumulate sufficient numbers of particles. Meanwhile, recent image super-resolution (SR) techniques based on neural networks have shown state-of-the-art performance on natural images. Building on these advances, here, we present a multiple-image SR algorithm based on deep internal learning designed specifically to work under low-SNR conditions. Our approach leverages the internal image statistics of cryo-EM movies and does not require training on ground-truth data. When applied to single-particle datasets of apoferritin and T20S proteasome, we show that the resolution of the 3D structure obtained from SR micrographs can surpass the limits imposed by the imaging system. Our results indicate that the combination of low magnification imaging with in silico image SR has the potential to accelerate cryo-EM data collection by virtue of including more particles in each exposure and doing so without sacrificing resolution.
| S-EPMC10951919 | biostudies-literature
Project description:DNA polymerase ζ (Pol ζ) plays a key role in DNA translesion synthesis (TLS) and mutagenesis in eukaryotes. Previously, a two-subunit Rev3-Rev7 complex had been identified as the minimal assembly required for catalytic activity in vitro. Herein, we show that Saccharomyces cerevisiae Pol ζ binds to the Pol31 and Pol32 subunits of Pol δ, forming a four-subunit Pol ζ(4) complex (Rev3-Rev7-Pol31-Pol32). A [4Fe-4S] cluster in Rev3 is essential for the formation of Pol ζ(4) and damage-induced mutagenesis. Pol32 is indispensible for complex formation, providing an explanation for the long-standing observation that pol32Δ strains are defective for mutagenesis. The Pol31 and Pol32 subunits are also required for proliferating cell nuclear antigen (PCNA)-dependent TLS by Pol ζ as Pol ζ(2) lacks functional interactions with PCNA. Mutation of the C-terminal PCNA-interaction motif in Pol32 attenuates PCNA-dependent TLS in vitro and mutagenesis in vivo. Furthermore, a mutant form of PCNA, encoded by the mutagenesis-defective pol30-113 mutant, fails to stimulate Pol ζ(4) activity, providing an explanation for the observed mutagenesis phenotype. A stable Pol ζ(4) complex can be identified in all phases of the cell cycle suggesting that this complex is not regulated at the level of protein interactions between Rev3-Rev7 and Pol31-Pol32.
| S-EPMC3526297 | biostudies-literature
Project description:BackgroundProliferating cell nuclear antigen (PCNA), a ring-shaped homotrimer complex, promotes DNA replication via binding to DNA polymerase. Trimerized PCNA is critical for DNA replication. Enhancer of zeste homologue 2 (EZH2), which primarily acts as a histone methyltransferase, is essential for proliferation. However, how EZH2 promotes proliferation by controlling DNA replication through PCNA remains elusive.ResultsHere, we showed that low EZH2 levels repressed the proliferation of human dental pulp cells (hDPCs). The EZH2 protein level was dramatically upregulated in hDPCs at S phase in the absence of H3K27 trimethylation. Molecularly, EZH2 interacted with PCNA via the PIP box and dimethylated PCNA at lysine 110. Dimethylation of PCNA is essential for stabilization of the PCNA trimer and the binding of DNA polymerase ? to PCNA.ConclusionsOur data reveal the direct interaction between PCNA and EZH2 and a novel mechanism by which EZH2 orchestrates genome duplication.
| S-EPMC6071395 | biostudies-literature