Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the current coronavirus disease 2019 (COVID-19) pandemic. A major virulence factor of SARS-CoVs is the ...nonstructural protein 1 (Nsp1), which suppresses host gene expression by ribosome association. Here, we show that Nsp1 from SARS-CoV-2 binds to the 40
ribosomal subunit, resulting in shutdown of messenger RNA (mRNA) translation both in vitro and in cells. Structural analysis by cryo-electron microscopy of in vitro-reconstituted Nsp1-40
and various native Nsp1-40
and -80
complexes revealed that the Nsp1 C terminus binds to and obstructs the mRNA entry tunnel. Thereby, Nsp1 effectively blocks retinoic acid-inducible gene I-dependent innate immune responses that would otherwise facilitate clearance of the infection. Thus, the structural characterization of the inhibitory mechanism of Nsp1 may aid structure-based drug design against SARS-CoV-2.
Abstract Tigecycline is widely used for treating complicated bacterial infections for which there are no effective drugs. It inhibits bacterial protein translation by blocking the ribosomal A-site. ...However, even though it is also cytotoxic for human cells, the molecular mechanism of its inhibition remains unclear. Here, we present cryo-EM structures of tigecycline-bound human mitochondrial 55S, 39S, cytoplasmic 80S and yeast cytoplasmic 80S ribosomes. We find that at clinically relevant concentrations, tigecycline effectively targets human 55S mitoribosomes, potentially, by hindering A-site tRNA accommodation and by blocking the peptidyl transfer center. In contrast, tigecycline does not bind to human 80S ribosomes under physiological concentrations. However, at high tigecycline concentrations, in addition to blocking the A-site, both human and yeast 80S ribosomes bind tigecycline at another conserved binding site restricting the movement of the L1 stalk. In conclusion, the observed distinct binding properties of tigecycline may guide new pathways for drug design and therapy.
Translational stalling events that result in ribosome collisions induce Ribosome-associated Quality Control (RQC) in order to degrade potentially toxic truncated nascent proteins. For RQC induction, ...the collided ribosomes are first marked by the Hel2/ZNF598 E3 ubiquitin ligase to recruit the RQT complex for subunit dissociation. In yeast, uS10 is polyubiquitinated by Hel2, whereas eS10 is preferentially monoubiquitinated by ZNF598 in human cells for an unknown reason. Here, we characterize the ubiquitination activity of ZNF598 and its importance for human RQT-mediated subunit dissociation using the endogenous XBP1u and poly(A) translation stallers. Cryo-EM analysis of a human collided disome reveals a distinct composite interface, with substantial differences to yeast collided disomes. Biochemical analysis of collided ribosomes shows that ZNF598 forms K63-linked polyubiquitin chains on uS10, which are decisive for mammalian RQC initiation. The human RQT (hRQT) complex composed only of ASCC3, ASCC2 and TRIP4 dissociates collided ribosomes dependent on the ATPase activity of ASCC3 and the ubiquitin-binding capacity of ASCC2. The hRQT-mediated subunit dissociation requires the K63-linked polyubiquitination of uS10, while monoubiquitination of eS10 or uS10 is not sufficient. Therefore, we conclude that ZNF598 functionally marks collided mammalian ribosomes by K63-linked polyubiquitination of uS10 for the trimeric hRQT complex-mediated subunit dissociation.
Translation of aberrant mRNAs induces ribosomal collisions, thereby triggering pathways for mRNA and nascent peptide degradation and ribosomal rescue. Here we use sucrose gradient fractionation ...combined with quantitative proteomics to systematically identify proteins associated with collided ribosomes. This approach identified Endothelial differentiation-related factor 1 (EDF1) as a novel protein recruited to collided ribosomes during translational distress. Cryo-electron microscopic analyses of EDF1 and its yeast homolog Mbf1 revealed a conserved 40S ribosomal subunit binding site at the mRNA entry channel near the collision interface. EDF1 recruits the translational repressors GIGYF2 and EIF4E2 to collided ribosomes to initiate a negative-feedback loop that prevents new ribosomes from translating defective mRNAs. Further, EDF1 regulates an immediate-early transcriptional response to ribosomal collisions. Our results uncover mechanisms through which EDF1 coordinates multiple responses of the ribosome-mediated quality control pathway and provide novel insights into the intersection of ribosome-mediated quality control with global transcriptional regulation.
The rixosome defined in Schizosaccharomyces pombe and humans performs diverse roles in pre‐ribosomal RNA processing and gene silencing. Here, we isolate and describe the conserved rixosome from ...Chaetomium thermophilum, which consists of two sub‐modules, the sphere‐like Rix1‐Ipi3‐Ipi1 and the butterfly‐like Las1‐Grc3 complex, connected by a flexible linker. The Rix1 complex of the rixosome utilizes Sda1 as landing platform on nucleoplasmic pre‐60S particles to wedge between the 5S rRNA tip and L1‐stalk, thereby facilitating the 180° rotation of the immature 5S RNP towards its mature conformation. Upon rixosome positioning, the other sub‐module with Las1 endonuclease and Grc3 polynucleotide‐kinase can reach a strategic position at the pre‐60S foot to cleave and 5′ phosphorylate the nearby ITS2 pre‐rRNA. Finally, inward movement of the L1 stalk permits the flexible Nop53 N‐terminus with its AIM motif to become positioned at the base of the L1‐stalk to facilitate Mtr4 helicase‐exosome participation for completing ITS2 removal. Thus, the rixosome structure elucidates the coordination of two central ribosome biogenesis events, but its role in gene silencing may adapt similar strategies.
Synopsis
The rixosome is involved in ribosome biogenesis and gene silencing. Its cryo‐EM structure explains how it can participate in pre‐60S ribosome maturation during 5S RNP rotation and ITS2 processing.
Rix1 sub‐module of the rixosome functions as central hub to trigger the 5S RNP rotation on pre‐60S particles.
Las1‐Grc3 endonuclease flexibly attached to the rixosome can be strategically positioned at the pre‐60S foot to perform ITS2 processing.
The rixosome is involved in ribosome biogenesis and gene silencing. Its cryo‐EM structure explains how it can participate in pre‐60S ribosome maturation during 5S RNP rotation and ITS2 processing.
For understanding generic documents, information like font sizes, column layout, and generally the positioning of words may carry semantic information that is crucial for solving a downstream ...document intelligence task. Our novel BERTgrid, which is based on Chargrid by Katti et al. (2018), represents a document as a grid of contextualized word piece embedding vectors, thereby making its spatial structure and semantics accessible to the processing neural network. The contextualized embedding vectors are retrieved from a BERT language model. We use BERTgrid in combination with a fully convolutional network on a semantic instance segmentation task for extracting fields from invoices. We demonstrate its performance on tabulated line item and document header field extraction.
BERT is a popular language model whose main pre-training task is to fill in the blank, i.e., predicting a word that was masked out of a sentence, based on the remaining words. In some applications, ...however, having an additional context can help the model make the right prediction, e.g., by taking the domain or the time of writing into account. This motivates us to advance the BERT architecture by adding a global state for conditioning on a fixed-sized context. We present our two novel approaches and apply them to an industry use-case, where we complete fashion outfits with missing articles, conditioned on a specific customer. An experimental comparison to other methods from the literature shows that our methods improve personalization significantly.
The process of reconstructing experiences from human brain activity offers a unique lens into how the brain interprets and represents the world. In this paper, we introduce a method for ...reconstructing music from brain activity, captured using functional magnetic resonance imaging (fMRI). Our approach uses either music retrieval or the MusicLM music generation model conditioned on embeddings derived from fMRI data. The generated music resembles the musical stimuli that human subjects experienced, with respect to semantic properties like genre, instrumentation, and mood. We investigate the relationship between different components of MusicLM and brain activity through a voxel-wise encoding modeling analysis. Furthermore, we discuss which brain regions represent information derived from purely textual descriptions of music stimuli. We provide supplementary material including examples of the reconstructed music at https://google-research.github.io/seanet/brain2music
Over the past years, fashion-related challenges have gained a lot of attention in the research community. Outfit generation and recommendation, i.e., the composition of a set of items of different ...types (e.g., tops, bottom, shoes, accessories) that go well together, are among the most challenging ones. That is because items have to be both compatible amongst each other and also personalized to match the taste of the customer. Recently there has been a plethora of work targeted at tackling these problems by adopting various techniques and algorithms from the machine learning literature. However, to date, there is no extensive comparison of the performance of the different algorithms for outfit generation and recommendation. In this paper, we close this gap by providing a broad evaluation and comparison of various algorithms, including both personalized and non-personalized approaches, using online, real-world user data from one of Europe's largest fashion stores. We present the adaptations we made to some of those models to make them suitable for personalized outfit generation. Moreover, we provide insights for models that have not yet been evaluated on this task, specifically, GPT, BERT and Seq-to-Seq LSTM.
Video-to-music generation demands both a temporally localized high-quality listening experience and globally aligned video-acoustic signatures. While recent music generation models excel at the ...former through advanced audio codecs, the exploration of video-acoustic signatures has been confined to specific visual scenarios. In contrast, our research confronts the challenge of learning globally aligned signatures between video and music directly from paired music and videos, without explicitly modeling domain-specific rhythmic or semantic relationships. We propose V2Meow, a video-to-music generation system capable of producing high-quality music audio for a diverse range of video input types using a multi-stage autoregressive model. Trained on 5k hours of music audio clips paired with video frames mined from in-the-wild music videos, V2Meow is competitive with previous domain-specific models when evaluated in a zero-shot manner. It synthesizes high-fidelity music audio waveforms solely by conditioning on pre-trained general-purpose visual features extracted from video frames, with optional style control via text prompts. Through both qualitative and quantitative evaluations, we demonstrate that our model outperforms various existing music generation systems in terms of visual-audio correspondence and audio quality. Music samples are available at tinyurl.com/v2meow.
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