The Short- and Long-Range RNA-RNA Interactome of SARS-CoV-2

Molecular Cell, Год журнала: 2020, Номер 80(6), С. 1067 - 1077.e5

Опубликована: Ноя. 5, 2020

The Coronaviridae is a family of positive-strand RNA viruses that includes SARS-CoV-2, the etiologic agent COVID-19 pandemic. Bearing largest single-stranded genomes in nature, coronaviruses are critically dependent on long-distance RNA-RNA interactions to regulate viral transcription and replication pathways. Here we experimentally mapped vivo interactome full-length SARS-CoV-2 genome subgenomic mRNAs. We uncovered network spanning tens thousands nucleotides. These reveal subgenomes adopt alternative topologies inside cells engage different with host RNAs. Notably, discovered long-range interaction, FSE-arch, encircles programmed ribosomal frameshifting element. FSE-arch conserved related MERS-CoV under purifying selection. Our findings illuminate structure-based mechanisms governing replication, discontinuous transcription, translation will aid future efforts develop antiviral strategies.

Язык: Английский

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The architecture of the SARS-CoV-2 RNA genome inside virion

Nature Communications, Год журнала: 2021, Номер 12(1)

Опубликована: Июнь 24, 2021

Abstract SARS-CoV-2 carries the largest single-stranded RNA genome and is causal pathogen of ongoing COVID-19 pandemic. How folded in virion remains unknown. To fill knowledge gap facilitate structure-based drug development, we develop a situ conformation sequencing technology, named vRIC-seq, for probing viral structure unbiasedly. Using vRIC-seq data, reconstruct tertiary reveal surprisingly “unentangled globule” conformation. We uncover many long-range duplexes higher-order junctions, both which are under purifying selections contribute to sequential package genome. Unexpectedly, D614G other two accompanying mutations may remodel into more stable forms. Lastly, structure-guided design potent small interfering RNAs can obliterate Vero cells. Overall, our work provides framework studying structure, function, dynamics emerging deadly viruses.

Язык: Английский

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Secondary structural ensembles of the SARS-CoV-2 RNA genome in infected cells

Nature Communications, Год журнала: 2022, Номер 13(1)

Опубликована: Март 2, 2022

SARS-CoV-2 is a betacoronavirus with single-stranded, positive-sense, 30-kilobase RNA genome responsible for the ongoing COVID-19 pandemic. Although population average structure models of were recently reported, there little experimental data on native structural ensembles, and most structures lack functional characterization. Here we report secondary heterogeneity entire in two lines infected cells at single nucleotide resolution. Our results reveal alternative conformations across critical frameshifting stimulation element (FSE) that are drastically different from prevailing models. Importantly, find this ensemble promotes rates much higher than canonical minimal FSE similar to ribosome profiling studies. highlight value studying its full length cellular context. The genomic detailed here lay groundwork coronavirus biology will guide design RNA-based therapeutics.

Язык: Английский

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Advances and opportunities in RNA structure experimental determination and computational modeling

Nature Methods, Год журнала: 2022, Номер 19(10), С. 1193 - 1207

Опубликована: Окт. 1, 2022

Язык: Английский

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SARS-CoV-2 biology and host interactions

Nature Reviews Microbiology, Год журнала: 2024, Номер 22(4), С. 206 - 225

Опубликована: Янв. 15, 2024

Язык: Английский

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RNA secondary structure packages evaluated and improved by high-throughput experiments

Nature Methods, Год журнала: 2022, Номер 19(10), С. 1234 - 1242

Опубликована: Окт. 1, 2022

Язык: Английский

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Cepharanthine analogs mining and genomes of Stephania accelerate anti-coronavirus drug discovery

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Фев. 20, 2024

Abstract Cepharanthine is a secondary metabolite isolated from Stephania . It has been reported that it anti-conronaviruses activities including severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Here, we assemble three genomes ( S. japonica , yunnanensis and cepharantha ), propose the cepharanthine biosynthetic pathway, assess antiviral potential of compounds involved in pathway. Among genomes, near telomere-to-telomere assembly with one remaining gap, have chromosome-level assemblies. Following by gene mining metabolomics analysis, identify seven analogs broad-spectrum anti-coronavirus activities, SARS-CoV-2, Guangxi pangolin-CoV (GX_P2V), swine diarrhoea coronavirus (SADS-CoV), porcine epidemic diarrhea virus (PEDV). We also show two other genera, Nelumbo Thalictrum can produce analogs, thus for compound discovery. Results generated this study could accelerate drug

Язык: Английский

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Current Strategies of Antiviral Drug Discovery for COVID-19

Frontiers in Molecular Biosciences, Год журнала: 2021, Номер 8

Опубликована: Май 13, 2021

SARS-CoV-2 belongs to the family of enveloped, single-strand RNA viruses known as Betacoronavirus in Coronaviridae, first reported late 2019 China. It has since been circulating world-wide, causing COVID-19 epidemic with high infectivity and fatality rates. As beginning April 2021, pandemic infected more than 130 million people led 2.84 deaths. Given severity epidemic, scientists from academia industry are rushing identify antiviral strategies combat disease. There several drugs for coronaviruses including empirical testing drugs, large-scale phenotypic screening compound libraries target-based drug discovery. To date, an increasing number have shown anti-coronavirus activities vitro vivo, but only remdesivir neutralizing antibodies approved by US FDA treating COVID-19. However, remdesivir's clinical effects controversial new still urgently needed. We will discuss current status discovery efforts against potential future directions. With ever-increasing movability human population globalization world economy, emerging reemerging viral infectious diseases seriously threaten public health. Particularly past ongoing outbreaks cause respiratory, enteric, hepatic neurological animals (Woo et al., 2009). The coronavirus (HCoV) strains (HCoV-229E, HCoV-OC43, HCoV-NL63, HCoV-HKU1) usually common cold mild, self-limiting upper respiratory tract infections. By contrast, emergence three deadly betacoronaviruses, middle east syndrome (MERS) (Zaki 2012), severe acute (SARS-CoV) (Lee 2003), (Jin 2020a) highlight need treatment is etiological agent disease named World Health Organization (WHO) (Zhu N. 2020). This manifests either asymptomatic infection or a mild pneumonia. causes extent morbidity mortality whole world, especially regions out Similar SARS MERS, CoV-2 genome encodes four structural proteins, sixteen non-structural proteins (nsp) accessory proteins. include spike (S), envelope (E), membrane (M), nucleoprotein (N). glycoprotein directly recognizes engages cellular receptors during entry. papain-like protease (PLpro), 3-chymotrypsin-like (3CLpro), helicase, RNA-dependent polymerase (RdRp) key enzymes involved transcription replication. were considered attractive targets develop agents (Zumla 2016). catalytic sites SARS-CoV2 share similarities CoV MERS genomic sequences (Morse Besides, structures drug-binding pockets highly conserved among Therefore, it follows naturally that existing anti-SARS-CoV anti-MERS targeting these can be repurposed SARS-CoV-2. Based on previous studies SARS-CoV MERS-CoV, anticipated therapeutics used control prevent (Li de Clercq, 2020; Wang 2020c; Ita, 2021), small-molecule peptides, monoclonal antibodies. urgency outbreak, here we development based which derived.

Язык: Английский

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Predicting dynamic cellular protein–RNA interactions by deep learning using in vivo RNA structures

Cell Research, Год журнала: 2021, Номер 31(5), С. 495 - 516

Опубликована: Фев. 23, 2021

Interactions with RNA-binding proteins (RBPs) are integral to RNA function and cellular regulation, dynamically reflect specific conditions. However, presently available tools for predicting RBP-RNA interactions employ sequence and/or predicted structures, therefore do not capture their condition-dependent nature. Here, after profiling transcriptome-wide in vivo secondary structures seven cell types, we developed PrismNet, a deep learning tool that integrates experimental structure data RBP binding matched cells accurately predict dynamic various PrismNet results 168 RBPs support its utility both understanding CLIP-seq largely extending such interaction analyze additional types. Further, employs an "attention" strategy computationally identify exact RBP-binding nucleotides, discovered enrichment among sites structure-changing variants (riboSNitches), which can link genetic diseases dysregulated bindings. Our rich learning-based prediction provide access previously inaccessible layer of cell-type-specific interactions, clear treating human diseases.

Язык: Английский

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A map of the SARS-CoV-2 RNA structurome

NAR Genomics and Bioinformatics, Год журнала: 2021, Номер 3(2)

Опубликована: Апрель 9, 2021

Abstract SARS-CoV-2 has exploded throughout the human population. To facilitate efforts to gain insights into biology and target virus therapeutically, it is essential have a roadmap of likely functional regions embedded in its RNA genome. In this report, we used bioinformatics approach, ScanFold, deduce local structural landscape genome with highest likelihood being functional. We recapitulate previously-known elements structure provide model for folding an frameshift signal. Our results find that greatly enriched unusually stable evolutionarily ordered structure, which provides large reservoir potential drug targets RNA-binding small molecules. Results are enhanced via re-analyses publicly-available genome-wide biochemical probing datasets broadly agreement our models. Additionally, ScanFold was updated incorporate experimental data as constraints analysis comparisons between other modelling approaches. Ultimately, able identify eight highly structured/conserved motifs agree data, without explicitly using these data. All made available public database (the RNAStructuromeDB: https://structurome.bb.iastate.edu/sars-cov-2) readily viewable at https://structurome.bb.iastate.edu/sars-cov-2-global-model-comparisons.

Язык: Английский

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